Astromag data system concept

A feasible, top-level data system is defined that could accomplish and support the Astromag Data System functions and interfaces necessary to support the scientific objectives of Astromag. This data system must also be able to function in the environment of the Space Station Freedom Manned Base (SSFMB) and other anticipated NASA elements

Effect of antenatal group discussion on fear of childbirth among pregnant women in a Nigerian tertiary hospital

Background: Antenatal group discussions (AGDs) are utilized in antenatal peer support. Its application in controlling fear of childbirth (FOC) has not been widely studied in Africa. We examined the effect of AGDs on FOC among pregnant women. Methods: This experiment was done between in 2020 at a teaching hospital in Nigeria. We randomly assigned 218 consenting primigravid women into treatment (n = 111) and control groups (n = 107) and followed them from 31 to 38 weeks of gestation. The treatment group had one AGD session per week for 6 weeks, with each session lasting 120 minutes. The control group had no AGDs. The FOC Questionnaire was used for collecting data at 31 and 38 weeks of gestation. Inferential statistics were used for data analyses at a 5% significance level using SPSS 21. Results: At 31 weeks of pregnancy, 80.2% and 72.9% of participants in the treatment and control groups had unhealthy FOC (range 5 - 9) with no significant difference between the groups (p = 0.204). At 38 weeks, FOC was significantly less in the treatment group compared to the control group (17.1% vs. 48.6%, p<0.001). The AGD reduced the likelihood of unhealthy FOC by 65.0% (RR: 0.35, 95%CI: 0.22 - 0.55). Conclusions: Participation in AGDs reduced FOC among pregnant women, hence recommended. The current caesarean statistics may further reduce if pregnant women were encouraged to utilize AGDs.

"Aegean Seals of the Late Bronze Age: Stylistic Groups. VII. Concordance"

The seventh, and last, in a series of articles attributing Aegean sealstones and finger rings of the Late Bronze Age to stylistic groups

Average glandular doses and national diagnostic reference levels in mammography examinations in Turkey

In order to establish national diagnostic reference levels for mammography examinations, entrance skin air kerma, entrance skin dose and average glandular doses (AGDs) were calculated for a total of 25 624 cranio-caudal (CC) and mediolateral oblique (MLO) projections of 6309 patients for 40-49 and 50-64 age groups. The average entrance skin air kerma and entrance skin dose values for both age groups were found to be higher in MLO projections compared with CC projections. The minimum and maximum values of AGDs were determined as 0.4 and 7.9 mGy for both projections. The maximum numbers of AGDs for CC and MLO projections were calculated in the range of 1.1-1.5 and 1.6-2.0 mGy, respectively. The third quartile values of AGDs were calculated for each compressed breast thickness between 20 and 99 mm. The first national diagnostic reference levels of the country were established for each 10-mm compressed breast thickness in mammography examinations.Turkish Atomic Energy AuthorityMinistry of Energy & Natural Resources - Turke

A comparison between sire and animal model for lifetime Production traits in Egyptian buffaloes

A total of 1621 lactation records of Egyptian buffaloes, kept at Mehalet Mousa farm, belonging to the Animal production Research Institute, Ministry of Agriculture, were used. Data were analyzed by using sire model (SM) and animal model (AM). For SM, the model includes the fixed effects of year and month of birth and age at first calving as covariate and sire as a random effect. For AM, the model includes the fixed effects of month and year of birth and random effects of animals and errors on lifetime milk yield (LTMY), total lactation period (TLP), age at disposal (AGDS) and number of lactation completed (NLC). Means were 10552 kg, 1173 d, 125 mo., and 5.97 for LTMY, TLP, AGDS and NLC, respectively. Estimates of heritability from sire model were 0.45, 0.18, 0.90 and 0.36 for LTMY, TLP, AGDS and NLC, respectively and from AM were 0.27, 0.17, 0.12 and 0.06 for above traits studied, respectively. Estimates of phenotypic correlations among traits studied ranged from 0.55 to 0.73 for SM and for AM 0.40 to 0.80 and genetic correlations among traits studied ranged from 0.19 to 0.96 for SM and from AM ranged from 0.10 to 0.98. Rank correlations among lifetime and longevity traits as estimated from SM were positive and highly significant (P<0.01) and ranged from 0.08 to 0.98 as estimated from SM. Rank correlations of sire transmitting ability among lifetime and longevity traits as estimated from AM were positive and significant (P <0.01) and ranged from 0.33 to 0.88

La colección cluniense de glíptica

Se analizan diferentes entalles y un camafeo procedentes de la ciudad romana de Clunia. Tanto los temas grabados en ellos como los materiales empleados en su confección son los habituales en la glíptica del momento. Su cronología abarca desde los momentos finales del s. I d.C. hasta el s. III d.C.We analyse various engraved gems and a cameo from the Roman city of Clunia. 80th the subjects engraved as well as the materials used are those commonly found in contemporary glyptics. The pieces analysed date from the late first century A.D. to the third century A.D

Analyzing the Real-World Applicability of DGA Classifiers

Separating benign domains from domains generated by DGAs with the help of a binary classifier is a well-studied problem for which promising performance results have been published. The corresponding multiclass task of determining the exact DGA that generated a domain enabling targeted remediation measures is less well studied. Selecting the most promising classifier for these tasks in practice raises a number of questions that have not been addressed in prior work so far. These include the questions on which traffic to train in which network and when, just as well as how to assess robustness against adversarial attacks. Moreover, it is unclear which features lead a classifier to a decision and whether the classifiers are real-time capable. In this paper, we address these issues and thus contribute to bringing DGA detection classifiers closer to practical use. In this context, we propose one novel classifier based on residual neural networks for each of the two tasks and extensively evaluate them as well as previously proposed classifiers in a unified setting. We not only evaluate their classification performance but also compare them with respect to explainability, robustness, and training and classification speed. Finally, we show that our newly proposed binary classifier generalizes well to other networks, is time-robust, and able to identify previously unknown DGAs.Comment: Accepted at The 15th International Conference on Availability, Reliability and Security (ARES 2020