Learner autonomy stands on the top priorities of scholars due to its pivotal role in fostering student-centered learning methods. It empowers the learners to be in charge of their learning process and be the center of...Learner autonomy stands on the top priorities of scholars due to its pivotal role in fostering student-centered learning methods. It empowers the learners to be in charge of their learning process and be the center of attention in language learning education. For this purpose, different AI tools were used and implemented in pedagogy to narrow the divide in promoting learning/teaching approaches. This study aims to gauge the impact of using LLM-ChatGPT to teach EFL learners the present simple tense autonomously via providing automated feedback, and chances for regular drillings without over reliance on teacher. It also aims to investigate the EFL learners’ perception of using LLM-ChatGPT as a reinforcement approach to learner autonomy. A cohort comprising 50 EFL learners would participate in the study and a between subject design method using control and experimental groups would be implemented. The findings of the study indicated that learners who were taught present simple tense’s rule through using LLM-ChatGPT application, with less teacher’s dominance, scored grades similar to those who were taught the same tense’s rule by the teacher (sage on the stage approach). This substantiates the idea that LLM-Chat GPT acts a role akin to teachers in teaching grammatical rules. Moreover, the learners felt that LLM-ChatGPT application had a positive impact on fostering autonomous learning.展开更多
This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations ove...This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.展开更多
Parkinson’s disease(PD)is a progressive neurodegenerative disorder characterized by tremors,rigidity,and decreased movement.PD poses risks to individuals’lives and independence.Early detection of PD is essential bec...Parkinson’s disease(PD)is a progressive neurodegenerative disorder characterized by tremors,rigidity,and decreased movement.PD poses risks to individuals’lives and independence.Early detection of PD is essential because it allows timely intervention,which can slow disease progression and improve outcomes.Manual diagnosis of PD is problematic because it is difficult to capture the subtle patterns and changes that help diagnose PD.In addition,the subjectivity and lack of doctors compared to the number of patients constitute an obstacle to early diagnosis.Artificial intelligence(AI)techniques,especially deep and automated learning models,provide promising solutions to address deficiencies in manual diagnosis.This study develops robust systems for PD diagnosis by analyzing handwritten helical and wave graphical images.Handwritten graphic images of the PD dataset are enhanced using two overlapping filters,the average filter and the Laplacian filter,to improve image quality and highlight essential features.The enhanced images are segmented to isolate regions of interest(ROIs)from the rest of the image using a gradient vector flow(GVF)algorithm,which ensures that features are extracted from only relevant regions.The segmented ROIs are fed into convolutional neural network(CNN)models,namely DenseNet169,MobileNet,and VGG16,to extract fine and deep feature maps that capture complex patterns and representations relevant to PD diagnosis.Fine and deep feature maps extracted from individual CNN models are combined into fused feature vectors for DenseNet169-MobileNet,MobileNet-VGG16,DenseNet169-VGG16,and DenseNet169-MobileNet-VGG16 models.This fusion technique aims to combine complementary and robust features from several models,which improves the extracted features.Two feature selection algorithms are considered to remove redundancy and weak correlations within the combined feature set:Ant Colony Optimization(ACO)and Maximum Entropy Score-based Selection(MESbS).These algorithms identify and retain the most strongly correlated features while eliminating redundant and weakly correlated features,thus optimizing the features to improve system performance.The fused and enhanced feature vectors are fed into two powerful classifiers,XGBoost and random forest(RF),for accurate classification and differentiation between individuals with PD and healthy controls.The proposed hybrid systems show superior performance,where the RF classifier used the combined features from the DenseNet169-MobileNet-VGG16 models with the ACO feature selection method,achieving outstanding results:area under the curve(AUC)of 99%,sensitivity of 99.6%,99.3%accuracy,99.35%accuracy,and 99.65%specificity.展开更多
The hip’s lower limb exoskeleton essential and most important function is to support human’s payload as well as to enhance and assist human’s motion. It utilizes an electro-hydraulic servo manipulator which is requ...The hip’s lower limb exoskeleton essential and most important function is to support human’s payload as well as to enhance and assist human’s motion. It utilizes an electro-hydraulic servo manipulator which is required to achieve precise trajectory tracking and positioning operations. Nevertheless,these tasks require precise and robust control,which is very difficult to attain due to the inherent nonlinear dynamic behavior of the electro-hydraulic system caused by flow-pressure characteristics and fluid volume control variations of the servo valve. The sliding mode controller(SMC)is a widely used nonlinear robust controller,yet uncertainties and delay in the output degrade the closed-loop system performance and cause system instability. This work proposes a robust controller scheme that counts for the output delay and the inherent parameter uncertainties. Namely,a sliding mode controller enhanced by time-delay compensating observer for a typical electro-hydraulic servo system is adapted. SMC is utilized for its robustness against servo system parameters’ uncertainty whereas a time-delay observer estimates the variable states of the controller(velocity and acceleration). The main contribution of this paper is improving on the closed loop performance of the electro hydraulic servo system and mitigating the delay time effects. Simulation results prove the robustness of this controller,which forces the position to track the desired path regardless of the changes of the amount of transport delay of the system’s states. The performance of the proposed controller is validated by repeating the simulation analysis while varying the amount of delay time.展开更多
With the emergence of 5G mobile multimedia services,end users’demand for high-speed,low-latency mobile communication network access is increasing.Among them,the device-to-device(D2D)communication is one of the consid...With the emergence of 5G mobile multimedia services,end users’demand for high-speed,low-latency mobile communication network access is increasing.Among them,the device-to-device(D2D)communication is one of the considerable technology.In D2D communication,the data does not need to be relayed and forwarded by the base station,but under the control of the base station,a direct local link is allowed between two adjacent mobile devices.This flexible communicationmode reduces the processing bottlenecks and coverage blind spots of the base station,and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless networks.One of the important factors which affects the quality-of-service(QoS)of D2D communications is co-channel interference.In order to solve this problem of co-channel interference,this paper proposes a graph coloring based algorithm.The main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user resource.The proposed algorithm also provides simpler power control.The heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is acquired.Simulation results show that the proposed algorithm effectively reduced the co-channel interference,power consumption and improved the system throughput as compared with existing algorithms.展开更多
Objective: To explore the change of platelet indices namely plateletcrit, platelet distribution width and mean platelet volume among patients with recurrent pregnancy loss (RPL). Methods: The medical records of 45 wom...Objective: To explore the change of platelet indices namely plateletcrit, platelet distribution width and mean platelet volume among patients with recurrent pregnancy loss (RPL). Methods: The medical records of 45 women with a history of RPL and 45 women who gave birth without RPL were reviewed retrospectively from three governmental hospitals in Yemen. The personal, obstetric and complete blood count reports were analyzed. Results: Platelets' count and indices were significantly higher among RPL patients when compared to the control and the receiver operating characteristic curve for each platelet index showed significant area under the curve, with higher area for plateletcrit followed by platelet distribution width and then mean platelet volume. While the multiple logistic regression analysis for all platelets indices revealed that the platelet distribution width was the significant predictor for RPL in this study. Conclusions: The use of platelet indices may help gynecologists in predicting high risk pregnancy (pregnancy loss) in the low resources areas inYemen.展开更多
This paper studies the thermal performance of outdoor residential spaces in the old part—historical part—of Sana’a city in the winter period and its impact on the residents’ satisfaction who occupied the buildings...This paper studies the thermal performance of outdoor residential spaces in the old part—historical part—of Sana’a city in the winter period and its impact on the residents’ satisfaction who occupied the buildings which overlook these spaces and use them on a pedestrian comfort basis. The analysis was carried out through the results of field measurements which study the temperature, relative humidity, and the air movement inside the selected outdoor spaces in the period of winter (2 months) data recorded through the devices used and compared with those obtained from the General Authority of Meteorology and Aviation—Meteorology Sector. Despite the passage of years, the author remained occupied with the opinion of the people whose homes overlook those outdoors spaces and what is their opinion of their performance. Therefore, an assessment was conducted in November 2020 to know the opinion of the people about the performance of these outdoor spaces and to compare the results of the field measurements with the results of the assessment. The measurements were conducted by using data-loggers that spread in some outdoor spaces in 7 spaces in old city of Sana’a and in its modern extension during the winter period which is the time of concern of this work. The measurements showed that the outdoor residential spaces in the old city of Sana’a are represented an advantage for winter climate over that of the modern city, so the focus in this paper was on that outdoors with the question of the users of the outdoor spaces in the old city only to clarify their satisfaction with it and whether it has succeeded as well from their point of view. Results presented in this paper are important to consider the relationship between the climatical performance of outdoor spaces and the comfort of the residents in the urban environment and give implications for urban planners and architects to improve the climate-based design methodology towards sustainable developments.展开更多
Hastening transmission by efficiently providing compression is our goal in this work. Image compression consists in reducing information size representing an image. Elimination of redundancies and non-pertinent inform...Hastening transmission by efficiently providing compression is our goal in this work. Image compression consists in reducing information size representing an image. Elimination of redundancies and non-pertinent information enables memory space minimization and thus fast data transmission. Optics can offer an alternative choice to overcome the limitation of numerical compression algorithms. In this paper, we propose real-time optical image compression using a real Fourier plane to save time required for compression by using the principles of coherent optics. Digital and optical simulation results are presented and analyzed. An optical compression decompression setup is demonstrated using two different SLMs (SEIKO and DisplayTech). The purpose of this method is to simplify our earlier method, improve the quality of reconstructed image, and avoid the disadvantages of numerical algorithms.展开更多
Background: Inflammatory gingival enlargement is a more common clinical feature with orthodontic therapy than other features. Therefore, this study was designed to the evaluation of the influence of fixed orthodontic ...Background: Inflammatory gingival enlargement is a more common clinical feature with orthodontic therapy than other features. Therefore, this study was designed to the evaluation of the influence of fixed orthodontic treatment duration on the severity of inflammatory gingival enlargement (fixed orthodontic induced gingival enlargements) and some properties of saliva. Material and Methods: The sample size comprised 145 patients undergoing fixed orthodontic treatment for at least 6 months aged 13 - 32 years. They were divided according to orthodontic treatment duration into three groups. Group I (n = 47) included the patients who were treated for less than 6 months, group II (n = 51) included the patients who were treated for a period of 6 - 12 months, and group III (n = 47) included the patients who were managed for more than 12 months. Data were obtained from the outpatient clinics, college of dentistry, King Khalid University, Abha, Saudi Arabia, and some dental centers in Sana’a city, the Republic of Yemen. This study was conducted from October 2021 G to January 2022 G. Clinical examination was done for plaque index (PLI), gingival index (GI), and gingival enlargement indexes (GEI). Saliva was collected in sterile test tubes then salivary flow and pH were measured. Statistical analysis was done with SPSS (version 23) and ANOVA test to evaluate the impact of orthodontic treatment duration on the severity of inflammatory gingival enlargement and some properties of saliva. Results: The statistical analysis demonstrated the highest mean plaque index (PLI) was among groups III and I participants whereas, the highest mean gingival index and mean gingival enlargement were among groups II and III participants. The present study revealed an increase in salivary flow with decreased salivary pH values with an increase in orthodontic therapy duration. There were statistically significant differences in clinical findings and salivary flow and pH values were observed in the comparison between groups I, II and III except PLI (p Conclusion: There was a higher inflammatory gingival enlargement associated with a higher plaque index in patients under orthodontic treatment for more than 12 months more than the patients for less than 6 months and the patients for a period of 6 - 12 months. There were correlations between an increase of salivary flow and pH values and an increase of other variables in this study, such as plaque index, gingival index, and gingival enlargement index with an increased orthodontic therapy duration.展开更多
Background: Enhanced recovery after surgery (ERAS) has been tested in a wide variety of surgeries with promising outcomes. However, there is a need for a standardized, evidence-informed approach to both the developmen...Background: Enhanced recovery after surgery (ERAS) has been tested in a wide variety of surgeries with promising outcomes. However, there is a need for a standardized, evidence-informed approach to both the development of new ERAS Society guidelines, and the adaptation and revision of existing guidelines. Developing countries have limited resources and deserve every effort to improve economic status. Aim of the Study: to evaluate perinatal maternal outcomes of ERAS<sup>?</sup> versus routine care protocols in women undergoing elective cesarean section (CS) in a lower middle-income country with limited resources ranked as a third most country performing CS worldwide using a multidisciplinary team (MDT) management. Design: A prospective randomized Controlled Trial. Setting: Outpatient department (OPD) and labor ward at the Woman’s Health hospital, Assiut University, Egypt. Participants: Healthy pregnant women planned for elective CS (300 women) were randomly divided into a study group offered ERAS protocol and a control group offered regular care. Results: Repeat CS was the main indication of elective CS in both groups without significant difference (89 cases (59.3%) and 75 cases (50%) in both groups respectively). Other indications included cephalopelvic disproportion in 17 cases (11%) and 19 cases (12.6%), placenta previa in 28 (18.6%) and 34 (22.6%) cases, DM in 11 (7%) and 19 (12.6%) cases, and others in 5 (0.3%) and 3 (2%) cases in both groups respectively. The study group took much less time to eat and walk. It had significantly lower pain levels and postoperative problems, as well as much greater women’s satisfaction and a shorter hospital stay (p = 0.001). Conclusions: Collaboration of nursing, obstetricians and anesthesiologists is the cornerstone for a successful ERAS for CS. Significant better perinatal maternal outcomes encourage expansion of ERAS in lower middle-income countries with limited resources.展开更多
文摘Learner autonomy stands on the top priorities of scholars due to its pivotal role in fostering student-centered learning methods. It empowers the learners to be in charge of their learning process and be the center of attention in language learning education. For this purpose, different AI tools were used and implemented in pedagogy to narrow the divide in promoting learning/teaching approaches. This study aims to gauge the impact of using LLM-ChatGPT to teach EFL learners the present simple tense autonomously via providing automated feedback, and chances for regular drillings without over reliance on teacher. It also aims to investigate the EFL learners’ perception of using LLM-ChatGPT as a reinforcement approach to learner autonomy. A cohort comprising 50 EFL learners would participate in the study and a between subject design method using control and experimental groups would be implemented. The findings of the study indicated that learners who were taught present simple tense’s rule through using LLM-ChatGPT application, with less teacher’s dominance, scored grades similar to those who were taught the same tense’s rule by the teacher (sage on the stage approach). This substantiates the idea that LLM-Chat GPT acts a role akin to teachers in teaching grammatical rules. Moreover, the learners felt that LLM-ChatGPT application had a positive impact on fostering autonomous learning.
文摘This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.
文摘Parkinson’s disease(PD)is a progressive neurodegenerative disorder characterized by tremors,rigidity,and decreased movement.PD poses risks to individuals’lives and independence.Early detection of PD is essential because it allows timely intervention,which can slow disease progression and improve outcomes.Manual diagnosis of PD is problematic because it is difficult to capture the subtle patterns and changes that help diagnose PD.In addition,the subjectivity and lack of doctors compared to the number of patients constitute an obstacle to early diagnosis.Artificial intelligence(AI)techniques,especially deep and automated learning models,provide promising solutions to address deficiencies in manual diagnosis.This study develops robust systems for PD diagnosis by analyzing handwritten helical and wave graphical images.Handwritten graphic images of the PD dataset are enhanced using two overlapping filters,the average filter and the Laplacian filter,to improve image quality and highlight essential features.The enhanced images are segmented to isolate regions of interest(ROIs)from the rest of the image using a gradient vector flow(GVF)algorithm,which ensures that features are extracted from only relevant regions.The segmented ROIs are fed into convolutional neural network(CNN)models,namely DenseNet169,MobileNet,and VGG16,to extract fine and deep feature maps that capture complex patterns and representations relevant to PD diagnosis.Fine and deep feature maps extracted from individual CNN models are combined into fused feature vectors for DenseNet169-MobileNet,MobileNet-VGG16,DenseNet169-VGG16,and DenseNet169-MobileNet-VGG16 models.This fusion technique aims to combine complementary and robust features from several models,which improves the extracted features.Two feature selection algorithms are considered to remove redundancy and weak correlations within the combined feature set:Ant Colony Optimization(ACO)and Maximum Entropy Score-based Selection(MESbS).These algorithms identify and retain the most strongly correlated features while eliminating redundant and weakly correlated features,thus optimizing the features to improve system performance.The fused and enhanced feature vectors are fed into two powerful classifiers,XGBoost and random forest(RF),for accurate classification and differentiation between individuals with PD and healthy controls.The proposed hybrid systems show superior performance,where the RF classifier used the combined features from the DenseNet169-MobileNet-VGG16 models with the ACO feature selection method,achieving outstanding results:area under the curve(AUC)of 99%,sensitivity of 99.6%,99.3%accuracy,99.35%accuracy,and 99.65%specificity.
文摘The hip’s lower limb exoskeleton essential and most important function is to support human’s payload as well as to enhance and assist human’s motion. It utilizes an electro-hydraulic servo manipulator which is required to achieve precise trajectory tracking and positioning operations. Nevertheless,these tasks require precise and robust control,which is very difficult to attain due to the inherent nonlinear dynamic behavior of the electro-hydraulic system caused by flow-pressure characteristics and fluid volume control variations of the servo valve. The sliding mode controller(SMC)is a widely used nonlinear robust controller,yet uncertainties and delay in the output degrade the closed-loop system performance and cause system instability. This work proposes a robust controller scheme that counts for the output delay and the inherent parameter uncertainties. Namely,a sliding mode controller enhanced by time-delay compensating observer for a typical electro-hydraulic servo system is adapted. SMC is utilized for its robustness against servo system parameters’ uncertainty whereas a time-delay observer estimates the variable states of the controller(velocity and acceleration). The main contribution of this paper is improving on the closed loop performance of the electro hydraulic servo system and mitigating the delay time effects. Simulation results prove the robustness of this controller,which forces the position to track the desired path regardless of the changes of the amount of transport delay of the system’s states. The performance of the proposed controller is validated by repeating the simulation analysis while varying the amount of delay time.
基金This work is supported by Suranaree University for Technology research and development fund.
文摘With the emergence of 5G mobile multimedia services,end users’demand for high-speed,low-latency mobile communication network access is increasing.Among them,the device-to-device(D2D)communication is one of the considerable technology.In D2D communication,the data does not need to be relayed and forwarded by the base station,but under the control of the base station,a direct local link is allowed between two adjacent mobile devices.This flexible communicationmode reduces the processing bottlenecks and coverage blind spots of the base station,and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless networks.One of the important factors which affects the quality-of-service(QoS)of D2D communications is co-channel interference.In order to solve this problem of co-channel interference,this paper proposes a graph coloring based algorithm.The main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user resource.The proposed algorithm also provides simpler power control.The heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is acquired.Simulation results show that the proposed algorithm effectively reduced the co-channel interference,power consumption and improved the system throughput as compared with existing algorithms.
文摘Objective: To explore the change of platelet indices namely plateletcrit, platelet distribution width and mean platelet volume among patients with recurrent pregnancy loss (RPL). Methods: The medical records of 45 women with a history of RPL and 45 women who gave birth without RPL were reviewed retrospectively from three governmental hospitals in Yemen. The personal, obstetric and complete blood count reports were analyzed. Results: Platelets' count and indices were significantly higher among RPL patients when compared to the control and the receiver operating characteristic curve for each platelet index showed significant area under the curve, with higher area for plateletcrit followed by platelet distribution width and then mean platelet volume. While the multiple logistic regression analysis for all platelets indices revealed that the platelet distribution width was the significant predictor for RPL in this study. Conclusions: The use of platelet indices may help gynecologists in predicting high risk pregnancy (pregnancy loss) in the low resources areas inYemen.
文摘This paper studies the thermal performance of outdoor residential spaces in the old part—historical part—of Sana’a city in the winter period and its impact on the residents’ satisfaction who occupied the buildings which overlook these spaces and use them on a pedestrian comfort basis. The analysis was carried out through the results of field measurements which study the temperature, relative humidity, and the air movement inside the selected outdoor spaces in the period of winter (2 months) data recorded through the devices used and compared with those obtained from the General Authority of Meteorology and Aviation—Meteorology Sector. Despite the passage of years, the author remained occupied with the opinion of the people whose homes overlook those outdoors spaces and what is their opinion of their performance. Therefore, an assessment was conducted in November 2020 to know the opinion of the people about the performance of these outdoor spaces and to compare the results of the field measurements with the results of the assessment. The measurements were conducted by using data-loggers that spread in some outdoor spaces in 7 spaces in old city of Sana’a and in its modern extension during the winter period which is the time of concern of this work. The measurements showed that the outdoor residential spaces in the old city of Sana’a are represented an advantage for winter climate over that of the modern city, so the focus in this paper was on that outdoors with the question of the users of the outdoor spaces in the old city only to clarify their satisfaction with it and whether it has succeeded as well from their point of view. Results presented in this paper are important to consider the relationship between the climatical performance of outdoor spaces and the comfort of the residents in the urban environment and give implications for urban planners and architects to improve the climate-based design methodology towards sustainable developments.
文摘Hastening transmission by efficiently providing compression is our goal in this work. Image compression consists in reducing information size representing an image. Elimination of redundancies and non-pertinent information enables memory space minimization and thus fast data transmission. Optics can offer an alternative choice to overcome the limitation of numerical compression algorithms. In this paper, we propose real-time optical image compression using a real Fourier plane to save time required for compression by using the principles of coherent optics. Digital and optical simulation results are presented and analyzed. An optical compression decompression setup is demonstrated using two different SLMs (SEIKO and DisplayTech). The purpose of this method is to simplify our earlier method, improve the quality of reconstructed image, and avoid the disadvantages of numerical algorithms.
文摘Background: Inflammatory gingival enlargement is a more common clinical feature with orthodontic therapy than other features. Therefore, this study was designed to the evaluation of the influence of fixed orthodontic treatment duration on the severity of inflammatory gingival enlargement (fixed orthodontic induced gingival enlargements) and some properties of saliva. Material and Methods: The sample size comprised 145 patients undergoing fixed orthodontic treatment for at least 6 months aged 13 - 32 years. They were divided according to orthodontic treatment duration into three groups. Group I (n = 47) included the patients who were treated for less than 6 months, group II (n = 51) included the patients who were treated for a period of 6 - 12 months, and group III (n = 47) included the patients who were managed for more than 12 months. Data were obtained from the outpatient clinics, college of dentistry, King Khalid University, Abha, Saudi Arabia, and some dental centers in Sana’a city, the Republic of Yemen. This study was conducted from October 2021 G to January 2022 G. Clinical examination was done for plaque index (PLI), gingival index (GI), and gingival enlargement indexes (GEI). Saliva was collected in sterile test tubes then salivary flow and pH were measured. Statistical analysis was done with SPSS (version 23) and ANOVA test to evaluate the impact of orthodontic treatment duration on the severity of inflammatory gingival enlargement and some properties of saliva. Results: The statistical analysis demonstrated the highest mean plaque index (PLI) was among groups III and I participants whereas, the highest mean gingival index and mean gingival enlargement were among groups II and III participants. The present study revealed an increase in salivary flow with decreased salivary pH values with an increase in orthodontic therapy duration. There were statistically significant differences in clinical findings and salivary flow and pH values were observed in the comparison between groups I, II and III except PLI (p Conclusion: There was a higher inflammatory gingival enlargement associated with a higher plaque index in patients under orthodontic treatment for more than 12 months more than the patients for less than 6 months and the patients for a period of 6 - 12 months. There were correlations between an increase of salivary flow and pH values and an increase of other variables in this study, such as plaque index, gingival index, and gingival enlargement index with an increased orthodontic therapy duration.
文摘Background: Enhanced recovery after surgery (ERAS) has been tested in a wide variety of surgeries with promising outcomes. However, there is a need for a standardized, evidence-informed approach to both the development of new ERAS Society guidelines, and the adaptation and revision of existing guidelines. Developing countries have limited resources and deserve every effort to improve economic status. Aim of the Study: to evaluate perinatal maternal outcomes of ERAS<sup>?</sup> versus routine care protocols in women undergoing elective cesarean section (CS) in a lower middle-income country with limited resources ranked as a third most country performing CS worldwide using a multidisciplinary team (MDT) management. Design: A prospective randomized Controlled Trial. Setting: Outpatient department (OPD) and labor ward at the Woman’s Health hospital, Assiut University, Egypt. Participants: Healthy pregnant women planned for elective CS (300 women) were randomly divided into a study group offered ERAS protocol and a control group offered regular care. Results: Repeat CS was the main indication of elective CS in both groups without significant difference (89 cases (59.3%) and 75 cases (50%) in both groups respectively). Other indications included cephalopelvic disproportion in 17 cases (11%) and 19 cases (12.6%), placenta previa in 28 (18.6%) and 34 (22.6%) cases, DM in 11 (7%) and 19 (12.6%) cases, and others in 5 (0.3%) and 3 (2%) cases in both groups respectively. The study group took much less time to eat and walk. It had significantly lower pain levels and postoperative problems, as well as much greater women’s satisfaction and a shorter hospital stay (p = 0.001). Conclusions: Collaboration of nursing, obstetricians and anesthesiologists is the cornerstone for a successful ERAS for CS. Significant better perinatal maternal outcomes encourage expansion of ERAS in lower middle-income countries with limited resources.
