Miracle-dz/UniFAR-FTUs huggingface dataset:
The concentration of circulating corticotropin-releasing hormone mRNA in maternal plasma is increased in preeclampsia.

BACKGROUND Increased fetal DNA in maternal plasma/serum has been reported in pregnancies complicated by preeclampsia. We hypothesize that fetal RNA may also be increased in maternal plasma in preeclampsia. METHODS We developed a real-time quantitative reverse transcription-PCR assay to measure the concentration of the mRNA of the corticotropin-releasing hormone (CRH) locus. Peripheral blood samples were obtained from healthy pregnant women both before and 2 h after delivery. Peripheral blood samples were also obtained from women suffering from preeclampsia and controls matched for gestational age. Plasma was harvested from these samples, and RNA was extracted. Plasma RNA was subjected to analysis by the reverse transcription-PCR assay. RESULTS CRH mRNA was detected in the plasma of 10 healthy pregnant women in the third trimester. CRH mRNA was found to be cleared very rapidly after cesarean section, with no detectable signal by 2 h postpartum. Plasma CRH mRNA concentrations were 1070 and 102 copies/mL, respectively, in 12 preeclamptic women and 10 healthy pregnant women matched for gestational age (Mann-Whitney test, P <0.001). CONCLUSION Plasma CRH mRNA represents a new molecular marker for preeclampsia. Maternal plasma RNA is gender- and polymorphism-independent and may allow noninvasive gene-expression profiling of an unborn fetus.
Molecular etiology of an indolent lymphoproliferative disorder determined by whole-genome sequencing

In an attempt to assess potential treatment options, whole-genome and transcriptome sequencing were performed on a patient with an unclassifiable small lymphoproliferative disorder. Variants from genome sequencing were prioritized using a combination of comparative variant distributions in a spectrum of lymphomas, and meta-analyses of gene expression profiling. In this patient, the molecular variants that we believe to be most relevant to the disease presentation most strongly resemble a diffuse large B-cell lymphoma (DLBCL), whereas the gene expression data are most consistent with a low-grade chronic lymphocytic leukemia (CLL). The variant of greatest interest was a predicted NOTCH2-truncating mutation, which has been recently reported in various lymphomas.
On extreme daily precipitation totals at Athens, Greece

Abstract. The paper studies changes in daily precipitation records at the National Observatory, Athens, during the period 1891–2004. This is the longest available time series of precipitation for Greece. The results show that both the shape and scale parameter of a fitted two parameter gamma distribution for the last two decades do show a significant difference of these parameters, when compared to any previous period from the 1890s through the 1970s. Also important changes are observed in daily precipitation totals exceeding various thresholds such as 10, 20, 30 and 50 mm. More specifically, a negative trend in the number of wet days (remarkable after 1968) and a positive trend in extreme daily precipitation are evident. The changes of heavy and extreme precipitation events in this part of SE Europe have significant environmental consequences which cause considerable damage and loss of life.
Multiclass Noisy Image Classification Based on Optimal Threshold and Neighboring Window Denoising

Classification of multi class images is very enviable for different recognition. This is affected by many factors such as noise, blur, low illumination, complex background, occlusion etc. Noise is one of the major factors causing degradation of the classification performance. This paper propose an efficient method for classification of multi class object images which are corrupted by Gaussian noise based on wavelet feature extraction. This work shows robustness of proposed method over the spatial domain denoising and feature extraction for classification.
Tagging Ontology – Towards a Common Ontology for Folksonomies

Collaborative tagging represents the process by which many users describe resources (e.g. web pages or photos) with free-form keywords (tags). The combination of all users tags for a certain resource reflects the common understanding of that resource from the users’ point of view, which is called “folksonomy”. Today there are many systems making use of folksonomies, most notably del.icio. us and flickr. These systems (also referred to as “social software”) allow the users to publish their taggings for the benefit of the community, mostly via RSS feeds. The problem is, that there is no common agreement about the semantics of a tagging, and thus every system uses a different representation, hindering interoperability between systems and the automated processing by software agents. In this paper we use Semantic Web technologies to develop an ontology for folksonomies, making interoperability and automated processing feasible. In order to validate our ontology we extract sample tagging data from del.icio. us and feed it into our ontology. Finally, we run some SPARQL queries against this data to prove that the folksonomic information can easily be accessed within our ontology.
Application of Nonparametric Techniques to Collaborative Recommender Systems

The introduction of the World Wide Web dramatically impacted our fundamental notion of information sharing, providing unparalleled awareness of both the power of information access and the penalty of information overload. Today’s research on Semantic Web techniques focuses on the next step, a Service Oriented Architecture supporting automated sharing of services as well as data. Personalized service/source recommendation tools, utilizing user preference data, would be extremely valuable in tailoring information access to the user. Much can be learned from the Recommender community about incorporating preference data into the retrieval process. However, it is critical that rigorous statistical techniques be maintained in combining results across data and service sources that are not under the control of a single developer. In this paper we explore the extension of nonparametric techniques to the development of Collaborative Recommenders and its impact on establishing a generalized recommendation service within a Service Oriented Architecture.
Production, Manufacturing and Logistics Hierarchical coordination mechanisms within the supply chain

The paper analyses operational coordination mechanisms between a producer and a supplier within a supply chain having private local information. For a make to order production setting the coordination is achieved through the combined use of a task-oriented and a control-oriented type of instrument. The task-oriented instrument describes the producers procurement policy for components whereas the control-oriented instrument is made up by penalty costs for non-correct delivery. In using both of these instruments various coordination schemes are employed in making use of the theory of hierarchical planning. Though it is assumed that producer and supplier possess some private information they are not taken to behave antagonistically. The question, which information should be disclosed, is of central importance for the overall performance of the supply chain and is the main focus of an extensive quantitative analysis which finally is used to give recommendations for the design of a supply contract. 2003 Elsevier B.V. All rights reserved.
Medical Visualization with New Generation Spatial 3D Displays

In this paper the capabilities of a modern spatial 3D display are exploited for m visualization tasks. The system gives multiple viewers the illusion of seeing virtual objects floating at fixed physical locations. The usage of this kind of display in conjunction with 3D visualization techniques helps disambig uating complex images, so it is proven to be a real advantage for immediate understanding and visualizatio n of medical data. We demonstrate this by reporting on some preliminary test cases of direct volume rendering techniques (Maximum Intensity Projection and X Ray simulation), as well as an example of a collaborative medical diag nostic application for analysis of Abdominal Aortic Aneurysms.
MPaaS : Monitoring values Prediction as a Service for energy consumption optimization purpose

The Wireless Sensor Networks (WSNs) deployment introduces many issues and challenges mainly in terms of energy independence. In this context, we adopted a self-adaptation strategy composed of four steps (Monitor, Analyze, Plan and Execute) to manage Quality of Service (QoS) [1]. This paper focuses on the first step which consists in monitoring and sending QoS values such as the value of power remaining in the battery of each sensor. We notice that the transmission process is very expensive in terms of energy and reduces the battery lifetime. In this work, we propose a probabilistic approach that estimates a part of these QoS monitoring values and therefore economizes their transmission energy and extends the sensor battery life. Our approach is based on the hidden Markov chain and the fuzzy logic and composed of two steps: (i) learning which allows apprehending the WSNs behavior and (ii) predicting which estimates QoS monitoring values. A WSN application deployed in a datacenter is studied as an illustration. The carried out experiments over AZEM WSN simulator show its feasibility and efficiency. Keywords— Wireless sensor network; probabilistic approach, hidden Markov chain; value of monitoring; prediction.
Is a General Women's Health Promotion Program as Effective as an HIV-Intensive Prevention Program in Reducing HIV Risk among Hispanic Women?

Objective. This study aimed to assess whether participants in an HIV-intensive prevention program and participants in a general women's health promotion program reported greater HIV risk-reduction than participants in a wait-list control group immediately following program participation and at three-month follow-up. Methods. The authors studied 162 Hispanic women ages 18 to 35 years, most of them immigrants. Three-fourths of the sample (74%) reported earning less than $800 a month, 29% did not have a high school degree, and 90% had children. Data were gathered through surveys at baseline, at intervention completion, and at three-month follow-up. Information was collected on sociodemographics, HIV risk factors, and risk behaviors. Crude and adjusted (for demographics and dose) logistic regression analyses were used to assess program effects on participants' risk reduction. Results. Crude logistic regression analyses reveal that both programs resulted in increased condom use at post-test and follow-up. Only participants in the HIV-intensive prevention program reported increased safer sex negotiation at post-test and follow-up, however, and only participants in the women's health promotion program reported increased HIV testing at post-test. Conclusion. Both interventions increased condom use. The HIV-intensive prevention program appeared to be more effective in promoting safer sex negotiation, and the women's health promotion program appeared more effective in promoting HIV testing. The findings suggest that both approaches may be viable ways to package HIV prevention for short-term behavior change in this population.
Mathematical foundation of Information Field Dynamics (revised version)

I assure the single handed composition of this master's thesis only supported by declared resources. Hierbei nimmt er zu jedem Zeitpunkt t zwischen der Startzeit und der Zeit T , zu welcher die Daten simuliert werden sollen, eine lineare Relation zwischen den Daten d(t) und dem Signal φ(t) durch einen Operator R(t) an. Messabweichungen werden durch einen Zufallsvektor n(t) dargestellt. Auch das Signal wird zu jedem Zeitpunkt als Zufallsvek-tor interpretiert, dessen Wahrscheinlichkeitsverteilung diejenigen Signale gewichtet, die möglicherweise zu den gemessenen Daten geführt haben. Die Daten können so als eine Realisierung des Zufallsvektors R(t)φ(t) + n(t) aufgefasst werden. IFD partitioniert das Zeitintervall (0, T ] durch ((t i , t i+1 ]) 2 N i=0 und simuliert induktiv für jedes i aus den Daten d(t i) des vorherigen Zeitschrittes die Daten d(t i+1), bis d(T) berech-net ist. Dabei wird die bedingte Wahrscheinlichkeitsdichte P φ(t i)|d(t i) aus Annahmenüber P φ(t i) und P n(t i) berechnet und gemäß der linearisierten Evolutionsgleichung weiteren-twickelt. Die so entstehende Dichte P φ(t i)|d(t i+1) wird dann mit der bedingten Wahrschein-lichkeitsdichte P φ(t i+1)|d(t i+1) abgeglichen. Dies geschieht durch Minimierung der relativen Entropie zwischen den Dichten bezüglich d(t i+1) und legt so den simulierten Datenvektor für den Zeitpunkt t i+1 fest. Dabei entsteht d(t i+1) durch Matrixmultiplikation aus d(t i). Es ergibt sich ein iterativer Algorithmus zur Berechnung von d(T) aus d(0). In dieser Arbeit wird der Ansatz in [1] auf mathematische Weise präzisiert und einzelne Teile werden korrigiert. Approximationsschritte werden dabei durch das Verschwinden des informationstechnischen Fehlers im Grenzfall δt = T 2 N → 0 gerechtfertigt. Am Beispiel des eindimensionalen Klein-Gordon Feldes, periodischüber [0, 2π), wird die Simulation mittels IFD illustriert. Dabei ensteht durch den Grenzübergang δt → 0 eine gewöhnliche Differentialgleichung für die Daten, deren Lösung eine direkte Simulation von d(T) durch d(0) durch Matrixmultiplikation zulässt. Dadurch kann der iterative Algorithmus von IFD durch die Berechnung einer einzelnen Matrix weiter vereinfacht werden.
An Improved Delphi Method for Machinability Evaluation and Examination in Process Planning

Machinability evaluation and examination is fundamental for process planning¿while an effective weight method is one of the primary concerns of machinability evaluation and examination in process planning. In this paper, a new improved approach for calculating the weights of extracted indices in machinability evaluation and examination in process planning is proposed based on the conventional Delphi method [1]. The proposed approach is the statistical method that is applied to develop an algorithm for calculating weights of extracted machinability indices. The proposed method follows three steps: (1) extracted machinability indices are sequenced according to importance by domain experts; (2) the statistical values are obtained from the evaluation data given by these experts; (3) the weights of extracted machinability indices are calculated according to this approach. The new method in the paper provides one solution to the existing evaluation system. An application case is used to illustrate the process of calculation of weights of extracted machinability indices in machinability evaluation and examination in process planning.
Mesenchymal Stem Cells in Immune-Mediated Bone Marrow Failure Syndromes

Immune-mediated bone marrow failure syndromes (BMFS) are characterized by ineffective marrow haemopoiesis and subsequent peripheral cytopenias. Ineffective haemopoiesis is the result of a complex marrow deregulation including genetic, epigenetic, and immune-mediated alterations in haemopoietic stem/progenitor cells, as well as abnormal haemopoietic-to-stromal cell interactions, with abnormal release of haemopoietic growth factors, chemokines, and inhibitors. Mesenchymal stem/stromal cells (MSCs) and their progeny (i.e., osteoblasts, adipocytes, and reticular cells) are considered as key cellular components of the bone marrow haemopoietic niche. MSCs may interfere with haemopoietic as well as immune regulation. Evidence suggests that bone marrow MSCs may be involved in immune-mediated BMFS underlying pathophysiology, harboring either native abnormalities and/or secondary defects, caused by exposure to activated marrow components. This review summarizes previous as well as more recent information related to the biologic/functional characteristics of bone marrow MSCs in myelodysplastic syndromes, acquired aplastic anemia, and chronic idiopathic neutropenia.
Learning to generate summary as structured output

We propose to use a structured output learning for summary generation based on the maximum coverage problem. Our method learns a function that outputs the benefit of each conceptual unit in the document cluster for this summarization model. In the training, we iteratively run a greedy algorithm that accepts items (sentences) with different costs (length) in order to generate a summary within the given maximum length limit. We empirically show that the structured output learning works well for this task and also examine its behavior in several dierent settings.
Preemptively scheduling hard-real-time sporadic tasks on one processor

Consideration is given to the preemptive scheduling of hard-real-time sporadic task systems on one processor. The authors first give necessary and sufficient conditions for a sporadic task system to be feasible (i.e., schedulable). The conditions cannot, in general, be tested efficiently (unless P=NP). They do, however, lead to a feasibility test that runs in efficient pseudo-polynomial time for a very large percentage of sporadic task systems. <<ETX>>
Melanogenic Effects Melanocortin Receptors without Eliciting Harness the Proresolving Properties of Biased Agonism as a Novel Strategy To

There is a need for novel approaches to control pathologies with overexuberant inﬂammatory reactions. Targeting melanocortin (MC) receptors represents a promising therapy for obesity and chronic inﬂammation, but lack of selectivity and safety concerns limit development. A new way to increase selectivity of biological effects entails the identiﬁcation of biased agonists. In this study, we characterize the small molecule AP1189 as a biased agonist at receptors MC 1 and MC 3 . Although not provoking canonical cAMP generation, AP1189 addition to MC 1 or MC 3 , but not empty vector, transfected HEK293 cells caused ERK1/2 phosphorylation, a signaling responsible for the proefferocytic effect evoked in mouse primary macrophages. Added to macrophage cultures, AP1189 reduced cytokine release, an effect reliant on both MC 1 and MC 3 as evident from the use of Mc1r 2 / 2 and Mc3r 2 / 2 macrophages. No melanogenesis was induced by AP1189 in B16-F10 melanocytes. In vivo, oral AP1189 elicited anti-inﬂammatory actions in peritonitis and, upon administration at the peak of inﬂammation, accelerated the resolution phase by ∼ 3-fold. Finally, given the clinical efﬁcacy of adrenocorticotropin in joint diseases, AP1189 was tested in experimental inﬂammatory arthritis, where this biased agonist afforded signiﬁcant reduction of macroscopic and histological parameters of joint disruption. These proof-of-concept analyses with AP1189, an active oral anti-inﬂammatory and resolution-promoting compound, indicate that biased agonism at MC receptors is an innovative, viable approach to yield novel anti-inﬂammatory molecules endowed with a more favorable safety proﬁle.
Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis

The detection of recorded epileptic seizure activity in EEG segments is crucial for the localization and classification of epileptic seizures. However, since seizure evolution is typically a dynamic and nonstationary process and the signals are composed of multiple frequencies, visual and conventional frequency-based methods have limited application. In this paper, we demonstrate the suitability of the time-frequency ( t-f) analysis to classify EEG segments for epileptic seizures, and we compare several methods for t- f analysis of EEGs. Short-time Fourier transform and several t-f distributions are used to calculate the power spectrum density (PSD) of each segment. The analysis is performed in three stages: 1) t-f analysis and calculation of the PSD of each EEG segment; 2) feature extraction, measuring the signal segment fractional energy on specific t-f windows; and 3) classification of the EEG segment (existence of epileptic seizure or not), using artificial neural networks. The methods are evaluated using three classification problems obtained from a benchmark EEG dataset, and qualitative and quantitative results are presented.
A Model-Based Customer Inference Engine

In complex and frequently changing product domains, customers need qualified consultation services that allow them to make well-informed purchasing decisions without requiring excessive technical knowledge about the product domain. In this paper we present an intuitive customer metamodel with an associated inference engine which can be integrated into conversational recommender systems to provide comfortable reasoning about customer needs. The inferred knowledge can be used to manage the recommendation dialogue and to map non-technical customer statements into preferences for technical attributes.
Merlot Journal of Online Learning and Teaching Switching Gears: Moving from E-learning to M-learning

This paper examines institutional practice regarding integration of mobile technologies into electronic teaching that has previously depended on computers alone. More specifically, this study explores challenges, opportunities and constraints reflected in efforts to transition from reliance on formal learning management systems for course development and delivery toward the infusion of media targeted to students' mobile devices. Based on three e-course case histories, this paper illustrates how the participants' university is addressing the transformational challenges found in the study and examines instructor perceptions about University support. The researchers conducted two in-depth semi-structured interviews which took place at different times to reflect the longitudinal experiences of the three participants over time. Main findings of the research suggest that institutional faculty need technical support, training and professional development to understand not only how to work with mobile devices but also the means to achieve clear instructional purposes with them.
Transient caloric restriction in early adulthood hastens disease endpoint in male, but not female, Cu/Zn‐SOD mutant G93A mice

Long‐term caloric restriction (CR) prolongs the lifespan in healthy insects, rodents, and nonhuman primates. We previously reported that long‐term CR improves motor performance but hastens clinical onset of disease in an animal model of amyotrophic lateral sclerosis (G93A mice). G93A mice overexpress the mutant human Cu/Zn‐SOD gene and show progressive lower motor neuron weakness and increased oxidative stress. To study short‐term (15 days) CR in the same animal model, we investigated the effect of transient caloric restriction (TCR) on paw grip endurance, clinical onset, disease progression (time from clinical onset to endpoint), and lifespan. Starting at age 40 days, 32 separately caged G93A mice were randomly divided into two groups: ad libitum (AL, n = 17; 10 females, 7 males) and TCR (n = 15; 6 females, 9 males) with a diet equal to 60% of AL. When the TCR mice lost 30% of their weight they were offered food AL until endpoint, otherwise all TCR mice were provided food AL from age 55 days until endpoint (i.e., range of TCR = 13–15 days). Paw grip endurance started to decrease significantly at age 96 days compared with baseline values for all the groups. TCR males reached clinical onset 5 days sooner than TCR females. Disease progression was 8 days faster in TCR mice than AL mice and 6 days faster in male mice than female mice. The probability of survival was significantly different between the groups, with the TCR males having a faster rate of reaching endpoint than TCR females, AL males, and AL females. We conclude that TCR hastens clinical onset of disease and shortens the lifespan in male, but not female, G93A mice. Moreover, TCR hastens progress of disease but has no effect on paw grip endurance. The female sex is protective against the detrimental effects of short‐term CR in G93A mice. Assuming we can extrapolate these results to humans, short‐term CR should be avoided in patients with amyotrophic lateral sclerosis, especially men. Muscle Nerve, 2006