Dietary protein intake and long-term outcomes after kidney transplantation

For kidney transplant recipients (KTR), optimal dietary protein quantity and quality is unknown. In this thesis, we aimed to investigate several aspects of protein intake after kidney transplantation and their associations with long-term outcomes. Through observational, prospective cohort studies, we found that higher protein intake was associated with longer patient and graft survival compared to low protein intake, likely through a multifactorial pathway that includes preservation of muscle mass and physical fitness. A relatively high urinary excretion of markers for white and red meat intake was found to be associated with lower risk of long-term graft failure. Protein intake provides amino acids as building blocks, but also amino acids that can be used as substrate for production of other molecules, including nitric oxide (NO) and hydrogen sulfide (H2S). We found that high urinary excretions of metabolites of NO and of H2S were respectively associated with longer patient and graft survival. Another compound that can originate from dietary protein, or is produced during endogenous protein turnover, is asymmetric dimethylarginine, of which we found that higher urinary excretion was associated with longer patient survival. Although observational in nature, the results of this thesis strongly suggest that KTR should not be subjected to a low protein intake and that a relatively high protein intake is advantageous for long-term survival. Therefore, we call for an intervention study to investigate the effect of protein intake in KTR on long-term outcomes, in order to determine the optimal quantity and quality of dietary protein intake in KTR

The Effects of Social Capital and Individual Factors on Knowledge Sharing Among ERP System Users

Enterprise Resource Planning (ERP) system is a management technology that advocates an integrated approach to conduct business. Before organizations apply technology to improve the overall performance, they must understand what their employees need to use it. ERP systems are knowledge intensive, which require high level of knowledge absorption and knowledge sharing between organizational members in order to be used successfully. Since the knowledge sharing is a key factor to use the ERP system, therefore this study aims to identify the social capital and individual factors affecting knowledge sharing among ERP users in small and medium-sized enterprises (SMEs). A quantitative method was employed using a self-administered questionnaire technique to collect data from 413 ERP users in Jordanian SMEs and SPSS software to analyse the data. This study found that social networks, trust, shared vision, self-efficacy, absorptive capacity; extrinsic motivation and intrinsic factors have influenced significantly on knowledge sharing among ERP users. Such a finding could provide guidelines for the management to enhance knowledge sharing among ERP users for successful ERP system usage

Improvement of Cepstrum Analysis for the Purpose to Detect Leak, Feature and Its Location in Water Distribution System based on Pressure Transient Analysis / Hanafi.M.Yusop ...[et al.]

Nowadays, pipeline system is one of the powerful technologies to be implemented in the real world. It is very essential for transporting fluid especially water from one point to the next point. But the pipeline system will also defect as leaks due to many reasons. Pressure Transient signal is a newly developed method to detect and localize leak phenomena since the signal has information about that phenomenon .The basic principal is the fact of water spouting out of a leak in pressurized pipe that generates a signal, and the signal may contain information to whether a leak exists and where it is located. To extract this signal, many signal analysis methods were implemented by researchers such as cross-correlation, genetic algorithm, and wavelets transform. Cepstrum analysis is proposed as a method to extract leak and pipe feature information from pressure transient signal by considering this method to analyse non-stationary data. Since in the real test, the originality and pure data are hard to be captured due to noise generated from environment and the noise level ratio is very low, pre-processing method as a filtering technique is implemented to analyse the real signal before the signal goes through cepstrum analysis as post-processing method. This research focused on the improvement of cepstrum analysis in order to extract information about the leak, pipe feature, and its location. In this research, cepstrum analysis was proposed as Post-Processing method. Discrete Wavelets Transform (DWT) and Principal Component Analysis (PCA) were proposed as Pre-Processing Methods. The pressure Transient signal was analysed using Matlab software. The results satisfactorily predicted the leak location as the comparison analysis using theoretical calculation and experimental results were just 0.4% to 3.8%. Therefore, PCA and DWT were recommended as data pre-processing methods to improve cepstrum analysis result

Histopathology Imagery Dataset of Ph-Negative Myeloproliferative Neoplasm.v2

Despite advanced technology in diagnostic tools to boost the procedure, the morphological assessment of bone marrow trephine (BMT) images remains critical to confirm and differentiate MPN subtypes. Hence, this histopathological imagery dataset was generated and focuses on the most typical MPN from Philadelphia chromosome (Ph)-negative type, which are Essential Thrombocythemia (ET), Polycythemia Vera (PV), Primary Myelofibrosis (MF). This dataset consists of 300 BMT images which can be used to enable computer vision applications such as image segmentation, disease classification, and object recognition. Hence, the application can assist medical practitioners to overcome current challenges such as high dependency on human expertise and misdiagnosis.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Histopathology Imagery Dataset of Ph-Negative Myeloproliferative Neoplasm

Despite advanced technology in diagnostic tools to boost the procedure, the morphological assessment of bone marrow trephine (BMT) images remains critical to confirm and differentiate MPN subtypes. Hence, this histopathological imagery dataset was generated and focuses on the most typical MPN from Philadelphia chromosome (Ph)-negative type, which are Essential Thrombocythemia (ET), Polycythemia Vera (PV), Primary Myelofibrosis (MF). This dataset consists of 300 BMT images which can be used to enable computer vision applications such as image segmentation, disease classification and object recognition.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV