SOS teeth with advanced caries and sociodemographic indicators, health-related habits and dental attendance patterns: data from the Dental, Oral, Medical Epidemiological (DOME) nationwide records-based study

Background "SOS teeth" are teeth that need to be treated first, and represent dental teeth with deep caries seen clinically and radiographically which may require root canal treatment or extraction. The aims of the present research were to study the associations of SOS teeth with: socio-demographic parameters, dental attendance patterns, health-related habits among young to middle-aged adults. Methods This cross-sectional records-based research analyzed data from the Dental, Oral, Medical Epidemiological (DOME) repository that captures comprehensive socio-demographic, medical, and dental databases of a nationwide sample of 132,529 records of dental attendees to military dental clinics for 1 year aged 18 to 50 years. Results SOS teeth had a significant positive association in the multivariate analysis with male sex [OR 1.137, 95% Confidence Interval (CI): 1.079–1.199], rural versus urban Jewish locality [OR 1.748 (1.082–2.825)], and consumption of sweetened beverages [OR 1.415 (1.337–1.496)]. SOS teeth retained significant negative associations (protective parameter) with academic [OR 0.647 (0.592–0.708)] and technicians (OR 0.616 (0.556–0.682)] compared to high school education, high [OR 0.437 (0.401–0.476)], and medium (OR 0.648 (0.598–0.702)] versus low socio-economic status, urban non-Jewish versus urban Jewish locality [OR 0.746 (0.693–0.802)], Asia (OR 0.658 (0.452–0.959)], North America (OR 0.539 (0.442–0.658)] and Israel [OR 0.735 (0.686–0.788)] versus western Europe birth countries. Conclusions Health authorities should be familiar with this profile of the patient who is vulnerable to SOS teeth and formulate policies and allow the appropriate implementation of strategies in those in high-risk populations.

Attendance Monitoring System of Schools in the Philippines with an Inclusion of Optimization Query Algorithm

In this paper, researchers had provided definite solutions in order to check and validate student attendance with the use of computerized seat plans along with the information and image of each student. This study also discussed the inclusion of Optimization Query Algorithm in order to identify and monitor student’s punctuality as well as the analysis of the reasons why they fail to attend their class. Attendance patterns are formed early in life because it validates one of the components of student’s academic and scholastic performance. Regular attendance is vital part of the grading component necessary to attain some portion of the student’s academic progress. You are missing out on active learning experiences and class attendance. As a result, they are more likely to to fail which tends to affect their academic performances.

Breeding site attendance and breeding success in Phyllomedusa trinitatis (Anura: Phyllomedusidae)

Using a natural marker, we documented breeding site attendance patterns by males and females of the Trinidad Leaf Frog, Phyllomedusa trinitatis. We followed attendance at a cluster of three isolated ponds over 53 and 56 consecutive nights in 2016 and 2019 respectively. Most females attended only once, but for those that attended more than once we calculated an inter-nesting interval (mean 27.6 days, N = 7). Males showed high pond fidelity, but some did attend at two of the ponds, always with a strong preference for one of them. Males showed three attendance patterns. A few attended on multiple consecutive nights (maximum, 19 nights); more were sporadic (one attended seven times over 46 nights with gaps of 15 and 19 days in the sequence); some attended only once (2016: 12, 2019: 15), but most were found to be present on multiple nights (2016: 38, 2019: 32). Our analysis suggested that these latter frogs were either newly recruited individuals or had been predated during the study. Our data show that rainfall has some influence on attendance. We found no relationship between male body condition and attendance pattern. In addition, there was no evidence that a particular male attendance pattern was optimal for breeding success.

Comparative egg attendance patterns of incubating polar petrels

Background The internal environment of eggs in most birds is regulated by transferring heat energy through contact incubation, maintaining nest microclimate, and frequent egg turning by the incubating parent on its nest. However, we lack information about egg attendance patterns in birds that breed in polar environments where variations in life history are expected to influence incubation behavior. Moreover, crevice/burrow nesting petrels in high-latitude regions are known for periodically leaving their egg unattended (hereafter ‘egg neglect’), but there is little reporting on the internal condition of unattended eggs. At Dumont d’Urville Station, Antarctica, we studied the incubation behavior of 24 snow (Pagodroma nivea) and 15 Cape (Daption capense) petrel pairs using egg loggers that recorded egg turning rates, orientation changes, and temperatures at 1 Hz for durations of 3–6 days. Results Egg turning frequency (1.31 ± 0.33 vs. 1.38 ± 0.39 turns h−1), angle change per turn (43.1 ± 43.2 vs. 48.6 ± 43.7° turn−1), and egg temperature (34.1 ± 2.3 vs. 34.1 ± 2.0 °C) were nearly identical for snow and Cape petrels, respectively. However, egg neglect was only observed in snow petrel nests (based on egg temperature changes) where loggers recorded mean durations of 1.34 ± 1.15 days (maximum duration of 3.63 days). During periods of neglect, eggs cooled to 5.5 ± 1.8 °C over an average of 91 min, but were rewarmed by parents in only 76 min at a rate of 0.33 °C min−1. Conclusions Egg temperatures of both species during regular incubation were within 1–2 °C of other high-latitude petrel species, but neglected snow petrel eggs remained several degrees above freezing, which was likely attributed to crevice nesting where neglected eggs are buffered by environmental conditions. Using egg rewarming rates, thermal capacity of eggs, and published metabolic rates, we estimate egg rewarming costs in snow petrels to be 1.5 to 1.9 × BMR. Excluding egg neglect periods, turning rates for both petrel species were lower than other seabirds studied using biologging devices, which may be associated with the prolonged incubation periods that are characteristic of procellariiform seabirds.

College Quality and Attendance Patterns: A Long-Run View

We construct a time series of college attendance patterns for the United States and document a reversal: family background was a better predictor of college attendance before World War II, but academic ability was afterward. We construct a model of college choice that explains this reversal. The model’s central mechanism is that an exogenous surge of college attendance leads better colleges to be oversubscribed, institute selective admissions, and raise their quality relative to their peers, as in Hoxby (2009). Rising quality at better colleges attracts high-ability students, while falling quality at the remaining colleges dissuades low-ability students, generating the reversal. (JEL I23, J12, N32)

Student Attendance Pattern Detection and Prediction

Since the early beginnings of education systems, attendance has always played a crucial role in student success, as well as in the overall interest of the matter. The most productive way of increasing the student attendance rate is to understand why it decreases, try to predict when it is going to happen, and act on causing factors in order to prevent it. Many benefits of predicted and increased attendance rate can be achieved, including better lecture organization (i.e. lecture time and duration, lecture class choice, etc). This paper describes the steps in the extraction of knowledge from the university's student database and making a model that predicts whether the student will attend the class or not. Results show that the attendance patterns are best reflected when employing a decision tree algorithm, a C4.5 model that is interpretable and able to predict the attendance with 0.81 AUC performance measure