Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Periconceptual Omega-3-Fatty Acid Supplementation on in Vitro Fertilization Success and Miscarriage Rates in Patients of a German Fertility Centre

Long-chain omega-3 fatty acids have been positively related with improvement of fertility in both women and men. Primary natural source of omega-3- fatty acids is seafood. As this also can bei the source of toxicants like f.e. lead, mercury and cadmium, reproductive benefits may be counteracted. Therefore, our approach was to supplement pharmaceutical grade omega-3-fatty acids in order to assess potential benefits of omega-3-fatty acids on modulation of IVF-success by dietary measures in a well-defined group of patients of a German Fertility Centre. A group of 52 IVF-patients with a history of at least two miscarriages or unsuccessful in vitro fertilization approaches received periconceptual omega-3-fatty acid supplementation for a time period of at least 3 weeks. The “historical” control group, consisting of 1109 patients without omega-3-fatty acid supplementation, was generated out of the Fertility Centre´s patient database. The same inclusion criteria (history of at least two miscarriages or unsuccessful in vitro fertilization approaches) were applied for both groups. Omega-3-fatty acid supplementation lead to significantly enhanced in vitro fertilization success rates as well as to reduction of miscarriage rates compared to patients of the control group. The results encourage to design further age-matched, double-blinded prospective studies in order to verify a positive influence of dietary intervention and lifestyle modification on fertility rates.
Developing teachers’ responsive pedagogy in mathematics, does it lead to short-term effects on student learning?

Abstract In this study, we examine the short-term effects of an intervention aimed at developing teachers’ responsive pedagogy in mathematics. The study analyses how an emphasis on responsive pedagogy in 9th grade classrooms over a period of seven months might strengthen students’ feedback, self-regulated learning, self-efficacy and achievement in mathematics. Nine schools attended as intervention group (N = 40 classes; 1003 students). 11 compatible schools (N = 37 classes; 896 students) were recruited as a control group. Students responded to a pre-post questionnaire and conducted a pre-post achievement test. Results show small, significant differences between the total scores for the pre- and post-measures in the intervention group for the variables elaboration, task value motivation, effort and persistence, self-efficacy and self-conception. Significant differences between the treatment and control group is found for the achievement emotions anxiety and enjoyment. No significant difference is found for achievement in mathematics.
Transformation-mediated twinning

Twinning plays a critical role in plasticity and strengthening of metals and alloys. In face-centered cubic materials, mechanical twinning is considered to be realized by the movement of twinning partial dislocations on consecutive close-packed atomic planes. Here, we report an unrivaled twinning mechanism which is accomplished through a preceding austenite to hexagonal martensite phase transformation. This transformation-mediated twinning operates predominantly in metastable face-centered cubic materials with small to intermediate negative stacking fault energy. It provides a continuous avenue for strain accommodation and strain hardening, realizing the joint transformation-induced plasticity and twinning-induced plasticity in the same system, and thus enabling the simultaneous improvement of strength and ductility. The disclosed plastic deformation mechanism explains the behavior of a large number of known alloys and greatly expands the composition territory for designing novel alloys with outstanding mechanical properties.
Aspects of convergence of random walks on finite volume homogeneous spaces

The purpose of this note is to discuss three aspects of weak* convergence of the $n$-step distributions of random walks on finite volume homogeneous spaces $G/\Gamma$ of semisimple real Lie groups. First, we investigate the obvious obstruction to the upgrade from Cesaro to non-averaged convergence: periodicity. We give examples where it occurs and conditions under which it does not. In a second part, we prove convergence towards Haar measure with exponential speed from almost every starting point. Finally, we establish strong uniformity for the Cesaro convergence towards Haar measure for uniquely ergodic random walks.
Planetary boundary layer height by means of lidar and numerical simulationsBoundary Layer variability over New Delhi, India, during EUCAARI project

In this work, the Ground-based lidar measurements were performed at Gual Pahari measurement station, approximately 20 km South of New Delhi, India, from March 2008 to March 2009. The height of the Planetary Boundary Layer (PBLH) is investigated over Gual Pahari, New Delhi, for almost a year. To this end, ground-based measurements from a multi-wavelengthPBL) was retrieved with a portable Raman lidar, were used. The system, utilizing the modified Wavelet 15 Covariance Transform (WCT) method was utilized for PBLH retrievals. Results. The lidar derived PBL heights were compared to radiosonde data from, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite observations and the Weather Research and Forecasting (WRF) model. In order totwo atmospheric models. The results were also analyzed on a seasonal basis. To examine the difficulties of PBLHPBL lidar detection from lidar, we analyzed three cases of PBLH 20 diurnal evolution under different meteorological and aerosol load conditions. we focused on three case studies of PBL diurnal evolution. In the presence of a multiple aerosol layerslayer structure, the employed algorithmWCT method exhibited high efficiency (r=0.9) in the attribution of PBLH, whereas weak aerosol gradients induced high variability in PBLH. A sensitivity analysis corroborated the stability of the utilized methodology. The PBL height determination. Good agreement with the 25 European Center for Medium-range Weather Forecasts (ECMWF) and the Weather Research and Forecasting (WRF) estimations was found (r=0.69 and r=0.74, respectively) for a cumulus convection case. In the aforementioned cases, temperature, relative humidity and potential temperature radiosonde profiles were well compared to the respective WRF profiles. The Bulk Richardson Number scheme, which was applied to radiosonde profile data, was in good agreement with lidar data, especially during 30 daytime (r=0.68). The overall comparison with CALIPSO satellite observations yielded; namely, CALIOP Level 2 Aerosol Layer Product, was very satisfying results (r=0.884), with CALIPSO Feature Detection Algorithms slightly overestimating PBLH. Due to the relatively warmer and drier winter and, correspondingly, colder and rainier pre-monsoon season,PBL height. Lidar measurements revealed that the maximum PBL height was reached approximately three hours after the seasonal PBLHsolar noon, 35 whilst the daily evolution of the PBL was completed, on average, one hour earlier. The PBL diurnal cycle during the measurement was also analyzed using ECMWF estimations, which produced a stronger cycle during the winter and pre-monsoon period was slightly weaker. The seasonal analysis of Formatted Formatted: English (United States) Formatted: English (United States)
Diversity of endophytic fungal community associated to the roots of Argania spinosa (L.) Skeels growing in the arid and semi-arid regions of Algeria

Current study identified endophytic fungi associated to Argania spinosa (argan) roots and revealed diverse haplotype diversity by the sequencing of internal transcribed spacer (ITS). 586 operational taxonomic units were identified and these operational taxonomic units (OTUs) could be assigned to fungal functional diversity such as endophytes, ectomycorrhiza and putative pathogens. Ascomycota phylum was abundant. Beside Ascomycota phylum, Basidiomycota members were also found in argan roots. Geopora, Sebacina, Knufia, Tomentella, Penicillim had high relative abundance. Our results highlighted a non-nested assemblage of fungi. Current non-nested findings also confirm that fungi have similar pattern found in other habitats. Pairwise analysis mirrored segregation pattern between same and different functional fungal group. Fungi in semi-arid conditions are non-randomly structured. Members of Ascomycota phylum had high Z-scores. This is the first molecular study conducted in arid and semi-arid habitats of Algeria aiming to identify fungi associated with roots in argan tree. Given the fact that deserts are among harsh environments and fungi associated to desert plants may have implications for biodiversity and ecosystem functioning.
Inference for likelihood-based estimators of generalized long-memory processes

Despite a recent proliferation of research using cyclical long memory, surprisingly little is known regarding the asymptotic properties of likelihood-based methods. Estimators have been studied in both the time and frequency domains for the Gegenbauer autoregressive moving average process (GARMA). However, a full set of asymptotic results for all parameters has only been proposed by Chung (1996a,b), who present somewhat tenuous results without an initial consistency proof. In this paper, we review the GARMA process and the properties of frequency and time domain likelihood-based estimators using Monte Carlo analysis. The results demonstrate the strong efficacy of both estimators and generally sup- port the proposed theory of Chung for the parameter governing the cycle length. Important caveats await. The results show that asymptotic confidence bands can be unreliable in very small samples under weak long memory, and the distribution theory under the null of an infinitely long cycle appears to be unusable. Possible solutions are proposed, including the use of narrower confidence bands and the application of theory under the alternative of finite cycles.
Forecast generation model of municipal solid waste using multiple linear regression

The objective of this study was to develop a forecast model to determine the rate of generation of municipal solid waste in the municipalities of the Cuenca del Canon del Sumidero, Chiapas, Mexico. Multiple linear regression was used with social and demographic explanatory variables. The compiled database consisted of 9 variables with 118 specific data per variable, which were analyzed using a multicollinearity test to select the most important ones. Initially, different regression models were generated, but only 2 of them were considered useful, because they used few predictors that were statistically significant. The most important variables to predict the rate of waste generation in the study area were the population of each municipality, the migration and the population density. Although other variables, such as daily per capita income and average schooling are very important, they do not seem to have an effect on the response variable in this study. The model with the highest parsimony resulted in an adjusted coefficient of 0.975, an average absolute percentage error of 7.70, an average absolute deviation of 0.16 and an average root square error of 0.19, showing a high influence on the phenomenon studied and a good predictive capacity.
Screening for REM Sleep Behaviour Disorder with Minimal Sensors

Rapid-Eye-Movement (REM) sleep behaviour disorder (RBD) is an early predictor of Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. This study investigates a minimal set of sensors to achieve effective screening for RBD in the population, integrating automated sleep staging (three state) followed by RBD detection without the need for cumbersome electroencephalogram (EEG) sensors. Polysomnography signals from 50 participants with RBD and 50 age-matched healthy controls were used to evaluate this study. Three stage sleep classification was achieved using a Random Forest (RF) classifier and features derived from a combination of cost-effective and easy to use sensors, namely electrocardiogram (ECG), electrooculogram (EOG), and electromyogram (EMG) channels. Subsequently, RBD detection was achieved using established and new metrics derived from ECG and EMG metrics. The EOG and EMG combination provided the best minimalist fully automated performance, achieving $0.57\pm0.19$ kappa (3 stage) for sleep staging and an RBD detection accuracy of $0.90\pm0.11$, (sensitivity, and specificity $0.88\pm0.13$, and $0.92\pm0.098$). A single ECG sensor allowed three state sleep staging with $0.28\pm0.06$ kappa and RBD detection accuracy of $0.62\pm0.10$. This study demonstrated the feasibility of using signals from a single EOG and EMG sensor to detect RBD using fully-automated techniques. This study proposes a cost-effective, practical, and simple RBD identification support tool using only two sensors (EMG and EOG), ideal for screening purposes.
MICSIM-A behavioural microsimulation model for the analysis of tax-benefit reform in the Netherlands

In this paper we present MICSIM. MICSIM is a behavioural microsimulation model for the analysis of structural labour supply effects of changes in the tax-benefit system in the Netherlands. The core of the model is a discrete choice model for labour supply. We estimate preferences for a large number of subgroups, using an exceptionally large and rich administrative household panel dataset. We find that men in couples have much smaller labour supply elasticities than women in couples, in particular when young children are present. Furthermore, cross-elasticities of women in couples are non-negligible. The labour supply elasticity is relatively high for single parents with young children, much lower for single parents with older children, and also relatively low for singles without children. The decision whether or not to participate is much more responsive to financial incentives than the hours per week decision, though for women in couples with young children the hours worked per week response is also relevant. We illustrate the workings of the model with a number of policy simulations. Because intensive margin responses are small, and cross-effects of the income of the husband on the labour supply of women are non-negligible, the impact of marginal tax rates on total hours worked of couples is limited. Because people are more responsive along the extensive margin, changes in the participation tax rate, via e.g. changes in social assistance and in the income dependent subsidy for families with children, have larger effects on total hours worked. An in-work tax credit targeted more at lower incomes is more effective in increasing labour supply than an across-the-board in-work tax credit. Fiscal incentives to work for mothers with young children are effective. Childcare subsidies are also an implicit subsidy for work for mothers with young children, but they are expensive from the perspective of the government because they encourage substitution of informal for formal care. JEL codes: C25, C52, H31, J22
COMPARISON OF PVT CORRELATIONS FOR PREDICTING CRUDE OIL PROPERTIES: THE BRAZILIAN CAMPOS BASIN CASE STUDY

Pressure-Volume-Temperature correlations are essential for estimating the required parameters necessary for the identification of reservoir fluid properties when experimental laboratory data are not readily available. Although several models have been published for different oil fields, there is a lack of studies addressing the Brazilian pre-salt region. Hence, in this paper we compared twenty empirical correlations for the determination of the solution gas-oil ratio, oil formation-volume-factor, and under-saturated oil viscosity for Brazilian pre-salt oil samples collected from the Campos Basin region, originally evaluated by Elias and Trevisan (2016). From our statistical results, some models presented good estimation performances when compared to said reference’s results. In fact, through a statistical analysis, Al-Shammasi (2001)’s correlation proved to be the best estimation method for solution gas-oil ratio, whereas Al-Marhoun (1985) and Beal’s (1946) correlations were deemed the most accurate for the prediction of oil formation-volume-factor and under-saturated oil viscosity, respectively.
The Effects of Sales Representatives on Customer Satisfaction in Logistics Service Industry

Logistics Service Providers (LSP) are companies that provide services as transportation, warehousing, handling, circulation and processing, delivery and information technology to other companies. Their industry has experienced an exponential growth worldwide, challenging their management to deliver solid value propositions to increasingly demanding customers, this is a task usually delivered by sales representatives, as they are the link between the customers and the company. Nicaragua has been chosen to be the place of study of this paper is because there is no similar study in the country that could provide important information about LSPs, thus it is inferred that their sales strategies are empirical, with a poor knowledge of their customer behavior and their decision making process. This study focuses on investigate the impact of: sales representative trust, commitment to the sales representative, sales representative´s consultative selling behavior and relational selling behavior in a customer´s satisfaction. The data recollection was made by applying 200 questionnaires distributed to LSP´s customers in Nicaragua, this information was later analyze with SPSS and AMOS. The results of this thesis demonstrate a positive relationship between the 4 independent variables: customer trust, customer commitment, consultative selling behavior and relational selling behavior with the dependent variable customer satisfaction.
Computing partition functions in the one-clean-qubit model

We present a method to approximate partition functions of quantum systems using mixed-state quantum computation. For positive semi-definite Hamiltonians, our method has expected running-time that is almost linear in $(M/(\epsilon_{\rm rel}\mathcal{Z} ))^2$, where $M$ is the dimension of the quantum system, $\mathcal{Z}$ is the partition function, and $\epsilon_{\rm rel}$ is the relative precision. It is based on approximations of the exponential operator as linear combinations of certain operators related to block-encoding of Hamiltonians or Hamiltonian evolutions. The trace of each operator is estimated using a standard algorithm in the one clean qubit model. For large values of $\mathcal{Z}$, our method may run faster than exact classical methods, whose complexities are polynomial in $M$. We also prove that a version of the partition function estimation problem within additive error is complete for the so-called DQC1 complexity class, suggesting that our method provides a super-polynomial speedup for certain parameter values. To attain a desired relative precision, we develop a classical procedure based on a sequence of approximations within predetermined additive errors that may be of independent interest.
ROLE OF PAP SMEAR AS A SCREENING TEST IN PRECANCEROUS AND CANCEROUS LESIONS OF CERVIX.

Introduction: A pap smear is a simple, co-effective, non invasive screening test in detecting precancerous and cancerous lesion of cervix and also useful for early detection and implementation of appropriative treatment in pre invasive cervical lesions. Early epithelial changes are recognised by pap smear test. Based on pap smear results to educate the women regarding symptoms of cervical cancer. Aim: Based on results of study, to differentiate between pre invasive and invasive carcinoma of cervix. Materials and Methods: The present study was done over a period of three years period (February 2016 - January 2019). The total number of 966 cases was studied in department of pathology, Government medical college, Kadapa. All the cases were categorised based on cyto-morphological features of pap smear. Requirement of materials: Cervical smears, coupling jars, suitable fixative is Isopropyl alcohol, Alcohol fixed slides were taken for Papanicolaou stain. Results: The present study done on total 966 cases, out of these inflammatory lesions were 628 cases (65.01%), ASCUS were 228 cases (23.60%), LSIL were 62 cases (6.41%), HSIL were 28 cases (2.89%) and malignancy seen in 20 cases (2.07%). Predominate age group in ASCUS and LSIL was fourth decade. HSIL was seen in Fifth decade. Depending on clinical data predominant cases 760cases (78.67%) were presented with leucorrhoea. Keywords: Cervical smears, Papanicolaou stain, Cervical lesions
Generating large scale‐free networks with the Chung–Lu random graph model

Random graph models are a recurring tool‐of‐the‐trade for studying network structural properties and benchmarking community detection and other network algorithms. Moreover, they serve as test‐bed generators for studying diffusion and routing processes on networks. In this paper, we illustrate how to generate large random graphs having a power‐law degree distribution using the Chung–Lu model. In particular, we are concerned with the fulfillment of a fundamental hypothesis that must be placed on the model parameters, without which the generated graphs lose all the theoretical properties of the model, notably, the controllability of the expected node degrees and the absence of correlations between the degrees of two nodes joined by an edge. We provide explicit formulas for the model parameters to generate random graphs that have several desirable properties, including a power‐law degree distribution with any exponent larger than 2, a prescribed asymptotic behavior of the largest and average expected degrees, and the presence of a giant component.
Stem-driven Language Models for Morphologically Rich Languages

Neural language models (LMs) have shown to benefit significantly from enhancing word vectors with subword-level information, especially for morphologically rich languages. This has been mainly tackled by providing subword-level information as an input; using subword units in the output layer has been far less explored. In this work, we propose LMs that are cognizant of the underlying stems in each word. We derive stems for words using a simple unsupervised technique for stem identification. We experiment with different architectures involving multi-task learning and mixture models over words and stems. We focus on four morphologically complex languages -- Hindi, Tamil, Kannada and Finnish -- and observe significant perplexity gains with using our stem-driven LMs when compared with other competitive baseline models.
Bayesian Approach for Determining Microlens System Properties with High-angular-resolution Follow-up Imaging

We present the details of the Bayesian analysis of the planetary microlensing event MOA-2016-BLG-227, whose excess flux is likely due to a source/lens companion or an unrelated ambient star, as well as of the assumed prior distributions. Furthermore, we apply this method to four reported planetary events, MOA-2008-BLG-310, MOA-2011-BLG-293, OGLE-2012-BLG-0527, and OGLE-2012-BLG-0950, where adaptive optics observations have detected excess flux at the source star positions. For events with small angular Einstein radii, our lens mass estimates are more uncertain than those of previous analyses, which assumed that the excess was due to the lens. Our predictions for MOA-2008-BLG-310 and OGLE-2012-BLG-0950 are consistent with recent results on these events obtained via Keck and Hubble Space Telescope observations when the source star is resolvable from the lens star. For events with small angular Einstein radii, we find that it is generally difficult to conclude whether the excess flux comes from the host star. Therefore, it is necessary to identify the lens star by measuring its proper motion relative to the source star to determine whether the excess flux comes from the lens star. Even without such measurements, our method can be used to statistically test the dependence of the planet-hosting probability on the stellar mass.