Miracle-dz/UniFAR-FTUs huggingface dataset:
Local Transformations of Androgens into Estradiol by Aromatase P450 Is Involved in the Regulation of Prolactin and the Proliferation of Pituitary Prolactin-Positive Cells

In previous studies we demonstrated the immunohistochemical expression of aromatase in pituitary cells. In order to determine whether pituitary aromatase is involved in the paracrine regulation of prolactin-producing pituitary cells and the physiological relevance of pituitary aromatase in the control of these cells, an in vivo and in vitro immunocytochemical and morphometric study of prolactin-positive pituitary cells was carried out on the pituitary glands of adult male rats treated with the aromatase antagonist fadrozole. Moreover, we analyzed the expression of mRNA for the enzyme in pituitary cells of male adult rats by in situ hybridization. The aromatase-mRNA was seen to be located in the cytoplasm of 41% of pituitary cells and was well correlated with the immunocytochemical staining. After in vivo treatment with fadrozole, the size (cellular and nuclear areas) of prolactin cells, as well as the percentage of prolactin-positive cells and the percentage of proliferating-prolactin cells, was significantly decreased. Moreover, fadrozole decreased serum prolactin levels. In vitro, treatment with fadrozole plus testosterone induced similar effects on prolactin-positive cells, inhibiting their cellular proliferation. Our results suggest that under physiological conditions aromatase P450 exerts a relevant control over male pituitary prolactin-cells, probably transforming testosterone to estradiol in the pituitary gland.
A novel LBG algorithm for image compression in wavelet transform domain

The paper presents a novel LBG algorithm for image compression in wavelet transform domain. The performance of the algorithm is evaluated by using standard 512×512 benchmark still images and the results compared to the traditional well-known JPEG standard. The important metric of time and Peak Signal to Noise Ratio are used to evaluate the novel algorithm. The results show that the strength of the algorithm lies in the speed of operation as it is much faster than the JPEG standard. It has speed advantages of almost 41% over the JPEG standard. Further more, the accuracy of the prediction of the Novel algorithm is better than that of the JPEG standards.
in Cells Lacking Mitochondrial DNA Apoptosis-associated Derangement of Mitochondrial Function

U937 cells lacking mitochondria! DNA (pÂ°cells) are auxotrophic for undine and pyruvate, hypersensitive to hypoglycÃ©mie conditions, and resistant to antimycin A-induced apoptosis. In spite of their obvious metabolic defects, pÂ°cells possess a normal mitochondria! transmembrane potential, as well as a near-normal capacity to generate Superoxide aniÃ3n after menadione treatment. Similarly to p1 controls, pÂ°cells undergo apoptosis in response to tumor necrosis factor-a plus cycloheximide. Detailed comparison of the apoptotic process in p+ and p" cells reveals essentially the same sequence of events. In response to tumor necrosis factor/cycloheximide, cells first lose their mitochondria! transmembrane potential (Ai//ml and then manifest late apoptotic alterations, such as generation of reactive oxygen species and DNA fragmentation. Experi ments involving isolated mitochondria from p* and pÂ°cells confirm that ;< mitochondria can be induced to undergo permeability transition, a process thought to account for the pre-apoptotic Ai//,,, disruption in cells. Like p ' mitochondria, pÂ°mitochondria contain a pre-formed soluble factor that is capable of inducing eliminatili condensation in isolated nuclei in vitro. This factor is released from mitochondria upon induction of permeability transition by calcium or the specific ligand of the adenine nucleotide translocator atractyloside. In conclusion, it appears that all structures involved in the maintenance and pre-apoptotic disruption of the Ai//,,,, as well as a mitochondria! apoptotic factor(s), are present in pÂ° cells and thus are controlled by the nuclear rather than by the mitochon dria! genome. These findings underline the contribution of mitochondria to the apoptotic process.
A Novel Cluster Formation Approach Based on The ILP for Wireless Sensor Networks

Wireless sensor networks (WSNs) have been widely studied and usefully employed in many applications. WSNs consist of small battery powered devices with limited energy resource. Once deployed, the tiny sensor nodes are usually inaccessible to the users. Hence, power efficiency is an important design goal that needs to be enhanced in order to prolong the effective lifetime of a network with a limited power supply. Organizing wireless sensor networks into clusters enables the efficient utilization of the limited energy resources of the deployed sensor nodes. In this paper, a novel cluster formation algorithm based on the ILP is presented according to considering the energy consumption as an optimization parameter while clustering is imperative. Then, we model this problem using integer linear programming (ILP) method and give the solution to it. At last, we make a comparison between the novel algorithm and the cluster formation method using in LEACH
Global Small Solution to the 2D MHD System with a Velocity Damping Term

This paper studies the global well-posedness of the incompressible magnetohydrody- namic (MHD) system with a velocity damping term. We establish the global existence and unique- ness of smooth solutions when the initial data is close to an equilibrium state. In addition, explicit large-time decay rates for various Sobolev norms of the solutions are also given.
Reliable multi method assessment of metacognition use in chemistry problem solving

Metacognition is fundamental in achieving understanding of chemistry and developing of problem solving skills. This paper describes an across-method-and-time instrument designed to assess the use of metacognition in chemistry problem solving. This multi method instrument combines a self report, namely the Metacognitive Activities Inventory (MCA-I), with a concurrent automated online instrument, Interactive MultiMedia Exercises (IMMEX). IMMEX presents participants with ill defined problems and collects students actions as they navigate the problem space. Artificial neural networks and hidden Markov modeling applied to the data collected with IMMEX produce two assessment parameters: the strategy state, which is related to the metacognitive qualities of the solution path employed, and the ability which is a measure of the problem difficulty students can properly handle. The ability values are significantly correlated with the MCA-I scores, and groups of students who performed using more metacognitive state strategies had significantly higher mean MCA-I values than those using fewer metacognitive strategies. This evidence is indicative of convergence between the methods. This instrument can be used diagnostically to guide the implementation of interventions to promote the use of metacognition; it takes little instructional time, is readily available and allows for the assessment of large cohorts.
Usability Metric Framework for Mobile Phone Application

Measuring usability is an essential task to ensure the application is accurate, has sufficient in speed and to ensure the safety of the user from strain injury as well. The increasing number of mobile phone users means that many businesses have deployed mobile applications to gain competitive advantage. Literature on how to measure usability is limited in the area of mobile phone applications. Recent technology like GPS receiver embedded into mobile phone creates new challenges to researchers. This paper attempts to review existing metrics for desktop computing and subsequently develop a conceptual model to evaluate mobile phone application. The model will consist of usability metric to evaluate mobile application.
A Catalog of Regulatory Sequences for Trait Gene for the Genome Editing of Wheat

Wheat has been cultivated for 10000 years and ever since the origin of hexaploid wheat it has been exempt from natural selection. Instead, it was under the constant selective pressure of human agriculture from harvest to sowing during every year, producing a vast array of varieties. Wheat has been adopted globally, accumulating variation for genes involved in yield traits, environmental adaptation and resistance. However, one small but important part of the wheat genome has hardly changed: the regulatory regions of both the x- and y-type high molecular weight glutenin subunit (HMW-GS) genes, which are alone responsible for approximately 12% of the grain protein content. The phylogeny of the HMW-GS regulatory regions of the Triticeae demonstrates that a genetic bottleneck may have led to its decreased diversity during domestication and the subsequent cultivation. It has also highlighted the fact that the wild relatives of wheat may offer an unexploited genetic resource for the regulatory region of these genes. Significant research efforts have been made in the public sector and by international agencies, using wild crosses to exploit the available genetic variation, and as a result synthetic hexaploids are now being utilized by a number of breeding companies. However, a newly emerging tool of genome editing provides significantly improved efficiency in exploiting the natural variation in HMW-GS genes and incorporating this into elite cultivars and breeding lines. Recent advancement in the understanding of the regulation of these genes underlines the needs for an overview of the regulatory elements for genome editing purposes.
Systematics in the X-ray cluster mass estimators

We examine the systematics affecting the X-ray mass estimators applied to a set of five galaxy clusters resolved at high resolution in hydrodynamic simulations, including cooling, star formation and feedback processes. These simulated objects are processed through the X-ray Map Simulator, X-MAS, to provide Chandra-like long exposures that are analysed to reconstruct the gas temperature, density and mass profiles used as input. These clusters have different dynamic state: we consider a hot cluster with temperature T = 11.4 keV, a perturbed cluster with T = 3.9 keV, a merging object with T = 3.6 keV, and two relaxed systems with T = 3.3 keV and T = 2.7 keV, respectively. These systems are located at z = 0.175 so that their emission fits within the Chandra ACIS-S3 chip between 0.6 and 1.2 R-500. We find that the mass profile obtained via a direct application of the hydrostatic equilibrium ( HE) equation is dependent upon the measured temperature profile. An irregular radial distribution of the temperature values, with associated large errors, induces a significant scatter on the reconstructed mass measurements. At R-2500, the actual mass is recovered within 1 sigma, although we notice this estimator shows high statistical errors due to high level of Chandra background. Instead, the poorness of the beta-model in describing the gas density profile makes the evaluated masses to be underestimated by similar to 40 per cent with respect to the true mass, both with an isothermal and a polytropic temperature profile. We also test ways to recover the mass by adopting an analytic mass model, such as those proposed by Nvarro, Frenk & White and Rasia, Tormen & Moscardini, and fitting the temperature profile expected from the HE equation to the observed one. We conclude that the methods of the HE equation and those of the analytic fits provide a more robust mass estimation than the ones based on the beta-model. In the present work, the main limitation for a precise mass reconstruction is to ascribe to the relatively high level of the background chosen to reproduce the Chandra one. After artificially reducing the total background by a factor of 100, we find that the estimated mass significantly underestimates the true mass profiles. This is manly due (i) to the neglected contribution of the gas bulk motions to the total energy budget and (ii) to the bias towards lower values of the X-ray temperature measurements because of the complex thermal structure of the emitting plasma.
Mobile Sensing to Model the Evolution of Political Opinions

Exposure and adoption of opinions in social networks are important questions in education, business, and government. We describe a novel application of ubiquitous computing based on using mobile phone sensors to measure and model the face-to-face interactions and subsequent opinion changes of undergraduates during the US presidential election campaign. We find that self-reported political discussants have characteristic interaction patterns and can be predicted from sensor data. Mobile features can be used to estimate unique individual exposure to different opinions, and help discover surprising patterns of dynamic homophily related to external political events, such as election debates and election day (4th Nov 2008). To our knowledge, this is the first time such dynamic homophily effects have been measured. Using sensor features and estimated exposure and past opinions, it is possible to predict future opinions for individuals (R ̃0.8, p ̃0.001), and measured exposure increases explained variance by up to 30% over that of survey responses of past opinions alone.
Homotopy groups of the moduli space of metrics of positive scalar curvature

We show by explicit examples that in many degrees in a stable range the homotopy groups of the moduli spaces of Riemannian metrics of positive scalar curvature on closed smooth manifolds can be non-trivial. This is achieved by further developing and then applying a family version of the surgery construction of Gromov–Lawson to certain nonlinear smooth sphere bundles constructed by Hatcher.
Soft resampling for improved information retention in particle filtering

The reweighing process of particle filtering can result in very large variance of particle weights; a problem known as degeneracy. The usual solution to this is an intermediary resampling step in which particles with lower weights are replaced by copies of those with large weights. This resampling inevitably results in loss of the information contained in those particles of low weights. Most of the existing stochastic and deterministic resampling schemes cause further loss of information because all the resampled particles have equal weights. These current techniques are what we would call, “hard resamplers,” and they impede the accumulation of information over many successive observations, which affects the detection of very covert targets. This paper presents two variants of a soft and deterministic resampling procedure that retains information contained in the weights over multiple observations. We demonstrate their effectiveness using a track-before-detect application.
Fonctionnalité de la signalisation en aval des récepteurs HER : implication dans la réponse cellulaire et tumorale aux thérapies ciblées

Les therapies ciblees dirigees contre les recepteurs de la famille des HER representent un progres majeur en cancerologie. Leur efficacite repose sur leur capacite a inhiber la signalisation oncogenique notamment recrutant les voies RAS/RAF/MAPK et PI3K/AKT. Independamment de l'expression de la cible moleculaire, l'activite des therapies ciblees est tributaire de la presence dans le tissu tumoral d'anomalies genetiques capables de perturber la signalisation cellulaire tumorale en aval des recepteurs. Notre travail a consiste a evaluer l'interet de l'evaluation de la fonctionnalite des voies de signalisation par analyse multiplexe des niveaux d'expression des formes phosphorylees des principales kinases intracellulaires en aval des recepteurs HER. La preuve de concept a ete tout d'abord apportee sur des modeles cellulaires genetiquement modifies, en montrant l'impact d'anomalies genetiques tumorales sur la fonctionnalite des voies de signalisation RAS/RAF/MAPK et PI3K/AKT et sur la reponse au cetuximab. Dans la seconde partie de ce travail, apres validation des techniques utilisees en situation clinique, nous avons montre la pertinence d'une approche de biologie integrative combinant analyse de genetique moleculaire et analyses fonctionnelles avec analyse en composante principale. Nos resultats, obtenus au cours d'une etude clinique retrospective dans les cancers colorectaux metastatiques, suggerent que l'utilisation des donnees issues de l'evaluation de la fonctionnalite des voies de signalisation en aval des recepteurs HER, pourraient a terme trouver des applications en qualite de marqueurs predictifs de reponse clinique aux therapies ciblees anti-HER
Approximating Posterior Distributions in Ensemble Forecasting

Ensemble forecasting is used in numerical weather prediction to give an improved estimate of the atmospheric state and to improve measures of forecast accuracy. While the method is effective, there are some fundamental issues in interpreting the ensemble as a statistically valid representation of uncertainty in the state of the atmosphere. Coupled with this interpretation is the difficulty in the specification of large, complex covariance matrices used to combine a numerical forecast with observed data. We approach this problem by representing the prior distribution as a mixture of Gaussian distributions, then generate an ensemble from the posterior and use this ensemble to construct a kernel approximation to the posterior distribution.
Coronary Slow Flow is Associated with Depression and Anxiety.

BACKGROUND There is an established relationship between depression/anxiety disorders and cardiovascular morbidity and mortality which has been previously documented. However, there has been no study evaluating coronary slow flow in association with depression and anxiety. METHODS AND RESULTS A total of consecutive 90 patients were included in the study. All patients completed scoring scales for depression [Hamilton Rating Scale for Depression (HAMD)] and anxiety (STAI-1, State anxiety subscale of State-Trait Anxiety Inventory; STAI-2, Trait anxiety subscale of State-Trait Anxiety Inventory). Thereafter, they underwent selective coronary angiography and 2 groups were formed: coronary slow flow (n = 42), and normal coronary flow (n = 48). The two groups had comparable baseline characteristics. However, significant differences were found between coronary slow flow and normal coronary flow groups regarding depression (13.1 ± 8.2 and 6.9 ± 6.7, p < 0.001 for HAMD, respectively) and anxiety (46.2 ± 15.0 vs. 32.6 ± 9.9, p < 0.001 for STAI-1 and 51.0 ± 16.7 vs. 43.0 ± 10.7, p = 0.009 for STAI-2, respectively) scores. There were also significant positive correlations between depression/anxiety scores and TIMI frame counts of all major epicardial coronary arteries. In addition, after adjustment for smoking, hypertension, scoring scales, and the presence of depressive mood, all scoring scales and depressive mood were found to be independent risk factors for coronary slow flow in multivariable logistic regression analysis. CONCLUSIONS Significant association was found among coronary slow flow, depression/anxiety scores and depressive mood. KEY WORDS Anxiety; Coronary slow flow; Depression; Scale.
Conditional privacy preserving security protocol for NFC applications

In recent years, various mobile terminals equipped with NFC (Near Field Communication) have been released. The combination of NFC with smart devices has led to widening the utilization range of NFC. It is expected to replace credit cards in electronic payment, especially. In this regard, security issues need to be addressed to vitalize NFC electronic payment. The NFC security standards currently being applied require the use of user's public key at a fixed value in the process of key agreement. The relevance of the message occurs in the fixed elements such as the public key of NFC. An attacker can create a profile based on user's public key by collecting the associated messages. Through the created profile, users can be exposed and their privacy can be compromised. In this paper, we propose conditional privacy protection methods based on pseudonyms to solve these problems. In addition, PDU (Protocol Data Unit) for conditional privacy is defined. Users can inform the other party that they will communicate according to the protocol proposed in this paper by sending the conditional privacy preserved PDU through NFC terminals. The proposed method succeeds in minimizing the update cost and computation overhead by taking advantage of the physical characteristics of NFC1.
User reviews matter! Tracking crowdsourced reviews to support evolution of successful apps

Nowadays software applications, and especially mobile apps, undergo frequent release updates through app stores. After installing/updating apps, users can post reviews and provide ratings, expressing their level of satisfaction with apps, and possibly pointing out bugs or desired features. In this paper we show-by performing a study on 100 Android apps-how developers addressing user reviews increase their app's success in terms of ratings. Specifically, we devise an approach, named CRISTAL, for tracing informative crowd reviews onto source code changes, and for monitoring the extent to which developers accommodate crowd requests and follow-up user reactions as reflected in their ratings. The results indicate that developers implementing user reviews are rewarded in terms of ratings. This poses the need for specialized recommendation systems aimed at analyzing informative crowd reviews and prioritizing feedback to be satisfied in order to increase the apps success.
A scale transform based method for rhythmic similarity of music

This paper introduces scale transforms to measure rhythmic similarity between two musical pieces. The rhythm of a piece of music is described by the scale transform magnitude, computed by transforming the sample autocorrelation of its onset strength signal to the scale domain. Then, two pieces can be compared without the impact of tempo differences by using simple distances between these descriptors like the cosine distance. A widely used dance music dataset has been chosen for proof of concept. On this data set, the proposed method based on scale transform achieves classification results as high as other state of the art approaches. On a second data set, which is characterized by much larger intra-class tempo variance, the scale transform based measure improves classification compared to previously presented measures by 41%.