KNOWLEDGE, ATTITUDES AND PRACTICES REGARDING THE USE OF ANTIBIOTICS: A CROSS-SECTIONAL STUDY FROM A RURAL AREA OF LEBANON

Despite the presence of a national policy restricting the easy access to antibiotics, irrational use of antibiotics continues to be widespread both in human use and livestock production in Lebanon. This study targets the general population in the rural region of Bekaa to assess their knowledge, attitudes and practices (KAP) towards antibiotic use. A cross sectional questionnaire was completed by 1151 participants, through face-to-face interviews. Study population was randomly selected. Descriptive statistics and correlation tests were applied in data analysis. 69.2% of participants had a very poor knowledge about antibiotics. More than 70% believed that viral infections may be treated by antibiotics; interrupting therapy when conditions improve and sharing antibiotics were considered appropriate by 79.4% and 80.3%, respectively. Only 14.1% were aware of the concept of “antibiotic resistance” and 58.3% didn’t know that antibiotics were used in animals. Despite their poor knowledge, more than half of participants (55.2%) expressed good attitude in terms of need for prescriptions (79.1%) when needed only (89.5%) and on the minimal use in agriculture (74%). Such positive attitude was generally reflected by their overall moderate practice among participants (65.8%). Nevertheless, only 10.9% of the participants obtained their antibiotics through a prescription, 62.7% kept leftover antibiotic for future use and 83.2% interrupted their antibiotic treatment. Moreover, participants’ attitudes and practices were significantly associated with gender, age and educational level. However, knowledge was associated only with gender and education. Knowledge showed significant positive correlation with attitude and practice. Findings suggest that intervention awareness programs specifically targeting specific segments in rural regions can be effective in directing the public to the rational use of antibiotics. Further research is recommended by conducting nationwide KAP studies covering communities of both urban and rural regions

A Shortest Data Window Algorithm for Detecting the Power Factor in presence of non-sinusoidal load current

During recent years, nonlinear power electronic equipments introduce harmonic pollution on electric power systems. It makes the traditional power factor meter can not act accurately when it monitors unbalanced and harmonic loads. In this paper, a new algorithm for detecting the power factor in presence of non-sinusoidal load current is proposed. The proposed algorithm detects the true power factor exactly. By uses only two successive sampled data points of the voltage and the current for each displacement power factor value calculation and two sampled data points for each distortion power factor value calculation, the total/true power factor becomes easy to measure using these values directly. The proposed detector implemented using microcontroller as a main part and has been tested for single phase power system. The test results show that it can measure the true power factor of the loads quickly and accurately

Vitamin D deficiency and low hemoglobin level as risk factors for severity of acute lower respiratory tract infections in Egyptian children: A case-control study

AbstractObjectiveAcute lower respiratory tract infection (ALRTI) is an important cause of morbidity in the developed world, and both morbidity and mortality in the developing world. Vitamin D has a major role in both acquired and innate immunity. Anemic children have less oxygen carrying capacity of blood. This study was done to determine the relation between vitamin D deficiency, anemia and the severity of ALRTIs in hospitalized children.MethodsThis study included 96 hospitalized infants with ALRTI, 48 diagnosed with pneumonia and 48 with bronchiolitis. Mean age was 10.67±3.143months. Matched age and sex infants with no respiratory illness were included. Serum 25 hydroxy vitamin D was measured in all cases and controls by Radio-immune assay. Hemoglobin level was measured by Coulter.ResultsVitamin D deficiency and low hemoglobin level were positively correlated with the severity of ALRTIs (r=0.798 and P=0.001) and (r=0.708, P=0.028), respectively. Low vitamin D level was significantly correlated with low hemoglobin level (r=0.708, P=0.028).ConclusionVitamin D deficiency was associated with severity of ALRTIs. Low hemoglobin level was more prevalent in those children. Improving the nutritional status in children by preventing vitamin D deficiency and low hemoglobin might influence the outcome of children with ALRTI

Development of images segmentation using image thresholder and batch processing technique on the blood smears

Image segmentation is an important part of image processing, and one of the most common approaches is threshold segmentation. A new segmentation technique with each pixel in the image has its own threshold is developed in response to the fact that standard threshold-based segmentation algorithms only establish one or many thresholds, making it difficult to extract the complex information in an image. This work employs image segmentation tools to examine images of thin blood smears data set. The goal is to explore options for a noniterative-based and automated system for detecting parasites in blood smears. This can be achieved by detecting the presence of a parasite in thin blood smears and quantifying the portion of red blood cells in the sample that are infected. First, we try segmenting the individual red blood cells from the background using the color thresholder. Next, we clean up the obtained cell mask and examine cell properties using the image region analyzer function, which allows quickly filling in region holes and filtering out regions based on their properties such as area dimensions or eccentricity. Then quickly gauge and specify the expected diameter range of the cells in pixels and indicate that the circles are dark relative to the background. Finally, we've combined the code for finding circles matching image histograms and the parasite threshold detection logic into a single function to quickly examine the performance of this function on the other images using the image batch processing technique. The proposed detection function labels the detected cells with blue circles the parasites are marked in red and the infected cells are highlighted in green. The proposed algorithm has appropriately compensated for the variability in image quality

COMPUTER-AIDED DESIGN OF ALGORITHMIC STATE MACHINE

The Algorithmic State Machine (ASM) is a method used to solve more complex industrial problems. The basic advantage of this method is to convert these problems to simpler circuits which consist only from the basic elements which are AND, OR and NOT gates, which can be implemented easily by using the Programmable Logic Array (PLA) circuits. The entry variables (number of inputs and states) for such problems are large, this made the theoretical (manual) solution is hard to solve. This research constructs a computer package called (ASM-CAD) to make the entire design using C++ and TC++ programming languages. Key Words: Algorithmic State Machine (ASM) method.Programmable Logic Array (PLA) circuit. Quine-McCluskey is a programmable method. 1

Evaluation of different laboratory methods for rapid diagnosis of tuberculous pleurisy*

Background/Objective: Tuberculous pleurisy is a diagnostic challenge due to its nonspecific clinical presentation, paucibacillary nature of the effusion together with the inefficiency of conventional laboratory methods motivating the evaluation of variable diagnostic strategies. Methods: Using thoracoscopy, the pleural cavity of 50 patients with undiagnosed exudative pleural effusion were fully examined and biopsy specimens of affected parietal pleura were taken under direct vision. Pleural fluid and biopsy specimen were subjected to microscopic examination (direct and after cytocentrifugation), culture, PCR, and histopathological examination. Results: The pleural biopsy specimens proved to have a higher detection rate of tubercle bacilli than pleural fluid. Also, cytocentrifugation improved the sensitivity of microscopic detection for both pleural fluid and biopsy specimens. Conclusion: The combination of microbiological results and histopathology examination of the pleural biopsy specimens is essential for the diagnosis of tuberculous pleurisy, as microbiological examination of pleural biopsy specimens has proved to have a higher detection rate than pleural fluid examination

Exploring the lived experience of Jordanian male nurses : a phenomenological study

Background: Human beings have an inbuilt desire to care and nurture others. In some professions such as nursing, women are perceived as privileged in relation to these traits, and women are in the majority in the nursing profession. The Gender theory suggests that men should adapt to feminine traits and nature in order to fit in the nursing profession. However, there is a paucity of literature in relation to Arab male nurses’ experience in nursing. Purpose: The purpose of this study was to explore the Jordanian male nurses’ experiences of their career within their Arabic community. Methods: A hermeneutic phenomenological approach, underpinned by VanManen’s perspective was used. Twenty-two Jordanian male nurses were approached from four hospitals in Jordan. Four focus groups comprising 5-6 interviewees in each were used. The focus groups were audio-recorded and transcribed verbatim. The data were analyzed using Van Manen’s hermeneutic approach and themes extracted from the Arabic version were compared critically with the analysis of the English version to develop the meaning of the narratives. Discussion: Three major themes emerged from the data: (i) personal gains; (ii) masculinity; (iii) and cultural influences. Whilst male nurses recognized nursing is a female dominant profession, they viewed themselves as more independent in decision making and more productive than their female counterparts. Significantly, the participants described nursing as a means of fulfilling their spiritual needs and thus a personal gain. The interviewees linked their masculinity to resilience and endurance. Participants described that men in nursing face some social constraints within the Arab community. Conclusion: The study findings partly supported the fact that nursing in Jordan is a predominantly female profession which lends support to the gender theory in which Jordanian male nurses experienced a social bias and disadvantages by Arabic culture stereotypes of a male nurse. Although nursing is still a feminine career, the findings of this study raise awareness that gender role stereotype might not hold a strong stance in relation to nursing and that could be attributed to elements such as economic and payment status

Toward Model-Generated Household Listing in Low- and Middle-Income Countries Using Deep Learning

While governments, researchers, and NGOs are exploring ways to leverage big data sources for sustainable development, household surveys are still a critical source of information for dozens of the 232 indicators for the Sustainable Development Goals (SDGs) in low- and middle-income countries (LMICs). Though some countries’ statistical agencies maintain databases of persons or households for sampling, conducting household surveys in LMICs is complicated due to incomplete, outdated, or inaccurate sampling frames. As a means to develop or update household listings in LMICs, this paper explores the use of machine learning models to detect and enumerate building structures directly from satellite imagery in the Kaduna state of Nigeria. Specifically, an object detection model was used to identify and locate buildings in satellite images. In the test set, the model attained a mean average precision (mAP) of 0.48 for detecting structures, with relatively higher values in areas with lower building density (mAP = 0.65). Furthermore, when model predictions were compared against recent household listings from fieldwork in Nigeria, the predictions showed high correlation with household coverage (Pearson = 0.70; Spearman = 0.81). With the need to produce comparable, scalable SDG indicators, this case study explores the feasibility and challenges of using object detection models to help develop timely enumerated household lists in LMICs