10 research outputs found
Mechanical and optical properties of machined, printed, and conventional dental polymers
OBJECTIVE: This study aims to compare the flexural strength and color stability of conventional, machined, and printed dental polymers. Secondarily, the effects of aging, fatigue, coffee, distilled water, and UV light on the color stability and flexural strength of the different dental polymers will be evaluated.
MATERIALS AND METHODS: Sixty disks 14mm in diameter and 2mm in thickness were fabricated from each of the following polymers: Jet Tooth Shade (Lang Dental), ProTemp (3M-ESPE), Telio CAD Temp (Ivoclar Vivadent), Vita CAD Temp (Vita), Temporary CB (FormLab), Dentca (Dentca), and Bego VarseoSmile Crown Plus (Bego). The sixty disks from each polymer were then divided into the six following groups: no treatment, thermocycling, fatigue, thermocycling and coffee, distilled
water and finally UV Light. Prior to any treatment, the color coordinates CIE L*a*b*, were registered first. The non-treated groups were fractured using the Instron Universal Testing Machine to obtain flexural strength values.
Thermocycling consisted of placing the specimens in 30 seconds 5°C water and then 30 seconds in 55°C water for 5,000 cycles. Fatigue testing consisted of cyclic
loading the disk specimens by calculating 60% of the mean load to failure from the non-treated group and subjecting them to 50,000 cycles. The third group was placed under thermocycling for 1,500 cycles and then placed in coffee for 15 days. Another group was placed in distilled water for 15 days. Finally, the UV light treatment consisted of exposing the disk specimens to UV light for ten hours over the course of five days. After treatment, the color coordinates were recorded again and fractured using the Instron Universal Testing Machine. The data was analyzed
for any statistically significant differences using ANOVA with a<0.05.
RESULTS: The flexural strength values were highest for Telio CAD Temp, that was affected only by UV light via a statistical analysis. ProTemp was second highest followed by Bego VarseoSmile Crown Plus, Dentca, Temporary CB, Vita CAD Temp and finally Jet Tooth Shade. Color differences were highest for Dentca followed by Jet Tooth Shade, ProTemp, Telio CAD Temp, Temporary CB and finally Vita CAD Temp. UV light and thermocycling/ coffee had the highest impact.
CONCLUSION: Telio CAD Temp had the highest overall flexural strength and was resistant to all post fabrication treatments except for UV light. ProTemp had the second highest overall flexural strength but was susceptible to multiple post fabrication treatments like distilled water, fatigue, and aging. The printed specimens had flexural strength values lower in the middle range of all tested materials. In terms of treatment, UV light and coffee/thermocycling had the biggest impact on the overall color stability values. Powder and Liquid based PMMA had the lowest overall flexural strengths
Are we ready for the next pandemic? Lessons learned from healthcare professionals’ perspectives during the COVID-19 pandemic
BackgroundThe mental health and wellbeing of people watching the Corona Virus Disease 2019 (COVID-19) pandemic unfold has been discussed widely, with many experiencing feelings of anxiety and depression. The state of mental health of medical staff on the frontlines providing care should be examined; medical staff are overworked to meet the demands of providing care to the rise in cases and deterioration in capacity to meet demands, and this has put them under great psychological pressure. This may lead to an increase in medical errors, affect quality of care, and reduce staff retention rates. Understanding the impact the pandemic has had on healthcare professionals is needed to provide recommendations to prepare for future crises.ObjectivesTo be able to meet the needs of the medical workforce on the frontlines and inform psychological support interventions and strategies for future pandemics, we aim to identify and explore the psychological impact of COVID-19 in Kuwait on healthcare professionals in close contact with patients.MethodsUsing semi-structured interviews, we conducted interviews between February and July 2021 with 20 healthcare professionals across Ministry of Health hospitals who were part of COVID teams. Interviews were transcribed verbatim, and analysis was conducted using principles of thematic framework analysis.ResultsThree themes emerged to help prepare future healthcare frontline workers on an individual, organizational, and national level: enhance self-resilience, a better-equipped workforce and healthcare environment, and mitigate stigma and increase public awareness.ConclusionThe results have assisted in highlighting areas of improvement to support the healthcare workforce in the current environment, as well as better prepare them for future pandemics. The findings have also provided insight to recommend targeted interventions. These should improve the psychological wellbeing and help in supporting healthcare professionals to reduce burnout, continue effective care of patients, and enhance resilience
Symptoms and management of cow's milk allergy: perception and evidence
IntroductionThe diagnosis and management of cow's milk allergy (CMA) is a topic of debate and controversy. Our aim was to compare the opinions of expert groups from the Middle East (n = 14) and the European Society of Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) (n = 13).MethodsThese Expert groups voted on statements that were developed by the ESPGHAN group and published in a recent position paper. The voting outcome was compared.ResultsOverall, there was consensus amongst both groups of experts. Experts agreed that symptoms of crying, irritability and colic, as single manifestation, are not suggestive of CMA. They agreed that amino-acid based formula (AAF) should be reserved for severe cases (e.g., malnutrition and anaphylaxis) and that there is insufficient evidence to recommend a step-down approach. There was no unanimous consensus on the statement that a cow's milk based extensively hydrolysed formula (eHF) should be the first choice as a diagnostic elimination diet in mild/moderate cases. Although the statements regarding the role for hydrolysed rice formula as a diagnostic and therapeutic elimination diet were accepted, 3/27 disagreed. The votes regarding soy formula highlight the differences in opinion in the role of soy protein in CMA dietary treatment. Generally, soy-based formula is seldom available in the Middle-East region. All ESPGHAN experts agreed that there is insufficient evidence that the addition of probiotics, prebiotics and synbiotics increase the efficacy of elimination diets regarding CMA symptoms (despite other benefits such as decrease of infections and antibiotic intake), whereas 3/14 of the Middle East group thought there was sufficient evidence.DiscussionDifferences in voting are related to geographical, cultural and other conditions, such as cost and availability. This emphasizes the need to develop region-specific guidelines considering social and cultural conditions, and to perform further research in this area
Investigating the Impact of Climate Change on Dust Storms Over Kuwait by the Middle of the Century Simulated by WRF Dynamical Downscaling
The aim of this study is to examine the impact of climate change on future dust storms in Kuwait. Dust storms are more frequent in summertime in the Arabian Peninsula, and can be highly influential on the climate and the environment in the region. In this study, the influence of climate change in the Middle East and especially in Kuwait was investigated by high-resolution (48, 12, and 4 km grid spacing) dynamic downscaling using the WRF (Weather Research & Forecasting) model. The WRF dynamic downscaling was forced by reanalysis using the National Centers for Environment Prediction (NCEP) model for the years 1997, 2000, and 2008. The downscaling results were first validated by comparing NCEP model outputs with the observational data. The global climate change dynamic downscaling model was run using current WRF regional climate model (RCM) simulations (2006–2010) and WRF-RCM climate simulations of the future (2056–2060). They were used to compare results between the present and the middle of the century. In general, the dominant features from (NCEP) runs were consistent with each other, as well as with WRF-RCM results. The influence of climate change in the Middle East and Kuwait can be projected from the differences between the current and model future run. The average temperature showed a positive trend in the future, as in other studies. The temperature was predicted to increase by around 0.5-2.5 °C over the next 50 years. No significant change in mean sea level pressure patterns was projected. However, amongst other things, a change in the trend of the surface wind speeds was indicated during summertime. As a result, the increase in temperature and the decline in wind speed in the future indicate a reduction in dust storm days in Kuwait by the middle of the century
GP-Based Knowledge Acquisition and Integration Mechanisms in Knowledge Management Processes
在目前的企業環境中,很多企業致力於管理和應用組織知識,來維持他們的核心能力和創造競爭優勢。有效率的管理組織知識,能減少解決問題的時間和成本,並增加組織學習和創新能力。並且,由於累積知識資源的需求,很多企業開始發展知識庫,以儲存組織及個人的知識,用來增加組織整體的效率、支援日常的運作以及企業策略的操作。
知識管理是現代的典範,可用來有效管理組織知識,進而改善組織績效。知識管理的目的是強調管理知識的流動及流程。在知識管理流程方面,主要區分為知識擷取、整合、儲存/歸類、散播和應用知識等程序。另外,資訊技術可用來協助知識管理,並能使知識管理更有效率。知識管理的主要議題之ㄧ是知識的擷取,由於目前知識來源的提供,主要是透過知識工作者,可是它對於知識工作者而言,是一種額外的負擔。因此,設計一個有效的方法來自動產生組織知識,以減輕他們的額外負擔,將是一個很重要的課題。第二個相當重要的議題是知識整合,由於不同來源的知識,可能造成組織知識的衝突,因此設計一個知識整合方法,把不同來源的知識整合成一個完整的知識,組織將會逐漸增加這方面的需求。
分類在很多應用中是常遭遇的問題,例如財務預測、疾病診斷等。在過去,分類規則常藉由決策樹的方法所產生,並用於解決分類的問題。在本論文中,提出兩個以遺傳規劃為基礎的知識擷取方法和兩個以遺傳規劃為基礎的知識整合方法,分別支援知識管理流程中的知識擷取和知識整合。
在兩個所提的知識擷取方法中,第一個方法是著重在快速和容易地找到想要的分類樹,但是,此方法可能會產生結構較複雜的分類樹。第二個方法是修正第一個方法,產生一個較精簡和應用性高的分類樹。這些所獲得的分類樹,能被轉換成規則集合,並匯入知識庫中,幫助企業決策的制定和日常的運作。
此外,在兩個所提的知識整合方法中,第一個方法,能自動結合多重的知識來源成為一個整合的知識,並可匯入知識庫中,但是此方法只考慮到單一時間點的整合。第二個方法則是可以解決不同時間點的知識整合問題。另外,本論文提出三個新的遺傳運算子,在演化過程中,可用來解決規則集合中有重複、包含和衝突等常見的問題,因而可以產生較精簡及一致性高的分類規則。最後,本論文採用信用卡資料及乳癌資料來驗證所提方法的可行性,實驗結果皆獲得良好的成效。In today’s business environment, many enterprises make efforts in managing and applying organizational knowledge to sustain their core competence and create competitive advantage. The effective management of organizational knowledge can reduce the time and cost of solving problems, improve organizational performance, and increase organizational learning as well as innovative competence. Moreover, due to the need to accumulate knowledge resources, many enterprises have devoted to developing their knowledge repositories. These repositories store organizational and individual knowledge that are used to increase overall organization efficiency, support daily operations, and implement business strategies.
Knowledge management (KM) is the modern paradigm for effective management of organizational knowledge to improve organizational performance. The intent of KM is to emphasize knowledge flows and the main process of acquisition, integration, storage/categorization, dissemination, and application. Furthermore, extant information technologies can provide a way of enabling more effective knowledge management. One of the important issues in knowledge management is knowledge acquisition. It is an extra burden for knowledge workers to contribute their knowledge into repositories, such that designing an effective method for abating an extra burden to automatically generate organizational knowledge will play a critical role in knowledge management. A second rather important issue in knowledge management is knowledge integration from different knowledge sources. Designing a knowledge-integration method to combine multiple knowledge sources will gradually become a necessity for enterprises.
Classification problems, such as financial prediction and disease diagnosis, are often encountered in many applications. In the past, classification trees were often generated by decision-tree methods and commonly used to solve classification problems. In this dissertation, we propose two GP-based knowledge-acquisition methods and two GP-based knowledge-integration methods to support knowledge acquisition and knowledge integration respectively in the knowledge management processes for classification tasks.
In the two proposed knowledge-acquisition methods, the first one is fast and easy to find the desired classification tree. It may, however, generate a complicated classification tree. The second method then further modifies the first method and produces a more concise and applicatory classification tree than the first one. The classification tree obtained can be transferred into a rule set, which can then be fed into a knowledge base to support decision making and facilitate daily operations.
Furthermore, in the two proposed knowledge-integration methods, the former method can automatically combine multiple knowledge sources into one integrated knowledge base; nevertheless, it focuses on a single time point to deal with such knowledge-integration problems. The latter method then extends the former one to handle integrating situations properly with different time points. Additionally, three new genetic operators are designed in the evolving process to remove redundancy, subsumption and contradiction, thus producing more concise and consistent classification rules than those without using them.
Finally, the proposed methods are applied to credit card data and breast cancer data for evaluating their effectiveness. They are also compared with several well-known classification methods. The experimental results show the good performance and feasibility of the proposed approaches
Forward Simulation of Multi-Frequency Microwave Brightness Temperature over Desert Soils in Kuwait and Comparison with Satellite Observations
© 2019 by the authors. In this study, we address the variations of bare soil surface microwave brightness temperatures and evaluate the performance of a dielectric mixing model over the desert of Kuwait. We use data collected in a field survey and data obtained from NASA Soil Moisture Active Passive (SMAP), European Space Agency Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and Special Sensor Microwave/Imager (SSM/I). In situ measurements are collected during two intensive field campaigns over bare, flat, and homogeneous soil terrains in the desert of Kuwait. Despite the prevailing dry desert environment, a large range of soil moisture values was monitored, due to precedent rain events and subsequent dry down. The mean relative difference (MRD) is within the range of ±0.005 m3·m-3 during the two sampling days. This reflects consistency of soil moisture in space and time. As predicted by the model, the higher frequency channels (18 to 19 GHz) demonstrate reduced sensitivity to surface soil moisture even in the absence of vegetation, topography and heterogeneity. In the 6.9 to 10.7 GHz range, only the horizontal polarization is sensitive to surface soil moisture. Instead, at the frequency of 1.4 GHz, both polarizations are sensitive to soil moisture and span a large dynamic range as predicted by the model. The error statistics of the difference between observed satellite brightness temperature (Tb) (excluding SMOS data due to radio frequency interference, RFI) and simulated brightness temperatures (Tbs) show values of Root Mean Square Deviation (RMSD) of 5.05 K at vertical polarization and 4.88 K at horizontal polarization. Such error could be due to the performance of the dielectric mixing model, soil moisture sampling depth and the impact of parametrization of effective temperature and roughness
Validation of NASA SMAP Satellite Soil Moisture Products over the Desert of Kuwait
The goal of this study is to validate and analyze NASA’s Soil Moisture Active Passive (SMAP) products over the desert of Kuwait. The study period was between April 2015 and April 2020. The study domain includes a mission candidate calibration/validation (Cal/Val) site that comprises six permanent soil moisture stations used to verify SMAP estimates. In addition, intensive field campaigns were conducted within and around the candidate Cal/Val site during the study period to collect additional thermogravimetric samples. The mean difference (MD), root mean squared difference (RMSD), unbiased root mean square difference (ubRMSD), and correlation coefficient (R) were computed to assess the agreement between SMAP SM products and in situ observations. The comparison of the six ground station sensors’ observations with the thermogravimetric samples led to an absolute mean bias (AMB) of 0.034 m3 m−3, which was then used to calibrate the sensors and bias-correct their measurements. The temporal consistency of the readings from the test site and calibrated sensors was assessed using the mean relative difference (MRD) and its standard deviation of relative difference (SDRD). Using a sampling density analysis, it was determined that a minimum of four ground stations would be required to validate the test site. Furthermore, the consistency between SMAP satellite soil moisture data and those derived from the Soil Moisture and Ocean Salinity (SMOS) satellite operated by the European Space Agency, and their agreement with in situ samples, was analyzed. The comparison of SMAP and SMOS soil moisture data with in situ observations showed that both satellites successfully captured the spatial and temporal distribution of soil moisture. For SMAP and SMOS, the lowest ubRMSE statistics were 0.043 m3 m−3 and 0.045 m3 m−3, respectively, which are slightly higher than the mission target of 0.04 m3 m−3