Assessment of Population pressure on Urban Housing in Ngwa Road, Ohanku and Obohia Parts of Aba South, Abia State Nigeria

The effect of population growth on urban housing is a global challenge but the worst examples are found in the developing world which has led to an increased growth of poorly planned cities in the developing world, and loss of aesthetics. The aim of this research is to assess the level of population pressure on urban housing within Ngwa Road, Ohanku and Obohia environs in Aba South local government area in Abia State. The research evaluated housing demand and supply in the area, condition of houses in the area, factors encouraging population growth in the study area and level of compliance of buildings with town planning laws. The study area has an estimated 2021 population of 138017 as projected from 88,951 in 2016 with a growth rate of 2.94%. The research data was collected through household survey, Aba South Town Planning Authority, National Population Commission and the Aba South Street Naming and House Numbering Office. The simple random sampling technique and the purposive sampling technique were employed by the researcher with a sample size of 399.9 at 0.05 confidence level which was determined using the Taro Yamane method for sample size collection. The Principle Component Analysis (PCA), Principle Component Regression (PCR), standard deviation, weighted mean, percentages/proportions to analyze the data collected. The Principal Component Analysis result showed that component I have the highest loading with eigen value of 6.721 while component II has an eigen value of 3.279. The result showed that ease of access to commercial activities and educational level of heads of households are major factors encouraging population growth in the study area. The research revealed a housing demand and supply cluster estimate of 60.11% which was not considered statistically high. The average response of 93.2% is that houses in the study area are in a poor condition. The Aba South town planning authority revealed a 0.741 standard deviation which shows a high level of non-compliance with town planning laws. The research hypothesis was tested using Spearman Rank Correlation test at 0.05 level of confidence and the null hypothesis was accepted. Looking at the Land-UseLand-Cover images of the area obtained for 3 epochs from 1980-2020, the study area experienced an major growth in rate of housing stock after year 2000 and with increasing population growth, the area may soon be unable to carry the population that will be found there. This research calls the attention of the Abia State government in particular and the federal government in general to address these challenges through recommended public-private partnership and decentralization of pull factors. These recommendat

A Roadway Safety Sustainable Approach: Modeling for Real-Time Traffic Crash with Limited Data and Its Reliability Verification

With the development of freeway system informatization, it is easier to obtain the traffic flow data of freeway, which are widely used to study the relationship between traffic flow state and traffic safety. However, as the development degree of the freeway system is different in different regions, the sample size of traffic data collected in some regions is insufficient, and the precision of data is relatively low. In order to study the influence of limited data on the real-time freeway traffic crash risk modeling, three data sets including high precision data, small sample data, and low precision data were considered. Firstly, Bayesian Logistic regression was used to identify and predict the risk of three data sets. Secondly, based on the Bayesian updating method, the migration test towards high and low precision data sets was established. Finally, the applicability of machine learning and statistical methods to low precision data set was compared. The results show that the prediction performance of Bayesian Logistic regression improves with the increasing of sample size. Bayesian Logistic regression can identify various significant risk factors when data sets are of different precision. Comparatively, the prediction performance of the support vector machine is better than that of Bayesian Logistic. In addition, Bayesian updating method can improve the prediction performance of the transplanted model.

Anatomical Evaluation of Root and Root Canal Configuration of Permanent Maxillary Dentition in the Population of the Kingdom of Saudi Arabia

Aim. This study is aimed at combining the sample sizes of all studies on permanent maxillary teeth conducted in different regions of the Kingdom of Saudi Arabia (KSA) to obtain a large sample size that represents the population of the KSA. The outcome of these combined studies is compared with international studies in terms of the number of roots, number of canals, and canal configurations on the basis of Vertucci’s classification. Methodology. The studies were systematically reviewed using the Preferred Reporting Items for Systematic Review and Meta-analysis chart. Studies were included in the analysis if they were conducted in the KSA, involved permanent human maxillary teeth, and had a sample of more than 10 teeth (power). By contrast, studies were excluded if they involved deciduous teeth in the sample size, investigated nonhuman teeth, were not conducted in the KSA, and were case reports, case series, review studies, and anomalies. Relevant literature was searched from PubMed, Scopus, Web of Science, Embase, Cochrane, and Direct Science by two calibrated teams, starting in August 2020, without time limits or language restrictions. Results. The database searches and cross-referencing identified a total of 19 relevant studies. All maxillary canines ( N = 1,018 ) had one root, whereas 98.4% had one canal and 98.3% had Vertucci type I. Moreover, 63.2% of the maxillary first premolars had two roots, and 91.4% had two canals. The most common Vertucci root canal configuration was type IV (64.6%). The maxillary second premolars mostly had one root (84.4%) and one canal (50.4%). The most common canal configuration was Vertucci type I (47.1%). The majority of maxillary first molars had three roots (98.9%), 48.7% of which had three canals, and 46.4% had four canals. The most prevalent feature of the canal morphology of mesiobuccal roots was Vertucci type II (35.3%). The investigated maxillary second molars had three roots, 88.0% of which had three canals. Conclusion. This systematic review represents the Saudi population since samples were combined from different studies from different regions of the country. Variations in findings were observed in the same group of teeth from different regions and the same region, while the overall combined samples results fell within the range of other international studies.

Critical Issues of Working during the COVID-19 Pandemic: Italian Healthcare Workers’ Experience

Background: The COVID-19 pandemic has strongly impacted on healthcare services’ organization and healthcare workers’ mental health, increasing the risk of psychological symptoms and burnout. Italy has been one of the most affected countries, especially the northern regions, even with exceptions in some rural provinces. Aim: We chose to investigate the mental health conditions of healthcare workers operating in the rural province of Rovigo (a small town in Veneto, northern Italy), where relatively few deaths and contagions were reported during the pandemic, even if Veneto—globally—was one of the most affected regions of Italy. We wanted to verify the psychological outcomes of health workers operating in a context where the impact of the pandemic appeared to be relatively mild. Methods: Through an online survey, we investigated perceived difficulties at work and in daily life, perceived loneliness and social support, coping strategies, and level of psychological distress (sample size: 749; mean age = 48.04 years, SD = 10.66). The questionnaire had both open- (2) and close-ended questions (5 single-choice and 13 multiple-choice). We verified possible associations between sex, age group, work department and percentage of responses with chi-square tests of independence on each question. Data cleaning excluded all contradictory answers from the multiple-choice questions from the analyses (final sample size: 640). Results: Frontliners and non-frontliners reported a similar experience of the COVID-19 pandemic (without significant differences in perceived difficulties, coping strategies and sources of support). Nevertheless, they still reported various forms of negative emotions (e.g., helplessness—40.94%; sadness—36.56%; frustration—32.66%) and lack of support from the health organization (especially frontliners—28.72%). However, psychological help was scarcely requested. Conclusions: Despite the province not being massively affected by the pandemic, healthcare workers felt the need for clearer and more supportive guidance. They seem to perceive collective opportunities to share needs and difficulties as more useful than individual interventions (as those provided by the ad hoc created listening service).

FREQUENCY OF COMMON FACTORS INFLUENCING THE GRAFT UPTAKE IN MYRINGOPLASTY AMONG THE TERTIARY CARE HOSPITAL KPK

Introduction: Tympanoplasty refers to any operation involving reconstruction of the tympanic membrane and /or the ossicular chain. Myringoplasty is a tympanoplasty without ossicular reconstruction. Over the years many methods have been used for closing perforations. Myringoplasty was introduced by Berthold in 1878 but the modern era began only in 1950s with the work of Wullstein and Zoellner. The study aims to analyse the common factors which are predictive of success of myringoplasty in adult patients and to construct and validate a prognostic index that could be used as tool to predict the success of myringoplasty in adults. Objectives: To determine the frequency of common factors influencing the graft uptake in myringoplasty. Materials and Method: In this study, a total sample size was 376, using 4.08% proportion of fourth degree perineal tear, 95% confidence level and 2% margin of error under WHO software for sample size determination. Moreover, consecutive non probability sampling technique was used. Results: The mean age was 40 years with standard deviation of ± 2.63. Sixty two percent of the patients were male while thirty eight percent patients were female. The success rate of myringoplasty was 90% while the failure rate was 15(10%) patients in which 4(25%) patients had medium perforation, 5(33%) patients had large perforation while 6(42%) patients had subtotal perforation. Regarding the causes of perforation among 15(10%) patients, 13(85%) patients had infection while only 2 patients had trauma. Conclusion: The study concludes that infection (85%) was the most common cause of perforation followed by trauma (15%) in the graft uptake in myringoplasty.

Methodology for Interactive Labeling of Patched Asphalt Pavement Images Based on U-Net Convolutional Neural Network

Image recognition based on deep learning generally demands a huge sample size for training, for which the image labeling becomes inevitably laborious and time-consuming. In the case of evaluating the pavement quality condition, many pavement distress patching images would need manual screening and labeling, meanwhile the subjectivity of the labeling personnel would greatly affect the accuracy of image labeling. In this study, in order for an accurate and efficient recognition of the pavement patching images, an interactive labeling method is proposed based on the U-Net convolutional neural network, using active learning combined with reverse and correction labeling. According to the calculation results in this paper, the sample size required by the interactive labeling is about half of the traditional labeling method for the same recognition precision. Meanwhile, the accuracy of interactive labeling method based on the mean intersection over union (mean_IOU) index is 6% higher than that of the traditional method using the same sample size and training epochs. In addition, the accuracy analysis of the noise and boundary of the prediction results shows that this method eliminates 92% of the noise in the predictions (the proportion of noise is reduced from 13.85% to 1.06%), and the image definition is improved by 14.1% in terms of the boundary gray area ratio. The interactive labeling is considered as a significantly valuable approach, as it reduces the sample size in each epoch of active learning, greatly alleviates the demand for manpower, and improves learning efficiency and accuracy.

Partner’s Perceived Social Support Influences Their Spouse’s Inflammation: An Actor–Partner Analysis

Social support has been linked to lower cardiovascular morbidity and mortality. However, most studies have examined perceived support as an intrapersonal construct. A dyadic approach to social support highlights how interdependence between individuals within relationships, including partner perceptions and interactions, can influence one’s health. This study’s overall purpose was to test actor–partner models linking perceived social support to inflammation. Ninety-four cisgender married couples completed perceived support measures and had their blood drawn for CRP and IL-6 to produce an overall inflammatory index. The primary results indicate that only a partner’s level of perceived support was related to lower inflammation in their spouse. Our sample size, although moderate for inflammatory studies, was probably not large enough to detect actor influences. These data highlight the importance of taking a dyadic perspective on modeling perceived support and its potential mechanism.

An Extension of Testlet-Based Equating to the Polytomous Testlet Response Theory Model

Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling. However, the violation of the local item independence assumption is inevitable when tests are built using testlet items. In this study, simulations are conducted to evaluate the performance of item response theory models and testlet response theory models for both the dichotomous and polytomous items in the context of equating tests composed of testlets. We also examine the impact of testlet effect, length of testlet items, and sample size on estimating item and person parameters. The results show that more accurate performance of testlet response theory models over item response theory models was consistently observed across the studies, which supports the benefits of using the testlet response theory models in equating for tests composed of testlets. Further, results of the study indicate that when sample size is large, item response theory models performed similarly to testlet response theory models across all studies.