Caring and Effective Teaching Behavior of Clinical Nursing Instructors in Clinical Area as Perceived by Their Students

Nursing is considered to be an applied science. Thus clinical teaching is central to nurse education. The quality of the student-teacher interaction in the clinical field can either facilitate or hinder the students' integration of theory to practice. It has been postulated that clinical instructors must possess caring behavior and effective clinical teacher characteristics if they want to facilitate students' entry and learning in a multifaceted world of clinical practice. So this study done to describe the clinical instructors’ caring and effective clinical teaching behaviors in clinical area as perceived by their students. A convenience sample of 113 nursing students affiliated to faculty of nursing, King Khalid University, Saudi Arabia was included. Two tools for data collection were used; the first on was developed by the researcher and it was concerned with measuring the effective teaching characteristics of the clinical nursing instructors and the second one was the Nursing Student Perceptions of Instructor Caring (NSPIC) which was concerned with measuring clinical instructor’s caring behaviors.  The participant nursing students has common and unique perspectives on the importance of a clinical instructor demonstrating effective teaching characteristics. In addition, caring behaviors demonstrated by clinical instructors were identified and they perceived their clinical instructors demonstrated the highest number of caring behaviors from the subscales of respectful sharing and appreciation of life’s meanings. Clinically, the results might be utilized to improve faculty awareness of students’ views on their teaching performance. On the other hand, the clinical faculty can be educated and provided with useful educational tools to assist them in providing effective clinical instructions. Keywords: effective clinical teaching characteristics, caring behavior, clinical teaching in nursin

Health Belief Model Based Intervention for Improving Nursing Students’ Knowledge and Behavior Regarding Osteoporosis Prevention

Osteoporosis is a preventable chronic disease that begins during childhood. It is a silent killer not diagnosed until an individual presents with a low impact fracture. Health belief model (HBM) based intervention increase awareness of risk factors and preventive behaviors. Aim: This study aimed to investigate the effect of health belief model based intervention on nursing students’ knowledge and behavior regarding osteoporosis prevention. Sample: A convenient sample of 100 female nursing students was included. Setting: The study was conducted at Applied Medical Sciences Collage, nursing department in Al Dawadmi, from September -November 2013. Data were collected before and after one month from the intervention. Results: Students knowledge about osteoporosis was improved significantly post implementation of the HBM based intervention, also there was a significant difference between students perception regarding health believe subscale before and after the HBM based intervention. Also osteoporosis protective behaviors among students were significantly changed post the intervention and there was a significant correlation between their knowledge, perception and level of calcium intake & daily activity post the intervention. Conclusion: Osteoporosis is a pediatric disease with geriatric consequences which need HBM based educational intervention during the adulthood stage to improve adult female knowledge, maintain osteoporosis preventive behaviors, and improve their health believes. Key words: Health belief model (HBM) based intervention, osteoporosis prevention, nursing students

Resistance to Educational Change from the Perspective of Teachers in Al Ain Educational Zone in UAE.

The study aimed to investigate the factors for teacher resistance toward the educational change in government schools in the U.A.E. The factors this study investigated are the: psychological, personal, school culture, and organizational factors. The study was guided by one research question and used the descriptive research method. Data for this study were collected through a survey using Likert Scale. It was sent to 414 teachers in public schools in different grade levels. Teachers selected were males and females, from different age group, years of experience and qualifications; and they were UAE national and foreign teachers. Only 255 teachers responded. Statistical tests including means, percentages, and standard deviations, and Chi-Square Test were applied to analyze the quantitative part of the questionnaire. The answers to the open-ended questions in the last part of the questionnaire were interpreted by tallying the answers. The results of this study showed that teachers felt the need for change and they trusted the change agents and principals. However, they need to be prepared psychologically because they feared the unknown consequences of change and they were exhausted from frequent changes that were imposed on them. Further, teachers faced difficulty in teaching students who were not grasping the new curriculum because of the language problem. What they needed was a well-planned change, supportive principals, effective staff development that relate to change, and good training programs and rewards. Above all, they ask for a change that fits the U

A New Router Certification Authority Protocol For Securing Mobile Internet Protocol Version 6

Protokol Internet Bergerak versi 6 (IPv6 Bergerak) telah dicadangkan sebagai satu protokol piawai untuk memberikan mobility dalam Rangkaian Generasi Seterusnya. Mobile Internet Protocol version 6 (Mobile IPv6) has been proposed as a standard protocol to provide mobility in Next Generation Networks

Interaction of microorganisms with sheet silicates

To study the interaction between microorganisms and sheet silicates, nontronite (NAu-2), and chlinochlore (CCa-2) as a powder form less than 2 µm were incubated with two microorganisms; Streptomyces acidiscabies and Schizophyllum commune strains in liquid culture flasks for two months. CCa-2 is a non swelling mineral, while NAu-2 is a swelling mineral, where hydrated ions incorporate into the mineral interlayer. Consequently, the mineral expands and additional mineral surfaces are more exposed to solution and microbial attack. That is why NAu-2 was more susceptible to microbial dissolution than the CCa-2. X-ray diffraction (XRD) spectra showed that there was no change at all in the structure of CCa-2, while NAu-2 became amorphous to X-rays. S. acidiscabies E13 strain produces some organic acids, exo- polysaccharides (EPS), enzymes, siderophores, and melanin. The production of some of these biomolecules together at the same time might be the main reason that the S. acidiscabies strain was more efficient not only in releasing some elements from both minerals than the S. commune strain, but also in inducing some surface normal retreats of CCa-2 polished pieces. Vertical scanning interferometry (VSI) images showed that the S. acidiscabies strain altered the surface of small polished pieces of CCa-2, and caused a maximum loss of 2.6 µm3 per 1 µm2. S. acidiscabies was also the most effective in comparison to chemical acid treatments regardless organic or non-organic, which indicated that neither protonation nor chelation alone could be the mechanisms for the S. acidiscabies strain to perform such normal surface retreats over the CCa-2. Most probably the actinobacterium strain was able to alter the CCa-2 mineral surface, by the excretion of some organic acids together with siderophores, where both products were concentrated within EPS biofilms. Direct areal contact might be essential also for such dissolution and etch pits formations, as S. commune strain has left the surface of the mineral after colonizing it for a very short time. Therefore, the fungus strain hasn’t caused any effect over the small polished CCa-2 pieces. Microbial pellets formed by the S. acidiscabies strain with CCa-2 had heavily encrusted mineral flakes and smooth hyphae, while in case of NAu-2, no trace for many mineral flakes but the hyphae were almost encrusted. S. commune strain wasn’t able to form microbial pellets with any amount of CCa-2, and formed pellets with only 0.25 g of the NAu-2 minerals. While other fungal strains (Ceratocystis polonica and Alternaria brassicola) which produce melanin have formed microbial pellets with 1 g of NAu-2. FTIR showed that S. acidiscabies strain has produced in the presence of the two minerals some EPS with concentrations higher than what is present in the strains grown alone in the minimal medium. Esters of long chain fatty acids in the form of triglycerides might be present too as they were detected by TEM. Maps showing spatial distribution of some FTIR bands for the S. acidiscbaies strain inoculated with NAu-2 have shown that EPS (polysaccharides and proteins), were localized inside the pellets for mineral attachment. While when the S. acidiscabies strain was incubated with CCa-2 the phosphate ester band at 1245 cm-1 mismatched the spatial distribution of fatty esters, which indicated that phospholipids were not a major component in the sample, however their distribution on the edges of the pellets with the rich Mg CCa-2 mineral showed that they are a potent magnesium chelator. CCa-2 haven’t induced neither S. acidiscabies nor S. commune strains to produce any extracellular proteins, while with NAu-2 both strains have produced some extracellular proteins in the liquid culture medium, which was measured by the Bradford assay

Enhancing imputation techniques performance utilizing uncertainty aware predictors and adversarial learning

One crucial problem for applying machine learning algorithms to real-world datasets is missing data. The objective of data imputation is to fill the missing values in a dataset to resemble the completed dataset as accurately as possible. Many methods are proposed in the literature that mostly differs on the objective function and types of the variables considered. The performance of traditional machine learning methods is low when there is a nonlinear and complex relationship between features. Recently, deep learning methods are introduced to estimate data distribution and generate values for missing entries. However, these methods are originally developed for large datasets and custom data types such as image, video, and text. Thus, adopting these methods for small and structured datasets that are prevalent in real-world applications is not straightforward and often yields unsatisfactory results. Also, both types of methods do not consider uncertainty in the imputed data. We address these issues by developing a simple neural network-based architecture that works well with small and tabular datasets and utilizing a novel adversarial strategy to estimate the uncertainty of imputed data. The estimated uncertainty scores of features are then passed to the imputer module, and it fills the missing values by paying more attention to more reliable feature values. It results in an uncertainty-aware imputer with a promising performance. Extensive experiments conducted on some real-world datasets confirm that the proposed methods considerably outperform state-of-the-art imputers. Meanwhile, their execution time is not costly compared to peer state-of-the-art methods

Edge Detection in Radar Images Using Weibull Distribution

Radar images can reveal information about the shape of the surface terrain as well as its physical and biophysical properties. Radar images have long been used in geological studies to map structural features that are revealed by the shape of the landscape. Radar imagery also has applications in vegetation and crop type mapping, landscape ecology, hydrology, and volcanology. Image processing is using for detecting for objects in radar images. Edge detection; which is a method of determining the discontinuities in gray level images; is a very important initial step in Image processing. Many classical edge detectors have been developed over time. Some of the well-known edge detection operators based on the first derivative of the image are Roberts, Prewitt, Sobel which is traditionally implemented by convolving the image with masks. Also Gaussian distribution has been used to build masks for the first and second derivative. However, this distribution has limit to only symmetric shape. This paper will use to construct the masks, the Weibull distribution which was more general than Gaussian because it has symmetric and asymmetric shape. The constructed masks are applied to images and we obtained good results.Comment: 9 pages,6 figure

Regulation of Trace Elements by Vitamin A in Paracetamol-induced Liver Toxicity in Rats

Abstract: This study was aiming to determine the effect of the Vitamin A on paracetamol-induced hepatotoxicity. Fifteen rats were randomly divided into five groups; (three rats each) control group, paracetamol (1000 mg/kg body weight) was used to induce hepatotoxicity in albino rats. Vitamin A (Retinyl palmtate) administered at the dose levels of 100, 500 and1000 IU/kg body weights orally for 7 days prior to paracetamol dose. Hepatic toxicity was observed in paracetamol group; aspartate aminotransaminase (AST) level was high as compared with control group (p = 0.003). The significant hepatoprotective effect of Vitamin A was observed at doses 500 and 1000 IU/kg body weight, as there was significant reduction of serum AST when compared to paracetamol group (p = 0.01 and 0.003 respectivly), where 100 IU/Kg vitamin A not significantly decrease AST. Liver trace element determined by X-ray fluorescence (XRF) (K, Ca, Fe, Cu, Zn and Rb) in paracetamol-treated group were found to be higher than that of the control group, although the only significant increase was observed with Cu. Br shows slight decrease compared to the control group. There were no significant differences between Vitamin A groups (100 mg/kg 500mg/kg and 1000mg/kg) and PCM-treated group in the liver tissue content of Ca, K, Zn, Cu, Rb and Br where Fe concentrations were significantly decrease at doses 500 and 1000IU/l (P value 0.05 and 0.045 respectively). Vitamin A shows protective effect by regulating liver tissue Fe. We recommend to perform further investigation on the mechanisms of Vitamin A hepatoprotective mechanisms of action