Miracle-dz/UniFAR-FTUs huggingface dataset:
Caries prevalence among schoolchildren in Zagreb, Croatia

Aim To investigate the prevalence of dental caries and treatment needs in schoolchildren aged 7-14 years from Zagreb. Methods Dental examinations based on the World Health Organization criteria were performed on 1168 children in the period 2009-2010. The teeth were clinically examined with standard dental instruments using visual-tactile method under standard dental light. We recorded the clinical indexes of decayed, missed, and filled teeth (DMFT and dmft; upper-case letters refer to permanent and lower-case letters to primary teeth) and decayed, missed, and filled surfaces (DMFS), as well as the significant caries index (SiC). Results The median DMFT and DMFS of all children were 3 and 4, respectively. The median DMFT and DMFS of 12-year-old children were 4 and 5, respectively. The highest median DMFT score of 7 was found among 14-year-old children. There was a significant difference between age groups (7-10 years and 11-14 years) in DMFT and DMFS. Among 8-year-old children, the median dmft index was the highest (5.5) and SiC index was 7.4. As far as the location of caries on the surface of the first permanent molar is concerned, caries occurred mostly in the central occlusal surface (27.6%). Conclusion Our results showed a high caries prevalence among schoolchildren in Zagreb, indicating a need for an extensive program of primary oral health care.
the Testis Mamu-AG Is Expressed in the Placenta and Nonclassical MHC Class I Molecule A Soluble Isoform of the Rhesus Monkey

The nonclassical MHC class I locus HLA-G is expressed primarily in the placenta, although other sites of expression have been noted in normal and pathological situations. In addition, soluble HLA-G isoforms have been detected in the serum of pregnant and nonpregnant women as well as men. The rhesus monkey placenta expresses a novel nonclassical MHC class I molecule Mamu-AG, which has features remarkably similar to those of HLA-G. We determined that the rhesus placenta expresses Mamu-AG mRNA ( Mamu-AG5 ), retaining intron 4 as previously noted in HLA-G5 . Immunostaining experiments with Ab 16G1 against the soluble HLA-G5 intron 4 peptide demonstrated that an immunoreactive protein(s) was present in the syncytiotrophoblasts of the chorionic villi of the rhesus placenta, within villous cytotrophoblasts, and occasionally within cells of the villous stroma. The Mamu-AG5 mRNA was readily detected in rhesus testis (although not in ejaculated sperm). Whereas an Ab against membrane-bound Mamu-AG stained few cells, primarily in the interstitium of the testis, there was consistent immunostaining for Mamu-AG5 in cells within the seminiferous tubules, which was corroborated by localization of Mamu-AG mRNA by in situ hybridization. While primary spermatocytes were negative, Sertoli cells, spermatocytes, and spermatids were consistently positive for 16G1 immunostaining. The speciﬁc recognition of the soluble Mamu-AG isoform was conﬁrmed by Western blotting of Mamu-AG5 expressed in heterologous cells. The results demonstrate that a soluble nonclassical MHC class I molecule is expressed in the rhesus monkey placenta and testis, and conﬁrm
A Novel Biological Dosimetry Method for Monitoring Occupational Radiation Exposure in Diagnostic and Therapeutic Wards: From Radiation Dosimetry to Biological Effects

Background and Objective Professional radiation workers are occupationally exposed to long-term low levels of ionizing radiation. Occupational health hazards from radiation exposure, in a large occupational segment of the population, are of special concern. Biological dosimetry can be performed in addition to physical dosimetry with the aim of individual dose assessment and biological effects. Methods In this biodosimetry study, some hematological parameters have been examined in 40 exposed and 40 control subjects who were matched by gender, age and occupational records (±3 years) in Kermanshah hospitals in Iran (2013-2014). The occupational radiation dose was measured by personal dosimetry device (film badges). The data was analyzed using SPSS V.20 and statistical tests such as two-sided Student’s t-test. Results Exposed subjects had a median exposure of 0.68±1.58 mSv/year by film badge dosimetry. Radiation workers with at least a 10-year record showed lower values of Mean Hemoglobin (Hb) and Mean Corpuscular Volume (MCV) compared to the control group (p<0.05). The mean value of Red Blood Cells (RBCs) in personnel working in Radiology departments seemed to show decrease in comparison with other radiation workers. Conclusion Although the radiation absorbed doses were below the permissible limits based on the ICRP, this study showed the role of low-level chronic exposure in decreasing Hb and MCV in the blood of radiation workers with at least 10 years records. Therefore, the findings from the present study suggest that monitoring of hematological parameters of radiation workers can be useful as biological dosimeter, and also the exposed medical personnel should carefully follow the radiation protection instructions and radiation exposure should be minimized as possible.
Estimating flow distributions from sampled flow statistics

Passive traffic measurement increasingly employs sampling at the packet level. Many high-end routers form flow statistics from a sampled substream of packets. Sampling controls the consumption of resources by the measurement operations. However, knowledge of the statistics of flows in the unsampled stream remains useful, for understanding both characteristics of source traffic, and consumption of resources in the network. This paper provides methods that use flow statistics formed from sampled packet stream to infer the frequencies of the number of packets per flow in the unsampled stream. A key task is to infer the properties of flows of original traffic that evaded sampling altogether. We achieve this through statistical inference, and by exploiting protocol level detail reported in flow records. We investigate the impact on our results of different versions of packet sampling.
Household availability of ultra-processed foods and obesity in nineteen European countries

Abstract Objective To assess household availability of NOVA food groups in nineteen European countries and to analyse the association between availability of ultra-processed foods and prevalence of obesity. Design Ecological, cross-sectional study. Setting Europe. Subjects Estimates of ultra-processed foods calculated from national household budget surveys conducted between 1991 and 2008. Estimates of obesity prevalence obtained from national surveys undertaken near the budget survey time. Results Across the nineteen countries, median average household availability amounted to 33·9 % of total purchased dietary energy for unprocessed or minimally processed foods, 20·3 % for processed culinary ingredients, 19·6 % for processed foods and 26·4 % for ultra-processed foods. The average household availability of ultra-processed foods ranged from 10·2 % in Portugal and 13·4 % in Italy to 46·2 % in Germany and 50·4 % in the UK. A significant positive association was found between national household availability of ultra-processed foods and national prevalence of obesity among adults. After adjustment for national income, prevalence of physical inactivity, prevalence of smoking, measured or self-reported prevalence of obesity, and time lag between estimates on household food availability and obesity, each percentage point increase in the household availability of ultra-processed foods resulted in an increase of 0·25 percentage points in obesity prevalence. Conclusions The study contributes to a growing literature showing that the consumption of ultra-processed foods is associated with an increased risk of diet-related non-communicable diseases. Its findings reinforce the need for public policies and actions that promote consumption of unprocessed or minimally processed foods and make ultra-processed foods less available and affordable.
The Effectiveness of an Interactive Instructional Context: Principles from the Parent-Child Interaction Literature

In the present study, the effectiveness of embedding a targeted linguistic structure within an interactive instructional context is examined. Ten subjects participated in a communication-games intervention which contained seven interactive elements drawn from the parent-child interaction literature. Ten subjects were assigned to a control group. A comparison of student performance before and after intervention supports the effectiveness of adopting instructional strategies that are consistent with a social-interaction perspective on language development. Qualitative results are presented that illustrate each of the interactional characteristics of the intervention. Implications for practice are discussed.
DS-EPL: domain-specific event processing language

Intelligent real-time applications have been successfully developed in several distinct application domains by using different kinds of EPLs. All EPLs available so far are independent of the problem domain and do provide rather low-level language constructs for event pattern specification. In this paper, we propose the utilization of Domain-specific Languages (DSL) for CEP in order to develop domain-specific event processing languages (DS-EPL). The DS-EPL approach will enable the developer to write event processing code on a higher level of abstraction, based on selfdefined domain-specific language constructs. Thus, an EPL can be specifically tailored to a particular problem domain. We present a domain-specific event processing language for the machine-to-machine (M2M) domain as a representative example and report some results of practical experiences.
Detecting coevolving amino acid sites using Bayesian mutational mapping

MOTIVATION The evolution of protein sequences is constrained by complex interactions between amino acid residues. Because harmful substitutions may be compensated for by other substitutions at neighboring sites, residues can coevolve. We describe a Bayesian phylogenetic approach to the detection of coevolving residues in protein families. This method, Bayesian mutational mapping (BMM), assigns mutations to the branches of the evolutionary tree stochastically, and then test statistics are calculated to determine whether a coevolutionary signal exists in the mapping. Posterior predictive P-values provide an estimate of significance, and specificity is maintained by integrating over uncertainty in the estimation of the tree topology, branch lengths and substitution rates. A coevolutionary Markov model for codon substitution is also described, and this model is used as the basis of several test statistics. RESULTS Results on simulated coevolutionary data indicate that the BMM method can successfully detect nearly all coevolving sites when the model has been correctly specified, and that non-parametric statistics such as mutual information are generally less powerful than parametric statistics. On a dataset of eukaryotic proteins from the phosphoglycerate kinase (PGK) family, interdomain site contacts yield a significantly greater coevolutionary signal than interdomain non-contacts, an indication that the method provides information about interacting sites. Failure to account for the heterogeneity in rates across sites in PGK resulted in a less discriminating test, yielding a marked increase in the number of reported positives at both contact and non-contact sites. SUPPLEMENTARY INFORMATION http://www.dimmic. net/supplement/
Phase dynamics at microtubule ends: the coexistence of microtubule length changes and treadmilling

The length dynamics both of microtubule-associated protein (MAP)-rich and MAP-depleted bovine brain microtubules were examined at polymer mass steady state. In both preparations, the microtubules exhibited length redistributions shortly after polymer mass steady state was attained. With time, however, both populations relaxed to a state in which no further changes in length distributions could be detected. Shearing the microtubules or diluting the microtubule suspensions transiently increased the extent to which microtubule length redistributions occurred, but again the microtubules relaxed to a state in which changes in the polymer length distributions were not detected. Under steady-state conditions of constant polymer mass and stable microtubule length distribution, both MAP-rich and MAP-depleted microtubules exhibited behavior consistent with treadmilling. MAPs strongly suppressed the magnitude of length redistributions and the steady-state treadmilling rates. These data indicate that the inherent tendency of microtubules in vitro is to relax to a steady state in which net changes in the microtubule length distributions are zero. If the basis of the observed length redistributions is the spontaneous loss and regain of GTP-tubulin ("GTP caps") at microtubule ends, then in order to account for stable length distributions the microtubule ends must reside in the capped state far longer than in the uncapped state, and uncapped microtubule ends must be rapidly recapped. The data suggest that microtubules in cells may have an inherent tendency to remain in the polymerized state, and that microtubule disassembly must be induced actively.
Uncertainty and Consumer Durables Adjustment

We study infrequent durables stock adjustment by consumers who also derive utility from non-durable consumption flows, in the presence of idiosyncratic income uncertainty. We first characterize how the extent of uncertainty bears theoretically on the cross-sectional distribution of the durable/non durable ratio, the probability of costly adjustment, and the size of adjustment. Then, we bring such predictions to bear on a data set with extensive information on disaggregated durable goods and subjective measures of future income uncertainty. The data feature two conceptually distinct sources of variation: cross-sectional heterogeneity of the sampled households' dynamic problems, and history-dependent heterogeneity in their situation at the beginning of the observation period. We note that the latter should affect the likelihood but not the size of stock adjustment decisions, and find broad support for theoretical predictions in formal selection-controlled regressions based on this insight.
Drug Overdose Surveillance Using Hospital Discharge Data

Objectives. We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. Methods. We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000–2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Results. Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. Conclusion. The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison.
Some Improvements on Deep Convolutional Neural Network Based Image Classification

Abstract: We investigate multiple techniques to improve upon the current state of the art deep convolutional neural network based image classification pipeline. The techiques include adding more image transformations to training data, adding more transformations to generate additional predictions at test time and using complementary models applied to higher resolution images. This paper summarizes our entry in the Imagenet Large Scale Visual Recognition Challenge 2013. Our system achieved a top 5 classification error rate of 13.55% using no external data which is over a 20% relative improvement on the previous year's winner.
Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions

We consider the situation when there is a large number of series, N, each with T observations, and each series has some predictive ability for some variable of interest. A methodology of growing interest is first to estimate common factors from the panel of data by the method of principal components and then to augment an otherwise standard regression with the estimated factors. In this paper, we show that the least squares estimates obtained from these factor-augmented regressions are root-T consistent and asymptotically normal if root(T)/N -> 0. The conditional mean predicted by the estimated factors is min(root(T),root(N)) consistent and asymptotically normal. Except when T/N goes to zero, inference should take into account the effect of "estimated regressors" on the estimated conditional mean. We present analytical formulas for prediction intervals that are valid regardless of the magnitude of N/T and that can also be used when the factors are nonstationary. Copyright The Econometric Society 2006.
The Relationship Between Quality of Work Life and Job Satisfaction of Faculty Members in Zahedan University of Medical Sciences

Background: Quality of work life is one of the most important factors for human motivating and improving of job satisfaction. Aim: The current study was carried out aimed to determine the relationship between quality of work life and job satisfaction in faculty members of Zahedan University of Medical Sciences. Method: In this descriptive-analytic study, 202 faculty members of Zahedan University of Medical Sciences in 2012 were entered the study through census. The job satisfaction questionnaire of Smith and Kendall and Walton Quality of Work Life questionnaire were used for data collection. Validity and reliability of questionnaires were confirmed in previous studies. Data analysis was done using SPSS 18. The Pearson correlation coefficient and multiple regression tests were used for data analysis. Result: The mean score of quality of work life was 121/30±37/08 and job satisfaction was 135/98±33/78. There was a significant and positive correlation between job satisfaction of faculty members and their quality of work life (P=0.003). In addition, two components of quality of work life “adequate and fair compensation” (β=0.3) and “Social Integration” (β=0.4) can predict job satisfaction of faculty members. Conclusion: According to correlation between job satisfaction and quality of work life in faculty members, job satisfaction can be improved through the changing and manipulating the components of quality of work life and in this way; the suitable environment for organization development should be provided.
Recursive Nonparametric Identification of Nonlinear Systems With Adaptive Binary Sensors

In this paper, the problem of identifying nonlinear systems under adaptive binary-valued output measurements is considered. We follow a nonparametric approach, which directly estimates the value of the nonlinear function representing the system at any fixed point with the help of a recursive kernel-based stochastic approximation algorithm with expanding truncations (SAAWET). The thresholds of the binary sensor are adaptively designed to achieve a sufficient richness of information in the output observations. The constructed estimates are proved to converge to the true values with probability one. Two numerical examples are given showing that the simulation results are consistent with the theoretical analysis.
Delay-Independent Stability and Performance of Distributed Congestion Control

Recent research efforts to design better Internet transport protocols combined with scalable active queue management (AQM) have led to significant advances in congestion control. One of the hottest topics in this area is the design of discrete congestion control algorithms that are asymptotically stable under heterogeneous feedback delay and whose control equations do not explicitly depend on the RTTs of end-flows. In this paper, we first prove that single-link congestion control methods with a stable radial Jacobian remain stable under arbitrary feedback delay (including heterogeneous directional delays) and that the stability condition of such methods does not involve any of the delays. We then extend this result to generic networks with fixed consistent bottleneck assignments and max-min network feedback. To demonstrate the practicality of the obtained result, we change the original controller in Kelly's work [ldquoRate Control for communication networks: Shadow prices, proportional fairness and stability,rdquo Journal of the Operational Research Society, vol. 49, no. 3, pp. 237-252, March 1998] to become robust under random feedback delay and fixed constants of the control equation. We call the resulting framework max-min Kelly control (MKC) and show that it offers smooth sending rate, exponential convergence to efficiency, and fast convergence to fairness, all of which make it appealing for future high-speed networks.