Miracle-dz/UniFAR-FTUs huggingface dataset:
Forthcoming in : Behavioral Dimensions of Retirement Economics

Models of retirement behavior have typically employed a traditional family framework that assumes all decisions are made by one agent–the male household head. As the proportion of married women approaching retirement with substantial work histories rises, bargaining models of marriage can provide an alternative framework, allowing us to consider separately the actions and intentions of the husband and wife and the prospect of dissolution of the marital unit through divorce or death. Game-theoretic models permit a broader range of rational behavior than joint utility family models, and may help to explain some empirical puzzles, such as the failure of consumption profiles to correspond to the individual life-cycle model. Bargaining models also have potentially important implications for retirement policy and in particular social security reform: control over resources and the ability to make independent decisions increase the ability of the husband or wife to negotiate household outcomes that are in their own private interest and affect the distribution of family resources. * Department of Economics, Box 353330, University of Washington, Seattle, WA 98195. Email: lundberg@u.washington. edu. Henry Aaron and Dick Startz have provided helpful comments, but are not responsible for remaining errors.
The Effect of Dietary Inclusion of Probiotics on Growth and Intestinal Morphology of Broiler Chickens

Asilcag Trading Ltd. Nicossia, Cyprus. Near East University, Faculty of Veterinary Medicine, Department of Histology and Embriology, Nicossia, North Cyprus Kafkas University, Faculty of Medicine, Department of Histology and Embriology, Kars, Turkey Kafkas University, Faculty of Veterinary Medicine, Department of Histology and Embriology, Kars, Turkey a Research support provided in part by a grant from the Scientific and Technological Research Council of Turkey, Ankara, Turkey Corresponding author’s Email: mgulmez@hotmail.com; ORCID: 0000-0003-3888-6815 Received: 07 Feb. 2019 Accepted: 15 Mar. 2019 ABSTRACT Probiotics are currently under investing the most valuable substances alternative to antibiotic growth promoters in poultry breeding practice. This research was performed to evaluate the effect of supplementing broiler drinking water with probiotics (Pediococcus acidilactici and Bacillus subtilis) at a concentration of ≥10 CFU/ml during 42 days of feeding period on growth performance and gut health. A total of 144 one-day-old Ross 308 broiler chicks (mixed gender) with an average initial BW of 42.3 g were used. The chicks were allotted to pens with 12 birds per pen and six replications per treatment with food and water provided ad libitum. Feed intake of Probiotic group was 4134 g, 338 g less than that of control group. Live weight of probiotic group was 2537 g and a 113 g more than that of control group. The feed conversion ratio of probiotic group was 1.61, 0.22 less than that of control group. The crypt depth of probiotic group (1110.46 ± 224.016 μm) was statistically deeper than that of control group (949.39 ± 114.166 μm) in ileum. Continuously use of probiotics in drinking water of commercial poultry flocks appears to be alternative to AGPs. The results of this study provide a greater understanding of the impact of long-life use of probiotics on broiler health and growth performances.
Study of Blood Glucose State and Its Relationship with Lipid Profiles in Diabetic Patients in Kirkuk Province

Background: Prevalence of Type 2 DM has been increasing steadily everywhere the globe and quick turning into an outbreak in some countries of the globe, particularly in poorly developed countries. Hyperlipidemia is a common comorbidity in diabetes and is associated with diabetes. Aim: The purpose of the present study is to investigate the blood lipid levels and their relationship with HbA1c and blood glucose in diabetic patients. Patients and Methods: One hundred –four, type 2 diabetic diagnosed patients (equal sex) attending Babagurgur diabetes center in K1 Hospital-Kirkuk from 10/11/2018 to 10/4/2019, were subjected to this study. Their ages ranged between 32-79 years with a mean age of 54.8 ± 8.3 years. Biochemical tests for evaluation of diabetes; fasting blood glucose (FBG) and hemoglobin A1c (HbA1c %), and lipid profiles; cholesterol, triglyceride (TG), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) levels were measured. Results: The results showed that there was a significant(p<0.05) increase in the tests of evaluation of blood sugar; FBG was 13.6 mmol/L and HbA1c of 9.6 % as mean values among the patients when compared with the same parameters in control group. Serum levels of cholesterol, triglycerides, and LDL showed significant (p<0.05) increase, while LDL decreased. HbA1c and FBG levels were correlated with increasing levels of cholesterol, triglycerides, and HDL. Regarding the changes in parameters among age groups, the age group 50-59 years constituted most the diabetic cases (43; 41.3%). Conclusion: It is concluded that the older age and poor glycemic control are important risk factors related to hyperlipidemia in the current T2DM population and associated with adverse lipid profiles.
Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks

We study, theoretically and experimentally, the departure time behavior of commuters in a Y-shaped network with two bottlenecks and costs attached to early and late arrivals as well as time spent in the bottlenecks. A mixed-strategy equilibrium solution is constructed which implies that, for certain parameter values, expanding one bottleneck, while keeping the capacity of the other fixed, may induce a shift in the endogenously-determined departure times so as to increase total travel costs. Our experimental results are strongly supportive of this paradoxical prediction and the equilibrium solution that gives rise to it. (JEL C72, C92, R49)
Accelerating Deep Learning Optimization in Mocha . jl Student :

The process of iteratively minimizing a cost function, as in machine learning, is typically done through Stochastic Gradient Descent (SGD). Even though this technique has existed and been widely used for decades, recent advances in deep-learning and other large scale learning problems have brought about new challenges to feasibly using SGD for very large scale problems. While there have been advances in accelerating gradient descent, minimal work has been done to investigate their effectiveness in a deep or any non-convex setting. In this project, I will improve the state of the art Julia deep learning platform, Mocha.jl, to support various different types of optimization schemes. By having a modular programing approach the optimizers created as part of this project will be able to be “plugged into” existing deep learning code by changing only a single line of code, but still achieve accelerated training speedups.
Assessment of Alkaline Phosphatase activity in Gingival Crevicular Fluid as a Skeletal Maturity Indicator

BACKGROUND AND OBJECTIVES: The aim of the study was to evaluate gingival crevicular fluid (GCF) alkaline phosphatase (ALP) activity in growing subjects in relation to stages of skeletal maturation, ie, the growth phase, as prepubertal, pubertal, and postpubertal. METHODS: Sixty healthy growing subjects (27 girls and 33 boys; age range, 9 – 18 years) were enrolled in this study that followed a double-blind, prospective, cross-sectional design. Collection of GCF was performed at the mesial and distal sites of both central incisors, for the maxilla and mandible. Growth phase was assessed through the hand wrist radiograph using Bjork and Grave method. GCF parameter was expressed as total ALP activity.RESULTS: The total GCF ALP activity showed a peak for the pubertal growth phase. No differences were seen between the maxillary and mandibular sites, or between the sexes, for any GCF parameter. CONCLUSION: The GCF ALP activity has potential as a diagnostic aid for identification of the pubertal growth phase in individual subjects
populations and environmental differences among beach mouse Adaptive basis of geographic variation : genetic , phenotypic

publication. Citations to Advance online articles must include the digital object identifier (DOIs) and date of initial online articles are citable and establish publication priority; they are indexed by PubMed from initial publication. the paper journal (edited, typeset versions may be posted when available prior to final publication). Advance Advance online articles have been peer reviewed and accepted for publication but have not yet appeared in
Spectral Regrowth Suppress Spectral Sidelobe Regrowth with Data Signal Predistortion

This article introduces a method to suppress the regrowth of the power spectral sidelobes of an OQPSK data stream by predistorting the modulated signal prior to soft saturation power amplification. The heart of the scheme is the adaptive cancellation of the “para signal,” which is defined as the product of two input signal characteristics: the fractional carrier amplitude ripple and the phase modulation. The predistortion operation augments the fractional ripple at the amplifier input, thus counteracting the inverse effect within the soft saturating amplifier. This scheme is remarkably simple, automatically adapts to changing amplifier characteristics, and may be introduced as an applique in existing transmitters. By employing the predistorter, the transmitter can operate at a higher power level in the amplifier than before, leaving the desired aspects of the transmitted signal intact while still meeting stringent specifications on spectral containment. With reference to Figure 1, the signal predistortion scheme described here is an applique operating at baseband, intermediate frequency (IF) or radio frequency (RF), inserted somewhere between either:
Learning Lower-Dimensional Embeddings of CyTOF Data with Deep Autoencoders

Autoencoders are an unsupervised learning approach of using neural networks to perform data compression, and can be trained to perform PCA or spectral graph clustering [3, 9, 8]. In this project, we investigate the use of deep sparse and denoising autoencoders as a method of data compression in biology to learn lower-dimensional embeddings and clusterings of single-cell mass cytometry data across different cell types. To validate the model, we first trained our model to learn embeddings for the MNIST dataset and data generated from multivariate gaussian distributions, and compared the embeddings to those generated by shallow, single hidden layer sparse and denoising autoencoders. Next, we experimented with how well the generated embeddings would cluster data from cells that are of the same type. For this, we trained the model on a blood dataset from Dr. Kang’s lab in the Yale School of Medicine, and measured how well k-means clustered labels from the embedding matched the true labels. We then compared our clustering performance to the results from a newly introduced clustering algorithm called Phenograph, which develops the Louvain method clustering approach to work on high-dimensional single-cell data [5]. Finally, we present some visualizations generated by the autoencoder after being trained on a clinical blood dataset from the Yale New Haven Hospital. Using our model, we plotted the middle layer of the autoencoder in two dimensions to highlight structural similarities and differences in the embeddings for blood samples from young and old patients after a kidney transplant. With these plots, we intend to further develop the model to help identify other kinds of phenotypic differences between cell samples from different patients.
An Empirical Study of Common Challenges in Developing Deep Learning Applications

Recent advances in deep learning promote the innovation of many intelligent systems and applications such as autonomous driving and image recognition. Despite enormous efforts and investments in this field, a fundamental question remains under-investigated—what challenges do developers commonly face when building deep learning applications? To seek an answer, this paper presents a large-scale empirical study of deep learning questions in a popular Q&A website, Stack Overflow. We manually inspect a sample of 715 questions and identify seven kinds of frequently asked questions. We further build a classification model to quantify the distribution of different kinds of deep learning questions in the entire set of 39,628 deep learning questions. We find that program crashes, model migration, and implementation questions are the top three most frequently asked questions. After carefully examining accepted answers of these questions, we summarize five main root causes that may deserve attention from the research community, including API misuse, incorrect hyperparameter selection, GPU computation, static graph computation, and limited debugging and profiling support. Our results highlight the need for new techniques such as cross-framework differential testing to improve software development productivity and software reliability in deep learning.
FlowScheduler : Towards Efficient Task Assignment for Hadoop

In recent years, the MapReduce programming model has emerged as the leading framework for developing large-scale, data intensive, applications such as collective intelligence, web indexing, and scientific experimentation. Hadoop is the open source implementation of MapReduce, and is a key piece of infrastructure at many institutions. The performance of Hadoop is linked with its scheduler, which reactively assigns tasks to servers for computation with a greedy Round Robin algorithm. We implement and benchmark the proposed FlowScheduler algorithm (by Fischer et al.) for task assignment in Hadoop. While some algorithms are faster in theory but not in practice, we show that FlowScheduler consistently provides better data-locality than the Round Robin Algorithm. We also demonstrate average case analyses of FlowScheduler’s performance and provide optimizations and analyses for the algorithm for real use cases.
The Effect of Neuromarketing Elements at the Pos on the Consumer ’ s Decision Making Process in the Retail Sector

The aim of this study was to outline the effect of neuromarketing on product presentation at the point of sale in the retail sector. Presented theories help to understand the different tools of neuromarketing. Design elements at the POS and forms of product presentation are discussed in order to realize how these elements influence purchasing behaviour. The data from the quantitative study depicted a significant correlation between dwelling time and money spent in the store. Moreover, people buy more when they make use of product tastings in stores and they spend most for their own consumption coupled with the purchase of a gift. However, it could not be proven that the scent in the shop is essential for the positive perception of the atmosphere.
ANTICIPATING SHOCKS IN THE STATE SPACE : CHARACTERIZING ROBUSTNESS AND BUILDING INCREASINGLY ROBUST EVOLUTIONS

Given dynamics and constraints, the viability kernel gathers points from which there exists an evolution which remains in the constraint set. In this paper, we aim at providing more information: we introduce and study the robustness map which associates each point of the viability kernel with the maximal size of the unexpected disturbance in the state space the system can support now and in the future while always remaining inside the constraint set. We first characterize the hypograph of the robustness map in terms of a viability kernel of an augmented problem. Then the main mathematical result is that the boundary of this hypograph is a viability domain for a particular augmented problem and that the associated regulation map governs increasingly robust evolutions. Given a time horizon, the problem of finding increasingly robust evolutions which reach a given level of robustness is finally solved by the computation of the reaching time of another augmented problem.
Artigo 1 : CULTURE AND PROPAGATION OF MICROSPORIDIA OF VETERINARY INTEREST-CULTURE OF MICROSPORIDIA Artigo 2 : B-1 CELLS AS A COMPONENT OF THE IMMUNE RESPONSE AGAINST MURINE

Microsporidia are obligate intracellular mitochrondria-lacking pathogens that rely on host cells to grow and multiply. Microsporidia, currently classified as fungi, are ubiquitous in nature and are found worldwide. They infect a large number of mammals and are recognized as opportunistic infection agents in HIV-AIDS patients. Its importance for veterinary medicine has been unveiled in recent years through the description of clinical and subclinical forms of infection in domestic and wild animals. Domestic and wild birds may be infected by the same human microsporidia, reinforcing their zoonotic potential. Microsporidiosis in fish are prevalent and cause significant economic losses for fish farming. Some species of microsporidia have been propagated in cell cultures, which may provide conditions for the development of diagnostic techniques, understanding of pathogenesis and immune responses and for the discovery of potential therapies. Unfortunately, the cultivation of these parasites is not fully standardized inmost research laboratories, especially in the veterinary field. The aim of this review is to relate the most important microsporidia of veterinary interest and demonstrate how these pathogens can be grown and propagated in cell culture for diagnostic purposes or for pathogenesis studies. Cultivation of microsporidia allowed the study of its life cycle, metabolism, pathogenesis, diagnosis, and may also serves as a repository for these pathogens for molecular, biochemical, antigenic, and epidemiological studies.
DESIGN OF HIGH POWER INPUT COUPLER FOR CORNELL ERL INJECTOR CAVITIES *

Figure 1: Input coupler in the injector cavity. A 75 kW CW coupler for superconducting injector cavities of Cornell ERL project has been designed. The coupler has variable coupling. Qext varies from 9.2×10 to 8.2×10. The prototype TTF-III TESLA coupler design has been revised to a great extent. Cooling of critical parts has been radically improved. The new design is close to be multipacting-free. The coupler design is presented, as well as results of its thermal analysis. Possible schemes of high power tests are discussed.
Wake-up Radio Ranges: A Performance Study

Wake-up radio technology helps to attenuate unnecessary power consumption by allowing a node to keep its main radio off until it is woken up by a signal to an auxiliary low-power radio receiver. In this paper, we evaluate the range performance of an ultra-low power wake-up radio receiver (WuR) integrated into a wireless device suitable for wireless sensor networking deployments. We run several ranging experiments, both indoors and outdoors, where a transmitter sends wake-up sequences to a receiver positioned meters away. We measure the amount of received sequences and whether they incur errors or not. Our experiments show that for distances up to 24m indoors the tested WuR receives more than 96% of the transmitted sequences. The WuR performs slightly better outdoors, with more than 99% of the sequences being received with negligible amounts of errors.
Pivot Machine Translation in INTERACT Project

The INTERnAtional network on Crisis Translation (INTERACT) project under EU Marie Skłodowska-Curie Actions (MSCA) Research and Innovation Staff Exchange (RISE) Programme aimed at researching translation in crisis scenarios. In this extended abstract, we present the work on Pivot Machine Translation under the INTERACT project.
Computer-Aided Inspection of Optical Components Using Computer Vision Technologies

Light-emitting diode (LED) lenses are one kind of common optical components. The LED lens with uneven surface is difficult to detect surface defects. This research proposes a wavelet packet transformation based partial least square approach to detect surface defects of optical components with uneven surfaces. Three procedures are developed to do the process of defect detection. Firstly, a spatial domain image is converted to wavelet pack domain and the wavelet features of the sub-band images are extracted. Secondly, the partial least square method is used to multivariate transform with wavelet features to obtain latent images. Thirdly, the latent images are fitted by a regression model to get the residual image where the surface defects have been separated. Experimental results show that performance of the wavelet pack based approach in the defect detection is effective and efficient.
Preliminary study on water buffaloes ( Bubalus bubalis ) in marshes of Iraq ( Defining some values of reproductive hormones )

The present study aimed to determine some of reproductive values of water buffaloes in marshes of Iraq which may be used as a primary values for assaying the reproduction and production of water buffaloes. The study performed on immature male and female water buffaloes. LH, FSH and Prolactin hormones were determined. The results showed effect of sex and age on FSH and Prolactin levels. The sex was effective in LH level, while the age was no effective on LH level of male water buffaloes, whereas it was effective in LH level of females. Results were discussed from physiological aspect as compared to previous scientific studies, especially these values, as to Iraqi buffaloes, are regarded new preliminary values.
The ACE2/Ang-(1-7)/Mas Axis Confers Cardiopulmonary Protection against Lung fibrosis and pulmonary hypertension

Rationale: An activated vasoconstrictive, proliferative and fibrotic axis of the renin angiotensin system (RAS; ACE-AngII-AT1R) has been implicated in the pathophysiology of pulmonary fibrosis (PF) and pulmonary hypertension (PH). The recent discovery of a counter-regulatory axis of the RAS comprising of ACE2-Ang-(1-7)Mas has led us to examine the role of this vasoprotective axis on such disorders. Objectives: We hypothesized that Angiotensin-(1-7) [Ang-(1-7)] treatment would exert protective effects against PF and PH. Methods: Lentiviral packaged Ang-(1-7)-fusion gene or ACE2 cDNA was intratracheally administered into the lungs of male SD rats. Two weeks following gene transfer, animals received bleomycin (2.5mg/kg). In a subsequent study, animals were administered monocrotaline (MCT, 50mg/Kg). Results: In the PF study, bleomycin administration resulted in a significant increase in right ventricular systolic pressure (RVSP), which was associated with the development of right ventricular hypertrophy (RVH). The lungs of these animals also exhibited excessive collagen deposition, decreased expression of ACE and ACE2, increased mRNA levels for TGF-β, and other pro-inflammatory cytokines and increased protein levels of the AT1R. Overexpression of Ang-(1-7) significantly prevented all the above mentioned pathophysiological conditions. Similar protective effects were also obtained with ACE2 overexpression. In the PH study, rats injected with MCT developed elevated RVSP, RVH, right ventricular fibrosis and pulmonary vascular remodeling, all of which were attenuated by Ang-(1-7) overexpression. Blockade of the Mas-receptor abolished the beneficial effects of Ang-(1-7) against MCT-induced PH. Page 2 of 48 Conclusions: In conclusion, our observations demonstrate a cardio-pulmonary protective role for the ACE2-Ang-(1-7)-Mas axis in the treatment of lung disorders. Page 3 of 48
Caption Generation for New Yorker Cartoons

We present a method for automatically generating humorous captions for New Yorker Cartoons. Every week, the New Yorker runs a cartoon captioning contest where readers can submit funny captions to an uncaptioned image. We propose that one method to produce humorous captions is to use keywords from the two parts of the incongruity apparent in the image. Given a description file with a manual description of these images, we show the results of extracting keywords and replacing a single word in a known cliche for humorous effect.