Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the accuracy of SNAP technology sleep sonography in detecting obstructive sleep apnea in adults compared to standard polysomnography.

OBJECTIVE To determine the accuracy of snoring and apnea analysis by SNAP (SNAP Laboratories; Glenview, IL), a technology that uses snoring recorded by a home microphone system and nasal airflow, to diagnose obstructive sleep apnea (OSA) as well as determine its severity. METHODS For all patients who had undergone a prior SNAP study and were referred to the Sleep Disorders Center of Lifespan Hospitals for polysomnography testing from January 2000 through December 2001, we compared the results of the SNAP study to standard polysomnography (polysomnography). The severity of each apnea-hypopnea index (AHI) [mild, moderate, or severe, as defined by the AHI Severity Task Force of the American Academy of Sleep Medicine] recorded by SNAP was compared to that of the polysomnography result. All polysomnography tests were scored independently and without the prior knowledge of any SNAP results. RESULTS For the 31 patients on whom data were available, the mean age, body mass index, and Epworth sleepiness scale scores were 50.3 years (range, 29 to 77 years), 31.6 kg/m(2) (range, 24 to 44 kg/m(2)), and 11.3 (range, 1 to 20), respectively. The mean follow-up time between the two studies was 5 months. The severity criteria indicated by the SNAP study accurately assessed the true severity confirmed by polysomnography in only 11 of 31 patients (35.5%). When the AHI severity score from the SNAP study was compared to polysomnography using a kappa statistic measure of agreement, there was overall agreement with a kappa value of 0.23 (p = 0.008), but the agreement was only fair. SNAP study severity scores were overestimated in 13 of 31 patients (41.9%) compared to the polysomnography results. In the majority of these subjects (8 of the 13 "overestimated" patients or 8 of 31 total patients [25.8%]), the SNAP study diagnosed OSA when the patient had a normal polysomnography finding. CONCLUSION Although there may be some night-to-night variability in polysomnography testing, these results suggest that SNAP studies do not appear to accurately assess the severity of OSA.
IMPACT OF HEALTH INSURANCE ON LAND-RELATED INVESTMENTS IN AFRICA : EVIDENCE FROM GHANA 1

It has been observed that health shocks decreases the productivity and potential investments into agriculture, and as such further perpetuates poverty among smallholder farmers. It is argued that, health insurance coverage for smallholder farmers can go a long way to ameliorate the impact of heath shocks and smoothen agricultural investments. However, very little is known about the impact that health insurance coverage has on smallholder farmers’ land-related investment. Thus, this study using enrolment information on the Ghana National Health Insurance Scheme (NHIS) examines the determinants of health insurance coverage amongst smallholder farmers and goes further to examine the impact of coverage on agricultural investments in the form of the level of agricultural inputs used in production and also the level of hired labour employed. The study employed a number of estimation approaches to address issues relating to endogeneity – the fact that NHIS coverage is nonrandom or in other words NHIS is not randomly assigned. To address this issue and estimate causal impact of NHIS, propensity score matching (PSM) estimations and two-stage stage residual inclusion model were estimated to augment the Ordinary Least Squares (OLS) estimator. The result shows that, household head characteristics such as gender, age and educational level, as well as farm size and household expenditure influences the enrollment in NHIS amongst smallholder farmers. In term of impact, estimates from propensity score matching and the two-stage residual inclusion reveals a positive and significant effect of NHIS on agricultural input used and improved hired labour use on smallholder farms.
Occurrence of Multidrug resistant (MDR) Campylobacter species isolated from retail Chicken meats in Selangor, Malaysia and their associated risk factors

Aims: Campylobacter infection is one of the leading bacterial food-borne illness and most frequently reported in humans in developed countries. This study was designed to determine the prevalence of multidrug resistant (MDR) Campylobacter and the risk factors associated with their occurrence in broiler chicken meat retailed in markets. Methodology and results: A total of 210 samples consisting of 140 chicken meat and 70 swabs from weighing scales and cutting boards were collected. Isolates were cultured by passive filtration method, identified by biochemical tests and confirmed using PCR assay. Thirty-two (32/210) 15.2% were positive for Campylobacter of which (25/210) 11.9%, (6/210) 2.9% and (1/210) 0.5% were Campylobacter jejuni, C. coli and C. upsaliensis respectively. The isolates showed high resistance to ampicillin (62.5%), enrofloxacin (56.3%) and nalidixic acid (50.0%), while only 3.1% were resistant to streptomycin. Multidrug resistant isolates (resistance to at least one antibiotics in three classes or more) was high at 71.9%. The risk factors significantly (p<0.05) associated with Campylobacter contamination on chicken’s meat included poor workers hygiene {OR: 5.250 (95% CI: 0.988-27.895)}, wearing improper work attire {OR: 2.700 (95% CI: 1.1446.374)}, poor protective equipment {OR 38.50 (95% CI: 2.915-508.463)}, poor environment/stall hygiene {OR 44.00 (95% CI: 2.193-882.66)}, and using tiled counter top surface {OR 6.667 (95% CI: 0.597-74.506). Conclusion, significance and impact of study: The finding of this study affirmed that lack or poor work hygiene, unclean environmental stall and protective equipment are associated with high occurrence of multidrug resistant Campylobacter species isolated from chicken meat
Homozygous parent affected sib pair method for detecting disease predisposing variants: Application to insulin dependent diabetes mellitus

For complex genetic diseases involving incomplete penetrance, genetic heterogeneity, and multiple disease genes, it is often difficult to determine the molecular variant (s) responsible for the disease pathogenesis. Linkage and association studies may help identify genetic regions and molecular variants suspected of being directly responsible for disease predisposition or protection, but, especially for complex diseases, they are less useful for determining when a predisposing molecular variant has been identified. In this paper, we expand upon the simple concept that if a genetic factor predisposing to disease has been fully identified, then a parent homozygous for this factor should transmit either of his/her copies at random to any affected children. Closely linked markers are used to determine identity by descent values in affected sib pairs from a parent homozygous for a putative disease predisposing factor. The expected deviation of haplotype sharing from 50%, when not all haplotypes carrying this factor are in fact equally predisposing, has been algebraically determined for a single locus general disease model. Equations to determine expected sharing for multiple disease alleles or multiple disease locus models have been formulated. The recessive case is in practice limiting and therefore can be used to estimate the maximum proportion of putative susceptibility haplotypes which are in fact predisposing to disease when the mode of inheritance of a disease is unknown. This method has been applied to 27 DR3/DR3 parents and 50 DR4/DR4 parents who have at least 2 children affected with insulin dependent diabetes mellitus (IDDM). The transmission of both DR3 and DR4 haplotypes is statistically different from 50% (P < 0.05 and P < 0.001, respectively). An upper estimate for the proportion of DR3 haplotypes associated with a high IDDM susceptibility is 49%, and for DR4 haplotypes 38%. Our results show that the joint presence of non‐Asp at DQP position 57 and Arg at DQa position 52, which has been proposed as a strong IDDM predisposing factor, is insufficient to explain the HLA component of IDDM predisposition. © 1993 Wiley‐Liss, Inc.
Development of the Simulator for Carrying a Lifted Load in Large Plant Construction

Large plant construction has numerous works, and the proportion of hoisting operations in the total construction work is high. In the hoisting operations, many things should be considered to keep the operations safe, and the work steps of the hoisting operations are planned by considering them. However, it is difficult for novice construction workers to understand the work steps with conventional two-dimensional drawings. Thus, to have those workers understand it well, we developed the hoisting-operation simulator considering the physical behavior of a load in conjunction with 3D viewer and physics engine. The simulator can visualize the work steps as three-dimensional animation. Moreover, by associating the simulator with mixed reality technology, we developed the system superimposing the 3D animation on reality space via head mount display. Experiments verify that the 3D animation of a load moves with the vibration due to the inertial force and that the 3D animation generated by the simulator is superimposed in the work site.
Robust Simultaneous Inference for Functional Data by Italo

Advancements in modern technology have enabled the collection of complex, high-dimensional data sets, such as curves, 2D or 3D images, and other objects living in a functional space, thus boosting the investigation of function data. This phenomenon affects all the fields involving applied statistics such as Geophysics (Ferraty et al., 2005), Environmetrics (Febrero et al., 2008), Ecology (Embling et al., 2012), Chemometrics (Daszykowski et al., 2007), and others, see also Ferraty and Vieu (2006). Not only revealing the wide variety of possible fields of application of functional data methods, the previous selected set of references also reflect the large scope of statistical problems, such as regression and inference, in which one may have to deal with under the context of functional data. Hence, functional data analysis (FDA) has become one of the most active fields of research in statistics during the last ten years. In this dissertation our objective is to develop outlying-resistant methods for the estimation of the mean curve of a functional dataset that remain valid even in the presence of a significant proportion of outlier curves. We also propose a method for the calculation of a simultaneous confidence band for the mean curve that is robust to outliers. Our work is based on B-Spline Smoothing, together with LADbased and M-based estimation techniques. We also extend both methods for the estimation of the difference of the mean functions of two populations, also obtaining a robust test statistics for the difference of the mean functions of two populations. We analyze the asymptotic properties of the proposed estimators, proving weak consistency and, for the M-based estimator, asymptotic normality. We implement an
DESIGN AND ANALYSIS OF A CLASS OF WEIGHTED-NEWTON METHODS WITH FROZEN DERIVATIVE

We present a generalized k-step scheme of weighted-Newton methods with increasing convergence order 2k+2 for nonlinear equations. The novelty of the scheme is that in each step the order of convergence is increased by an amount of two at the cost of only one additional function evaluation. The algorithm requires only single evaluation of Fréchet derivative which points to the name ‘methods with frozen derivative’. Local convergence including radius of convergence, error bounds and estimates on the uniqueness of the solution is presented. To maximize the computational efficiency, the optimal number of steps is computed. Theoretical results regarding convergence and computational efficiency are verified through numerical experimentation.
Correlation of Sensorimotor Activation with Functional Magnetic Resonance Imaging and Magnetoencephalography in Presurgical Functional Imaging: A Spatial Analysis

In this study we investigated the spatial heterotopy of MEG and fMRI localizations after sensory and motor stimulation tasks. Both methods are frequently used to study the topology of the primary and secondary motor cortex, as well as a tool for presurgical brain mapping. fMRI was performed with a 1.5T MR system, using echo-planar imaging with a motor and a sensory task. Somatosensory and motor evoked fields were recorded with a biomagnetometer. fMRI activation was determined with a cross-correlation analysis. MEG source localization was performed with a single equivalent current dipole model and a current density localization approach. Distances between MEG and fMRI activation sites were measured within the same anatomical 3-D-MR image set. The central region could be identified by MEG and fMRI in 33 of 34 cases. However, MEG and fMRI localization results showed significantly different activation sites for the motor and sensory task with a distance of 10 and 15 mm, respectively. This reflects the different neurophysiological mechanisms: direct neuronal current flow (MEG) and secondary changes in cerebral blood flow and oxygenation level of activated versus non activated brain structures (fMRI). The result of our study has clinical implications when MEG and fMRI localizations are used for pre- and intraoperative brain mapping. Although both modalities are useful for the estimation of the motor cortex, a single modality may err in the exact topographical labeling of the motor cortex. In some unclear cases a combination of both methods should be used in order to avoid neurological deficits.
Adaptive Control of Visual Effects for Frame Rate Maintenance in Real Time Ray Tracing

This paper presents strategies to control frame rate performance for a Real Time Ray Tracing engine based on OptiX framework by dynamically altering and adjusting visual effects based upon information directly collected from the scene. Performance studies were done to investigate the impact of the number of lights and the use of reflexive or translucent materials in order to validate the concept.
The allocation of resources within polygamous households : Evidence from Nigeria

Using household survey data from Nigeria we analyse the variation in labour supply across biological children within the polygamous household. In contrast with previous evidence, we find that children of the first wife work about three to five hours more per week and are less likely to attend school than children of other mothers. To rationalize our findings, we develop a theoretical framework which investigates the amount of education a child receives versus the time spent in domestic production in polygamous households. We show that if child labour acts as a means of mothers to increase the share of resources allocated to their own offsprings, the effect of the mothers’ rank on child labour supply is ambiguous. Linking our data to ethnographic information, we find suggestive evidence that our results are driven by those children who are more likely to inherit the land of their father in the long run. JEL Classification: D19; J22; O12
Data Imbalance and Classifiers : Impact and Solutions from a Big Data Perspective

Data being generated in real-time environment is prone to inconsistencies like data imbalance and messy data with noise. Hugeness of the data also poses an additional complexity to the prediction mechanisms. Data imbalance is an intrinsic part of the real-time data and hence cannot be overlooked. Experiments reveals that data imbalance and data hugeness do affect the predictors. However, each predictor model exhibits its own advantages, which can be observed in terms of their performance metrics. However, a single predictor with overall high performance is absent. Hence it was concluded that a combination of prediction algorithms would be best suitable for such data. In order to identify the appropriate set of algorithms, a performance analysis was carried out on several standard algorithms. An analysis on ensemble techniques was also carried out to identify the best combiner technique, and boosting and stacking ensembles were shortlisted as they exhibited promising models.
Effect of Nutritional Guideline for Kindergarten Teachers on Healthy Physical Growth of Preschool Children

Background: Early childhood is a critical time for the development of food preferences and eating patterns. Preschool is the perfect setting to educate children on the principles of good nutrition. The nutritional knowledge and awareness of preschool teachers are one of the most important factors affecting preschool children's nutritional habit. So The aim was: To study the effect of nutritional guideline for kindergarten teachers on healthy physical growth of preschool children. Design: Using cross sectional study, quasi-experimental design, one group study. Setting: Study was conducted in Shebin El-kom City Menofia Egypt at Private and Governmental kindergarten Sample: A convenience sample include 15 kindergarten teachers and 240 children aged 3-6 years. Tools: Three tools were used for teachers' knowledge related to healthy nutrition ,the second tool was a nutritional rating scale designed by Baker and Khalder (2007) for the teachers' nutritional practice and third tool was a questionnaire sheet for preschool children developed and validate by researcher . Results: As regards to sample Sociodemographic characteristics (60% and 75%) of kindergarten teachers were aged from 20 to less than 30 years the majority (60% and100%) of them has a bachelor degree of education in private and governmental kindergarten respectively also most (75% and 80% ) of them were married. The majority(94%) of children aged from 4-5 years, the number of girls exceed than boys. It was revealed that highly statistical significant improvements in teachers' knowledge and practice post educational nutritional guideline at (P<0.05) in each private and governmental kindergarten. There was a correlation and a highly statistically significant difference between teachers' nutritional knowledge , practice and physical growth of preschool children at p value <0.05 . Conclusion: It was concluded that nutritional guideline improve kindergarten teachers' knowledge and practices where it was positively affect on physical growth of the preschool child as it was prevent childhood malnutrition and promote healthy physical growth. So it was Recommended that: Provide nutritional training for the teachers about healthy nutrition for the preschool children and integrate nutritional courses for the preschool curriculum in the kindergarten to learning good food habits and practices include preventing buy any candy foods like gas drinks or chips in the Kindergarten.
36 Agent-based Bidding in Electronic Markets A Prototypical Approach

The overall change in computing from manipulation to delegation was already predicted in the mid-90s but hitherto remains a bold vision. Although software agents have the potential of fully automating processes, real world agent-based applications are very limited in number. Even in the case of electronic markets software agents are rarely employed, albeit they can act as autonomous representatives of human negotiators. The prototypical approach presented in this paper seizes the idea of an agentbased electronic marketplace and describes multilateral negotiations as a core of an electronic trading system. Owing to their open format (i.e. open bidding), agent-based multilateral negotiations are expected to reduce transaction costs and to improve the negotiation outcome. The multilateral negotiations are presented in two different environments: in AMTRAS, an agent-based marketplace for bonds, as well as in VTR, a web-based trading system for stocks. Two key features of these negotiations are the revelation of all bids, and the anonymous nature of trading. The information released in the negotiation constitutes the basis for further research such that the agents are capable of deploying own strategies inferred from the other's bidding behavior. The paper concludes with some recommendations as to how automation of the bidding process can be achieved using software agents'
Analysis of a complex trait with missing data on the component traits

Many complex agronomic traits are computed as the product of component traits. For the complex trait to be assessed in a field plot, each of the component traits needs to be measured in the same plot. When data on one or several component traits are missing, the complex trait cannot be computed. If the analysis is to be performed on data for the complex trait, plots with missing data on at least one of the component traits are discarded, even though data may be available on some of the component traits. This paper considers a multivariate mixed model approach that allows making use of all available data. The key idea is to employ a logarithmic transformation of the data in order to convert a product into a sum of the component traits. The approach is illustrated using a series of sunflower breeding trials. It is demonstrated that the multivariate approach allows making use of all available information in the case of missing data, including plots that may have data only on one of the component traits.
Characterization of neutralizing monoclonal antibodies directed against tetanus toxin fragment C

Abstract Clostridium tetani causes a life-threatening infectious disease by production of tetanus neurotoxin (TeNT), a 150 kDa molecule composed of light (LC) and heavy chain (HC) polypeptides. The TeNT HC contains an N-terminal domain critical for LC translocation and a C-terminal toxin receptor-binding domain known as fragment C. Despite extensive investigations on epitope specificity of anti-TeNT antibodies, the immunodominant neutralizing epitopes of the toxin are poorly defined. This study describes the generation and characterization of four monoclonal antibodies (MAb) specific for TeNT. The characteristics of each MAb were explored in terms of isotype, specificity, affinity, and immuno-globulin heavy chain variable region (IGHV) gene usage using ELISA, Western blotting, and sequencing techniques. The toxin neutralizing activity of the MAbs was also investigated using the in vitro GT1b neutralizing assay. The data demonstrated that all MAbs bind to tetanus toxin and toxoid. Sub-fragments binding analysis showed that two MAbs react with fragment C, one with both fragment C and LC, and one with LC. Only the two fragment C-specific MAbs were able to neutralize the toxin. Sequencing of the expressed VH and VL genes revealed rearrangements of various VH and VL gene segments in all hybridoma clones. Clonality of the hybridomas was also confirmed by a competition assay that showed recognition of distinct epitopes by these MAbs. The results suggest the importance of TeNT fragment C in terms of immunogenicity and toxin neutralization activity.
Influence of Water Stress and Rhizobial Inoculation on Relative Leaf Water content and Electrolyte Leakage in Selected Common Bean cultivars ( Phaseolus vulgaris L . )

s: Two seasons’ field and one season screen house experiments were conducted to assess the effect of water stress periods and rhizobial inoculation in five P. vulgaris cultivars on relative water content and electrolyte leakage. The experiment consisted of 2 levels of rhizobia (with and without inoculation), two stress levels (with and without water stress) and five cultivars of P. vulgaris (KAT B9, KAT B1, F9 Kidney Selection, F8 Drought line and JESCA). Rhizobial inoculated treatments and unstressed water treatments increased relative leaf water content and electrolyte leakage in field and screen house experiment. Cultivars F9 Kidney Selection, F8 Drought Line and variety JESCA significantly increased relative water content as compared with the other tested cultivars. However, varieties KAT B9 and KAT B1 significantly increased electrolyte leakage as compared with the other studied cultivars. Significant interactions were also observed between inoculation x water stress periods and the tested P vulgaris cultivars. Key words; Moisture, Inoculants, Varieties, ions