The causes of prescribing errors in English general practices: a qualitative study

Background: Few detailed studies exist of the underlying causes of prescribing errors in the UK. Aim: To examine the causes of prescribing and monitoring errors in general practice and provide recommendations for how they may be overcome. Design and setting: Qualitative interview and focus group study with purposive sampling of English general practices. Method: General practice staff from 15 general practices across three PCTs in England participated in a combination of semi-structured interviews (n = 34) and six focus groups (n = 46). Thematic analysis informed by Reason’s Accident Causation Model was used. Results: Seven categories of high-level error-producing conditions were identified: the prescriber, the patient, the team, the working environment, the task, the computer system, and the primary–secondary care interface. These were broken down to reveal various error-producing conditions: the prescriber’s therapeutic training, drug knowledge and experience, knowledge of the patient, perception of risk, and their physical and emotional health; the patient’s characteristics and the complexity of the individual clinical case; the importance of feeling comfortable within the practice team was highlighted, as well as the safety implications of GPs signing prescriptions generated by nurses when they had not seen the patient for themselves; the working environment with its extensive workload, time pressures, and interruptions; and computer-related issues associated with mis-selecting drugs from electronic pick-lists and overriding alerts were all highlighted as possible causes of prescribing errors and were often interconnected. Conclusion: Complex underlying causes of prescribing and monitoring errors in general practices were highlighted, several of which are amenable to intervention

Electron Momentum Density in Nickel (Ni)

In this paper, Compton profile of (Ni) was Calculated by employing both the renormalized-free atom(RFA) model and free electron(FE) model setting several configurations in subset (3d-4s). The results were compared with recent data ,It shows that the RFA calculation in(3d8.8-4s1.2) gives a better agreement with experiment.The calculated data used for the first time also to compute the cohesive energy of Nickle and compared it with available data. The Band structure and Density of state of Nickel crystals(DFT-LDA) also calculated by using code Quantum wise.Keywords: Compton profile,Electron momentum density, Cohesive energy, Band structure, Density of state

The Effective Role of Targeted Therapy in Advanced Colorectal Cancer

Though chemotherapy is the major strategy to manage patients with advanced-stage colorectal cancer (CRC), the main challenge is the progression of CRC despite using combination of different chemotherapeutic agents. So, to overcome this challenge, a new class Of therapy was developed naming “Targeted-therapy”. This class of drugs aim to target specific overexpressed or aberrant enzyme, receptor, or gene that have critical role in the growth and survival of colorectal cancerous cells. So that, by using combination of traditional strategy (chemotherapy) and targeted-drug, this will lead to improve survival and prevent the progression of advanced CR

Database forensic investigation process models: a review

Database Forensic Investigation (DBFI) involves the identification, collection, preservation, reconstruction, analysis, and reporting of database incidents. However, it is a heterogeneous, complex, and ambiguous field due to the variety and multidimensional nature of database systems. A small number of DBFI process models have been proposed to solve specific database scenarios using different investigation processes, concepts, activities, and tasks as surveyed in this paper. Specifically, we reviewed 40 proposed DBFI process models for RDBMS in the literature to offer up- to-date and comprehensive background knowledge on existing DBFI process model research, their associated challenges, issues for newcomers, and potential solutions for addressing such issues. This paper highlights three common limitations of the DBFI domain, which are: 1) redundant and irrelevant investigation processes; 2) redundant and irrelevant investigation concepts and terminologies; and 3) a lack of unified models to manage, share, and reuse DBFI knowledge. Also, this paper suggests three solutions for the discovered limitations, which are: 1) propose generic DBFI process/model for the DBFI field; 2) develop a semantic metamodeling language to structure, manage, organize, share, and reuse DBFI knowledge; and 3) develop a repository to store and retrieve DBFI field knowledge

Application of knowledge-oriented convolutional neural network for causal relation extraction in South China Sea conflict issues

Online news articles are an important source of information for decisions makers to understand the causal relation of events that happened. However, understanding the causality of an event or between events by traditional machine learning-based techniques from natural language text is a challenging task due to the complexity of the language to be comprehended by the machines. In this study, the Knowledge-oriented convolutional neural network (K-CNN) technique is used to extract the causal relation from online news articles related to the South China Sea (SCS) dispute. The proposed K-CNN model contains a Knowledge-oriented channel that can capture the causal phrases of causal relationships. A Data-oriented channel that captures the position information was added to the K-CNN model in this phase. The online news articles were collected from the national news agency and then the sentences which contain relation such as causal, message-topic, and product-producer were extracted. Then, the extracted sentences were annotated and converted into lower form and base form followed by transformed into the vector by looking up the word embedding table. A word filter that contains causal keywords was generated and a K-CNN model was developed, trained, and tested using the collected data. Finally, different architectures of the K-CNN model were compared to find out the most suitable architecture for this study. From the study, it was found out that the most suitable architecture was the K-CNN model with a Knowledge-oriented channel and a Data-oriented channel with average pooling. This shows that the linguistic clues and the position features can improve the performance in extracting the causal relation from the SCS online news articles

Investigating the mechanism of acoustically activated uptake of drugs from Pluronic micelles

BACKGROUND: This paper examines the mechanism of ultrasonic enhanced drug delivery from Pluronic micelles. In previous publications by our group, fluorescently labeled Pluronic was shown to penetrate HL-60 cells with and without the action of ultrasound, while drug uptake was increased with the application of ultrasound. METHODS: In this study, the amount of uptake of two fluorescent probes, Lysosensor Green (a pH-sensitive probe) and Cell Tracker Orange CMTMR (a pH-independent probe), was measured in HL-60 and HeLa cells. RESULTS: The results of our experiments show that the increase in drug accumulation in the cells as a result of ultrasonication is not due to an increase in endocytosis due to ultrasonication. CONCLUSIONS: We hypothesize that sonoporation plays an important role in the acoustically activated drug delivery of chemotherapy drugs delivered from Pluronic micelles

The impact of e-banking service quality on the sustainable customer satisfaction: Evidence from the Saudi Arabia commercial banking sector

The banking sector around the globe has witnessed a huge development in its services and products. The electronic banking services are considered as a competitive advantage for the banking sector. The purpose of this paper is to evaluate the effectiveness of e-banking service quality on customer satisfaction in the context of Saudi Arabian commercial banks. Both quantitative and qualitative research methods were used in the study. A sample of 308 customers from the banking sector participated in this study. The researchers have developed a self-structured questionnaire to collect the relevant data. In addition, secondary data was gathered from published sources, including websites, journal papers, and publications of the chosen commercial banks. The findings of this study show that the eight service quality dimensions; reliability, transactional efficiency, customer support, service security, ease of use, performance, satisfaction with service quality and service content have a significant impact on the level of user's satisfaction with e-banking in the Saudi Arabian commercial banks

Krüppel-like Factor 4 Regulates Intestinal Epithelial Cell Morphology and Polarity

Krüppel-like factor 4 (KLF4) is a zinc finger transcription factor that plays a vital role in regulating cell lineage differentiation during development and maintaining epithelial homeostasis in the intestine. In normal intestine, KLF4 is predominantly expressed in the differentiated epithelial cells. It has been identified as a tumor suppressor in colorectal cancer. KLF4 knockout mice demonstrated a decrease in number of goblet cells in the colon, and conditional ablation of KLF4 from the intestinal epithelium led to altered epithelial homeostasis. However, the role of KLF4 in differentiated intestinal cells and colon cancer cells, as well as the mechanism by which it regulates homeostasis and represses tumorigenesis in the intestine is not well understood. In our study, KLF4 was partially depleted in the differentiated intestinal epithelial cells by a tamoxifen-inducible Cre recombinase. We found a significant increase in the number of goblet cells in the KLF4-deleted small intestine, suggesting that KLF4 is not only required for goblet cell differentiation, but also required for maintaining goblet cell numbers through its function in inhibiting cell proliferation. The number and position of Paneth cells also changed. This is consistent with the KLF4 knockout study using villin-Cre [1]. Through immunohistochemistry (IHC) staining and statistical analysis, we found that a stem cell and/or tuft cell marker, DCAMKL1, and a proliferation marker, Ki67, are affected by KLF4 depletion, while an enteroendocrine cell marker, neurotensin (NT), was not affected. In addition, we found KLF4 depletion altered the morphology and polarity of the intestinal epithelial cells. Using a three-dimensional (3D) intestinal epithelial cyst formation assay, we found that KLF4 is essential for cell polarity and crypt-cyst formation in human colon cancer cells. These findings suggest that, as a tumor suppressor in colorectal cancer, KLF4 affects intestinal epithelial cell morphology by regulating proliferation, differentiation and polarity of the cells

Mobile based augmented reality for flexible human height estimation using touch and motion gesture interaction

Human height measurement can be achieved by using contact or non-contact techniques. Contact technique is the traditional measuring method which required human resources to perform the measurement. In contrast, for non-contact technique, several kinds of research for measurement have been conducted, mostly with image-processing methods and only a few with the Augmented Reality (AR) approach. The current measuring approaches mostly required external hardware such as laser pointer or artificial fiducial such as 2D markers. In this paper, the world tracking technique and Visual Inertial Odometry is the method used to estimate the human height. The main aim of this paper is to accurately estimate the human height using augmented reality (non-contacted measurements). The methodology used the Apple ARKit plugin, which is the software development tools to build an augmented reality application for IOS device. An algorithm was designed by using Golden Ratio rules to estimate human height from the lower part of human knee; The estimation result is displayed using AR technology to allow the justification of the accuracy of the result. The application is tested with four different measuring methods. The normal full-height measurement result had a 1.13cm (0.73%) bias and a 1.34cm (0.88%) Root Mean Square Error (RMSE); the self-full height measurement had a result of 0.89cm (0.58%) bias and a 1.27cm (0.83%) RMSE; the normal height estimation from the lower part of knee measurement had a result of 0.12cm (0.06%) bias and a 1.34cm (0.89%) RMSE; the self-height estimation from the lower part of knee measurement had a result of 0.15cm (0.09%) bias and a 1.04cm (0.66%) RMSE. The results show that the mobile phone with VIO can be a potential tool for obtaining accurate measurements of human height