Parasite Detection Model for Neglected Tropical Disease Diagnosis

Kato-katz is the most commonly used microscopy-based technique in the diagnosis of Neglected Tropical Diseases (NTDs). This paper describes the preliminary studies that are involved in the automated detection of parasitic eggs in a given Kato-katz image. The studies involve application of pattern recognition techniques based on template matching to detect the presence of parasites in the images of kato-katz slides. The results from this study indicate that using a combination of image segmentation and pattern recognition algorithms generates better results as they deal with the complex nature of the images, such as their spurious intensity patterns and shapes. Clinical Relevance— This paper describes interdisciplinary work that applies image processing algorithms to kato-katz images to solve clinical parasitology problems

Evaluating Delay Causes for Constructing Road Projects in Saudi Arabia

In this paper, we evaluate the causes of delays in road construction projects in Saudi Arabia. The research identifies four main groups of delay causes: external factors, contractor-related factors, project management factors, and environmental factors. External factors include changes in regulations and delays in obtaining permits and approvals. Contractor-related factors include inadequate resources and poor project planning. Project management factors encompass ineffective communication and poor coordination among stakeholders. Environmental factors include adverse weather conditions and unforeseen site conditions. The study recommends measures such as improved coordination, enhanced contract management, and advanced project management techniques to mitigate these delay causes. The findings provide valuable insights for stakeholders involved in road infrastructure development in Saudi Arabia, enabling them to implement strategies for timely project delivery and improved project performance

The growth and characterization of GaInSe2 single Crystals

GalnSe(2) single crystals have been grown and characterized by experimental techniques such as high-resolution transmission electron microscopy, x-ray diffraction, x-ray photoelectron spectroscopy and optical and electrical measurements. The samples were prepared in single-crystal form from a melt. The structural analysis indicates that GalnSe(2) has a hexagonal structure, and confirms the high quality of the produced single crystals. Quantitative information on electrical and optical properties of single-crystalline GalnSe(2) was obtained by investigating the resistivity and photoluminescence as a function of the temperature and excitation intensity

The application of artificial intelligence in diabetic retinopathy screening: a Saudi Arabian perspective

IntroductionDiabetic retinopathy (DR) is the leading cause of preventable blindness in Saudi Arabia. With a prevalence of up to 40% of patients with diabetes, DR constitutes a significant public health burden on the country. Saudi Arabia has not yet established a national screening program for DR. Mounting evidence shows that Artificial intelligence (AI)-based DR screening programs are slowly becoming superior to traditional screening, with the COVID-19 pandemic accelerating research into this topic as well as changing the outlook of the public toward it. The main objective of this study is to evaluate the perception and acceptance of AI in DR screening among eye care professionals in Saudi Arabia.MethodsA cross-sectional study using a self-administered online-based questionnaire was distributed by email through the registry of the Saudi Commission For Health Specialties (SCFHS). 309 ophthalmologists and physicians involved in diabetic eye care in Saudi Arabia participated in the study. Data analysis was done by SPSS, and a value of p < 0.05 was considered significant for statistical purposes.Results54% of participants rated their level of AI knowledge as above average and 63% believed that AI and telemedicine are interchangeable. 66% believed that AI would decrease the workforce of physicians. 79% expected clinical efficiency to increase with AI. Around 50% of participants expected AI to be implemented in the next 5 years.DiscussionMost participants reported good knowledge about AI. Physicians with more clinical experience and those who used e-health apps in clinical practice regarded their AI knowledge as higher than their peers. Perceived knowledge was strongly related to acceptance of the benefits of AI-based DR screening. In general, there was a positive attitude toward AI-based DR screening. However, concerns related to the labor market and data confidentiality were evident. There should be further education and awareness about the topic

Path analysis of the relationship between optimism, humor, affectivity, and marital satisfaction among infertile couples

Marital satisfaction is an important factor for establishing a family relationship, feeling satisfied, and living happily together. The aim of the present study was to investigate the relationship between optimism, humor, positive and negative affect, and marital satisfaction among infertile couples. The sample comprised 80 infertile Iranian couples (n = 160) who visited infertility clinics. Participants completed a series of Persian versions of psychometric scales related to optimism (Attributional Style Questionnaire), humor (Humor Styles Questionnaire), marital satisfaction (Enrich Marital Satisfaction Questionnaire), positive affect (PA) and negative affect (NA) (Positive and Negative Affect Schedule). The obtained result of Smart PLS statistical analysis confirmed the significant positive correlation between optimism and humor with marital satisfaction and high PA and low NA. Moreover, the findings also provided an adequate fit of the model. The findings demonstrated that infertile couples high in optimism and humor have higher levels of marital satisfaction and high PA and low PA. Based on the study’s findings, interventions for facilitating optimism and humor among infertile couples are discussed

Mental health in the slums of Dhaka - a geoepidemiological study

Gruebner O, Khan MH, Lautenbach S, et al. Mental health in the slums of Dhaka - a geoepidemiological study. BMC Public Health. 2012;12(1): 177.Background: Urban health is of global concern because the majority of the world's population lives in urban areas. Although mental health problems (e.g. depression) in developing countries are highly prevalent, such issues are not yet adequately addressed in the rapidly urbanising megacities of these countries, where a growing number of residents live in slums. Little is known about the spectrum of mental well-being in urban slums and only poor knowledge exists on health promotive socio-physical environments in these areas. Using a geo-epidemiological approach, the present study identified factors that contribute to the mental well-being in the slums of Dhaka, which currently accommodates an estimated population of more than 14 million, including 3.4 million slum dwellers. Methods: The baseline data of a cohort study conducted in early 2009 in nine slums of Dhaka were used. Data were collected from 1,938 adults (>= 15 years). All respondents were geographically marked based on their households using global positioning systems (GPS). Very high-resolution land cover information was processed in a Geographic Information System (GIS) to obtain additional exposure information. We used a factor analysis to reduce the socio-physical explanatory variables to a fewer set of uncorrelated linear combinations of variables. We then regressed these factors on the WHO-5 Well-being Index that was used as a proxy for self-rated mental wellbeing. Results: Mental well-being was significantly associated with various factors such as selected features of the natural environment, flood risk, sanitation, housing quality, sufficiency and durability. We further identified associations with population density, job satisfaction, and income generation while controlling for individual factors such as age, gender, and diseases. Conclusions: Factors determining mental well-being were related to the socio-physical environment and individual level characteristics. Given that mental well-being is associated with physiological well-being, our study may provide crucial information for developing better health care and disease prevention programmes in slums of Dhaka and other comparable settings

COVID-19 vaccine acceptance and hesitancy in low- and middle-income countries

Widespread acceptance of COVID-19 vaccines is crucial for achieving sufficient immunization coverage to end the global pandemic, yet few studies have investigated COVID-19 vaccination attitudes in lower-income countries, where large-scale vaccination is just beginning. We analyze COVID-19 vaccine acceptance across 15 survey samples covering 10 low- and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in our LMIC samples (mean 80.3%; median 78%; range 30.1 percentage points) compared with the United States (mean 64.6%) and Russia (mean 30.4%). Vaccine acceptance in LMICs is primarily explained by an interest in personal protection against COVID-19, while concern about side effects is the most common reason for hesitancy. Health workers are the most trusted sources of guidance about COVID-19 vaccines. Evidence from this sample of LMICs suggests that prioritizing vaccine distribution to the Global South should yield high returns in advancing global immunization coverage. Vaccination campaigns should focus on translating the high levels of stated acceptance into actual uptake. Messages highlighting vaccine efficacy and safety, delivered by healthcare workers, could be effective for addressing any remaining hesitancy in the analyzed LMICs.Publisher PDFPeer reviewe