Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroendocrine control of female reproductive function by the activin receptor ALK7

Activins are critical components of the signaling network that controls female reproduction. However, their roles in hypothalamus, and the specific functions of their different receptors, have not been elucidated. Here, we investigated the expression and function of the activin receptor ALK7 in the female reproductive axis using Alk7‐knockout mice. ALK7 was found in subsets of SF1‐expressing granulosa cells in the ovary, FSH gonadotrophs in the pituitary, and NPY‐expressing neurons in the arcuate nucleus of the hypothalamus. Alk7‐knockout females showed delayed onset of puberty and abnormal estrous cyclicity, had abnormal diestrous levels of FSH and LH in serum, and their ovaries showed premature depletion of follicles, oocyte degeneration, and impaired responses to exogenous gonadotropins. In the arcuate nucleus, mutant mice showed reduced expression of Npy mRNA and lower numbers of Npy‐expressing neurons than wild‐type controls. Alk7 knockouts showed a selective loss of arcuate NPY/AgRP innervation in the medial preoptic area, a key central regulator of reproduction. These results indicate that ALK7 is an important regulator of female reproductive function and reveal a new role for activin signaling in the control of hypothalamic gene expression and wiring. Alk7 gene variants may contribute to female reproductive disorders in humans, such as polycystic ovary syndrome. —Sandoval‐Guzmán, T. , Göngrich, C. , Moliner, A. , Guo, T. , Wu, H. , Broberger, C. , Ibáñez, C. F. Neuroendocrine control of female reproductive function by the activin receptor ALK7. FASEB J. 26, 4966–4976 (2012). www.fasebj. org
Mixed pixel return separation for a full-field ranger

Full-field amplitude modulated continuous wave range imagers commonly suffer from the mixed pixel problem. This problem is caused by the integration of light from multiple sources by a single pixel, particularly around the edges of objects, resulting in erroneous range measurements. In this paper we present a method for identifying the intensity and range of multiple return values within each pixel, using the harmonic content of the heterodyne beat waveform. Systems capable of measurements at less than 90 degree phase shifts can apply these methods. Our paper builds on previous simulation based work and uses real range data. The method involves the application of the Levy-Fullagar algorithm and the use of the cyclic nature of the beat waveform to extract the mean noise power. We show that this method enables the separation of multiple range sources and also decreases overall ranging error by 30% in the single return case. Error in the two return case was found to increase substantially as relative intensity of the return decreased.
Clustering-based approach for detecting breast cancer recurrence

This paper aims to assess the effectiveness of three different clustering algorithms, used to detect breast cancer recurrent events. The performance of a classical k-means algorithm is compared with a much more sophisticated Self-Organizing Map (SOM-Kohonen network) and a cluster network, closely related to both k-means and SOM. The three clustering algorithms have been applied on a concrete breast cancer dataset, and the result clearly showed that the best performance was obtained by the cluster network, followed by SOM and k-means, their predicting accuracy ranging from 62% to 78%. Based on the patients' segmentation regarding the occurrence of recurrent events, new patients may be labeled according to their medical characteristics as developing or not recurrent events, thus supporting health professionals in making informed decisions.
Deep Anterior Lamellar Keratoplasty in Keratoconic Patients with versus without Vernal Keratoconjunctivitis

Purpose: To compare the clinical outcomes of deep anterior lamellar keratoplasty (DALK) for keratoconus in patients with vernal keratoconjunctivitis (VKC) versus those without VKC. Methods: In this retrospective comparative study, records of 262 eyes with keratoconus (Group 1) and 28 keratoconic eyes with VKC (Group 2) that had undergone DALK were compiled. Reviewed parameters included length of follow-up, best-corrected visual acuity (BCVA), refractive error, complications and cumulative graft survival. Results: Mean duration of follow-up was 38.6 ± 20.2 and 34.4 ± 20.9 months in groups 1 and 2, respectively (P = 0.21). Mean post-operative BCVA was 0.19 ± 0.11 and 0.20 ± 0.15 logMAR, in groups 1 and 2 (P = 0.79). BCVA≥20/40 was achieved in 91.6 and 88.5% of eyes in groups 1 and 2, respectively (P = 0.48). Epithelial problems were encountered in 31.3 and 42.9% of operated eyes, respectively (P = 0.16). Vascularization of suture tracts and stitch abscesses were encountered more frequently in the eyes with VKC (P = 0.01 and <0.001, respectively). At the 33-month follow-up examination, rejection-free graft survival rates were 56.0% in group 1 and 33.3% in group 2, with mean durations of 41.0 and 32.1 months, respectively (P = 0.15). Graft survival rates were 98.1% in group 1 and 95.0% in group 2, with mean durations of 88.6 and 88.4 months, respectively (P = 0.74). Conclusion: Clinical outcomes of DALK in keratoconic eyes with VKC were comparable to those in eyes with keratoconus alone. However, complications such as suture tract vascularization and stitch abscesses were more common when VKC coexisted, necessitating closer monitoring.
Automated Facial Expression Recognition for Product Evaluation

Facial expression play an important role in signaling interest and opinion about a product. In this paper we present a negative affect classifier that detects nose wrinkles (AU9) or brow lowerer (AU4). Our approach uses an automatic mechanism for extracting the frames of interest in videos. We employ an automatic facial feature tracker to detect the area of interest in each frame, we then apply Gabor Jets for feature extraction followed by applying a dynamic Bayesian network classifier. We validate our classifier on two corpora: the first is of posed videos, the second is from a corpus of spontaneous videos of people evaluating two different beverages. We achieved an average accuracy of 97% for posed videos and 96% for spontaneous videos. We also, show that negative facial expressions captured using our machine vision technique are more predictive than selfreports. This was proven by correlating between self reports and reports provided by human coders which is used as our ground truth for our classifier.
Extracting Representative Tags for Flickr Users

Tags are very popular in online social communities (like You tube, Flickr) and provide valuable and crucial information for these communities. But at the same time, there exist a lot of noisy tags, which leads many researches to tag suggestion, tag recommendation for the items, such as to the websites, photos, books, movies, and so on. Most of them used the textural features of tags to extract related tags to items, like tag frequency. In our paper, we address the problem of tag recommendation for users in Flickr. This issue is as important as tag recommendation for items, because representative tags of users are strongly related to users¡¯ favorite topics. We propose several novel features of tags which we call them social features as well as textual features. Experimental results show that our proposed scheme achieves viable performance on tag recommendation for users.
Robustness of Next Generation Sequencing on Older Formalin-Fixed Paraffin-Embedded Tissue

Next Generation Sequencing (NGS) technologies are used to detect somatic mutations in tumors and study germ line variation. Most NGS studies use DNA isolated from whole blood or fresh frozen tissue. However, formalin-fixed paraffin-embedded (FFPE) tissues are one of the most widely available clinical specimens. Their potential utility as a source of DNA for NGS would greatly enhance population-based cancer studies. While preliminary studies suggest FFPE tissue may be used for NGS, the feasibility of using archived FFPE specimens in population based studies and the effect of storage time on these specimens needs to be determined. We conducted a study to determine whether DNA in archived FFPE high-grade ovarian serous adenocarcinomas from Surveillance, Epidemiology and End Results (SEER) registries Residual Tissue Repositories (RTR) was present in sufficient quantity and quality for NGS assays. Fifty-nine FFPE tissues, stored from 3 to 32 years, were obtained from three SEER RTR sites. DNA was extracted, quantified, quality assessed, and subjected to whole exome sequencing (WES). Following DNA extraction, 58 of 59 specimens (98%) yielded DNA and moved on to the library generation step followed by WES. Specimens stored for longer periods of time had significantly lower coverage of the target region (6% lower per 10 years, 95% CI: 3-10%) and lower average read depth (40x lower per 10 years, 95% CI: 18-60), although sufficient quality and quantity of WES data was obtained for data mining. Overall, 90% (53/59) of specimens provided usable NGS data regardless of storage time. This feasibility study demonstrates FFPE specimens acquired from SEER registries after varying lengths of storage time and under varying storage conditions are a promising source of DNA for NGS.
Near-IR spectroscopy of planetary nebulae precursors ?

We present near-IR spectroscopy of a sample of 30 IRAS sources recently identified as late AGB stars, post-AGB stars or early PNe. The spectra obtained are centered at various wavelengths covering the molecular hydrogen $v=1$ $\rightarrow $0 S(1) 2.122 μ m and $v=2$ $\rightarrow$1 S(1) 2.248 μ m emission lines, the recombination lines of hydrogen Br γ 2.166 μ m, Pf γ 3.741 μ m and Br α 4.052 μ m, and the CO[ $v=2$ $\rightarrow$0] first overtone bandhead at 2.294 μ m. As a result of these observations we have detected molecular hydrogen emission for the first time in 9 of these sources and confirmed a previous detection by Weintraub et al. ([CITE]). This increases from 4 to 13 the total number of proto-PNe detected in molecular hydrogen. In most cases, the positive detections also show emission in the recombination lines of hydrogen (with the exception of IRAS 17150-3224) indicating that the onset of molecular hydrogen emission takes place in the post-AGB phase, very shortly before the nebula becomes ionized. When the molecular hydrogen is fluorescence-excited the detection rate is found to be directly correlated with the evolutionary stage of the central star, rather than with the nebular morphology. When the temperature of the central star is hot enough, fluorescence excitation can be induced by the absorption of UV photons escaping from the rapidly evolving central post-AGB star. In contrast, shock-excited molecular hydrogen is detected only in strongly bipolar proto-PNe, sometimes even at an early stage in the post-AGB phase. Shock excitation is the consequence of the interaction of the fast post-AGB wind with the slow wind material ejected during the AGB. The strong correlation of shock-excited molecular hydrogen emission with bipolarity found confirms the result previously reported by Kastner et al. ([CITE]) in evolved PNe. However, our results show that this correlation does not exist in the case of fluorescence-excited molecular hydrogen.
A Design of New Face/Non-face Classifier Based on Face Boundary Training

In this paper, we propose a new face detector that is less affected with background. To reduce the affect of various backgrounds, we apply more strong constraints to face. In previous works, classier in face detector determine that the input image is more like face or more like non-face, so the training set for non- face has more affect face detection. But to apply more strong constraints for face, the detector determines only whether the input image is like face or not, i.e. background has less affect in decision process. Constraints that used in this paper for face is how the image is look like face (image based), and that the image satisfies structural features of face, especially edge of face. The experimental result for proposed face/non-face classifier showed 95.8% classification rate of face and 96.5% classification rate of non-face with a small quantity efface image for a set of training.
Do moodle reports and logs meet the needs of educational supervision?

We conducted a cross-sectional retrospective study in order to evaluate the usage of the software named Moodle Learning Management Software (LMS) with the purpose of educational auditing and its functionality. The study was performed over a practice of education, which deals with PBL activities with a networked learning approach. Course subjects were the instructional principles and methods. Students enrolled into the course from Hacettepe University Faculty of Education, Department of Computer Education and Instructional Technology in the academic year 2012-2013. The course was delivered via the Moodle LMS platform. The data stored in the database of the software was extracted to make auditing evaluations about the software, and auditing techniques were applied. A comparison was made between the data received from the software's modules that could be used for auditing purposes and the data on which the auditing techniques were applied after extracting and tutor-oriented evaluations were performed. The evaluations regarding the monitoring, assessing and managing of the teaching process in the activities of the Networked PBL of Moodle software's auditing function were made in consideration of the findings. It was concluded that Moodle was sufficient for meeting the basic data requirements for educational auditing, its modules alone did not have Computer Assisted Audit Techniques (CAATs) function; a CAATs add-in, which would be created or used for fulfilling the educational requirements, would be useful.
Information Diffusion and Provenance in Online Social Media Networks

Traditional data mining techniques are going through an extensive research so as to suit their application in the dynamically evolving social medi a networks which are not only large in size but als o require real time processing of data streams. One s uch application which is of social, industrial and political interest is to maximize (sometimes even minimize) i nformation diffusion in online social media networks. Word-of-mouth (w-o-m) communications have been larg ely employed in a wide range of application scenarios ranging from marketing strategies to crea ting mass awareness. In recent years, we saw an exp losion in the growth of online social networks with many s uccessful service providers like Facebook, twitter, YouTube, LinkedIn etc. ruling the market. The use of online social networks is not limited to fun and building professional networks. Online social netwo rks are now seen as a powerful medium to effect the social and political environment of a country and the world as a whole. Information on these social networkin g sites sometimes needs to be propagated very effectively a nd quickly to fulfill the concerned strategies. It is equally important that given some information present on so cial network, we are able to derive its origin so t hat rumours can be distinguished from truth. In this paper, we discuss some of the issues and challenges i n information diffusion and provenance from online social networks point of view. We also discuss some o f the approaches and models that have been used for infor mation diffusion and provenance in online social networks in recent past. Some of these approaches h ave been evaluated by researchers for specific soci al network services but we will discuss them in a gene ral sense.
FUSION OF INSAR AND GIS DATA FOR 3D BUILDING RECONSTRUCTION AND CHANGE DETECTION

The new generation of space-borne high resolution SAR sensors such as TerraSAR-X, SAR-Lupe or CosmoSkyMed provides SAR images of 1-3m spatial resolution or even below in special spotlight modes. Naturally, the development of methods to automatically derive detailed cartographic information of both rural and urban areas from this kind of data is a major issue driven by these missions. Since SAR is an active system and largely independent from weather conditions; it is furthermore an attractive imaging technology for rapidly acquiring area-wide information of regions hit by disasters such as floodings, landslides, or earthquakes. Thus, the development of automatic methods for damage analysis or – generally – change detection is another important issue. For such kind of tasks existing Geodata available from Geographic Information Systems (GIS) have to be adjusted with current SAR data. In this paper an approach for 3D building reconstruction based on multi-temporal information fusion by exploiting GIS and InSAR data is presented. Thereby, GIS data consisting of building footprints are used as initial information. The simulation exploits building hypotheses, which are based on the given 2D footprint and an assumed building height, and provides as result synthetic InSAR phases. An iterative adjustment between simulated and measured real InSAR phases enables the reconstruction of the current building shape. Our approach is tested on single-pass airborne InSAR data.
A multiwavelength study of the massive star-forming region IRAS 06055+2039 (RAFGL 5179)

Aims. We present a multiwavelength study of the massive star-forming region associated with IRAS 06055+2039. Methods. Narrow-band near-infrared (NIR) observations were carried out with UKIRT-UFTI in molecular hydrogen and Br γ lines to trace the shocked and ionized gases, respectively. We have used 2MASS ${\it J H K}_{\rm s}$ data to study the nature of the embedded cluster associated with IRAS 06055+2039. The radio emission from the ionized gas was mapped at 610 and 1280 MHz using the Giant Metrewave Radio Telescope (GMRT), India. Emission from warm dust and the unidentified infrared bands (UIBs) was estimated using the mid-infrared (8–21 μ m) data from the MSX survey. Submillimetre emission from the cold dust at 450 and 850 μ m was studied using JCMT-SCUBA. Results. For the infrared cluster associated with IRAS 06055+2039, we obtain a power-law slope of $0.43\pm0.09$ for the K s -band luminosity function (KLF), which is in good agreement with other young embedded clusters. We estimate an age of 2–3 Myr for this cluster. Apart from the diffuse emission, the high-resolution 1280 MHz map also shows the presence of several discrete sources that possibly represent high-density clumps. The morphology of shocked molecular hydrogen forms an arc towards the N-E of the central IRAS point source and envelopes the radio emission. Submillimetre emission shows the presence of a dense cloud core that is probably at an earlier evolutionary stage compared to the ionized region with shocked molecular gas lying between the two. The total mass of the cloud is estimated to be ~7000–9000 $M_{\odot}$ from the submillimetre emission at 450 and 850 μ m. Conclusions. The multiwavelength study of this star-forming complex reveals an interesting scenario where regions are at different stages in the evolution of star formation.
Global robust stability of a class of discrete-time interval neural networks

This paper is concerned with global robust stability of a general class of discrete-time interval neural networks which contain time-invariant uncertain parameters with their values being unknown but bounded in given compact sets. We first introduce the concept of diagonally constrained interval neural networks and present a necessary and sufficient condition for global robust stability of the interval networks regardless of the bounds of nondiagonal uncertain parameters of state feedback and connection weight matrices. Then we extend the result to general interval neural networks. Finally, simulation results illustrate the characteristics of the main results.
Detection of cell-cyclic elements in mis-sampled gene expression data using a robust Capon estimator

We present a method for the estimation of possible cell-cyclic elements in mis-sampled microarray data. Accurate assessment of the frequency content of microarray data gives insight into genes which could be cell-cycle regulated. Cell-cycle regulation is one component of the complex network of genetic regulatory processes and is especially relevant to the study of cancer. As cDNA microarray experiments involve human sampling of cell populations, slight variations in the sampling times invariably occur. We propose estimating the frequency content of microarray data using the recent robust Capon estimator, and formulate a suitable uncertainty region over which to minimize. The estimator is shown to yield robust estimates with real microarray data and to identify cell-cyclic genes that elude both the traditional periodogram and the Capon spectral estimator.
Adaptive multi-scale retinex algorithm for contrast enhancement of real world scenes

Contrast enhancement is a classic image restoration technique that traditionally has been performed using forms of histogram equalization. While effective these techniques often introduce unrealistic tonal rendition in real-world scenes. This paper explores the use of Retinex theory to perform contrast enhancement of real-world scenes. We propose an improvement to the Multi-Scale Retinex algorithm which enhances its ability to perform dynamic range compression while not introducing halo artifacts and greying. The algorithm is well suited to be implemented on the GPU and by doing so real-time processing speeds are achieved.
Memetic Computation—Past, Present & Future [Research Frontier]

Taking a lead from the multi-faceted definitions and roles of the term "meme" in memetics, a plethora of potentially rich memetic computing methodologies, frameworks and operational memeinspired algorithms have been developed with considerable success in several realworld domains in the last two decades. This article showcase several successful deployments of memetic computing methodologies for solving complex problems, from science, engineering to digital arts.
MAGIC-Pointing on Large High-Resolution Displays

Display space in offices constantly increased in the last decades. We believe that this trend will continue and ultimately result in the use of wall-sized displays in the future office. One of the most challenging tasks while interacting with large high-resolution displays is target acquisition. The most important challenges reported in previous work are the long distances that need to be traveled with the pointer while still enabling precise selection as well as seeking for the pointer on the large display. In this paper, we investigate if MAGIC-Pointing, controlling the pointer through eye gaze, can help overcome both challenges. We implemented MAGIC-Pointing for a 2.85m x 1.13m large display. Using this system we conducted a target selection study. The results show that using MAGIC-Pointing for selecting targets on wall-sized displays decreases the task completion time significantly and it also decreases the users' task load. We therefore argue that MAGIC-Pointing can help to make interaction with wall-sized displays usable.
A Guided Tour of the World of Rational Expectations Models and Optimal Policies

This working paper after quickly reviewing the different types of existing macro models presents some basic tools that have proved useful for analysing monetary policy in recent years. Through the use of a simple quantitative forward-looking model of output, inflation and interest rate determination, the paper tries to familiarise the reader with some of the techniques used in research on optimal policy, including rational expectations theory, timeconsistency analysis, the Lucas critique and computer simulation techniques. The explanation proceeds gradually. First, a single linear difference equation is used to explain how solutions to models with forward-looking expectations can be obtained. Then it deals with methods used to solve more general models for optimal policies. Finally, the potential usefulness of these techniques is explained through a series of applications to monetary policy.