Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between preeclampsia umbilical blood flow and perinatal outcome

Background: Doppler indices of the umbilical artery are used as indicator of fetal well being that permit early detection of fetal compromise and avoid delaying in the management. Study design: A prospective multiple logistic regression analysis studies. Objective: To compare Doppler parameters of umbilical artery including pulsatility index (PI) and resistance index (RI) and systolic diastolic ratio [S/D] in patients suffering from preeclampsia with those having normal pregnancies and to evaluate the diagnostic characteristics of these parameters in fetal outcome. Materials and Methods: One hundred singleton preeclamptic women at their term (50 with mild & 50 with severe preeclampsia) and 50 women with normal pregnancy were included in the study & subjected to doppler study of the umbilical artery where resistance index , pulsatility index & systolic diastolic ratio were measured using doppler ultrasound ( Acuson x3oo) at Al-Elwiya Maternity Teaching Hospital during the period from May 2013 to July 2014. Fetal outcome (fetal weight, Apgar score and Neonatal Care Unit admission NCU) were compared in the two groups and diagnostic characteristics of the Doppler indices were determined. The data are arranged on questionnaire papers and then subjected to statistical analysis. Results: Mean of pulsatility index (1.32), resistance index (0.77) and systolic diastolic ratio (3.38) in preeclamptic patients were significantly higher than normal group (PI 0.97, RI 0.64&S\D ratio 2.68), elevated Doppler indices were found to be associated with worse fetal outcome (low birth weight, Apgar score and higher NCU admission). Besides, those with severe preeclampsia showed significantly higher values of (PI 1.52, RI 0.83& S\D ratio 3.86) compared to those with mild preeclampsia (PI 1.24, RI 0.74 & S\D ratio 2.90). For PI, the cut-off of ≥0.98 yielded the highest sensitivity and specificity. Also, RI of 0.64 acquired a sensitivity of 100% and specificity of 44% and same result for S/D ratio. Conclusion: Umbilical artery pulsatility index, resistance index and S/D ratio increase in preeclampsia and these changes tend to be greater in severe preeclampsia and with worse fetal outcome (low birth weight, Apgar score and higher NCU admission) the cut-off values were 0.98 for PI and/or 0.64 for RI.
Joint depth and alpha matte optimization via fusion of stereo and time-of-flight sensor

We present a new approach to iteratively estimate both high-quality depth map and alpha matte from a single image or a video sequence. Scene depth, which is invariant to illumination changes, color similarity and motion ambiguity, provides a natural and robust cue for foreground/ background segmentation - a prerequisite for matting. The image mattes, on the other hand, encode rich information near boundaries where either passive or active sensing method performs poorly. We develop a method to combine the complementary nature of scene depth and alpha matte to mutually enhance their qualities. We formulate depth inference as a global optimization problem where information from passive stereo, active range sensor and matte is merged. The depth map is used in turn to enhance the matting. In addition, we extend this approach to video matting by incorporating temporal coherence, which reduces flickering in the composite video. We show that these techniques lead to improved accuracy and robustness for both static and dynamic scenes.
Cosmological tachyon condensation

We consider the prospects for dark matter/energy unification in k-essence type cosmologies. General mappings are established between the k-essence scalar field, the hydrodynamic and braneworld descriptions. We develop an extension of the general relativistic dust model that incorporates the effects of both pressure and the associated acoustic horizon. Applying this to a tachyon model, we show that this inhomogeneous "variable Chaplygin gas" does evolve into a mixed system containing cold dark matter like gravitational condensate in significant quantities. Our methods can be applied to any dark energy model, as well as to mixtures of dark energy and traditional dark matter.
Emissions from grassland burning in Kaziranga National Park, India – analysis from IRS-P6 AWiFS satellite remote sensing datasets

Biomass burning from vegetation fires is an important source of greenhouse gas emissions. In this study, we quantify biomass burning emissions from grasslands from the highly sensitive Kaziranga National Park, Assam, Northeast India. Most of the fires in the park are ‘controlled burning fires’ set by the park officials for management purposes. We evaluated the short-term impacts of fires and the resulting air pollution through integrating biomass burnt information from satellite remote sensing datasets. IRS-P6 Advanced Wide Field Sensor (AWiFS) data during March and April corresponding to dry season were evaluated to delineate the burnt areas. These burnt area estimates were then integrated with biomass data and emission factors for quantifying the greenhouse gas emissions. Results suggested that of the total study area of 37,822 ha, nearly 3163.282 ha has been burnt during March, 2005. Within one month, the burnt area increased to 7443.92 ha by April, i.e., from 8.36% to 19.68%. In total, biomass burning from the grasslands contributed to 29.65 Tg CO2, 1.19 Tg CO, 0.071 Tg NOx, 0.042 Tg CH4, 0.0625 Tg total non-methane hydrocarbons, 0.152 Tg of particulate matter, and 0.062 Tg of organic carbon and 0.008 Tg of black carbon during April. The importance of ‘fire’ as a management tool for maintaining the wildlife habitat has been highlighted in addition to some of the adverse affects of air pollution resulting from such management practices. The results from this study will be useful to forest officials as well as policy makers to undertake some sustainable forest management practices to maintain an ideal habitat for Kaziranga's wildlife.
Learning best wavelet packet bases for compressed sensing of classes of images : application to brain MR imaging

We study the feasibility of learning an adapted wavelet packet basis for a class of signals and subsequently using this basis for reconstruction of unseen signals of the same class. In particular, we learn an adapted basis for a set of brain MR images and then use this basis as a sparsifying transform for image reconstruction from undersampled MR data. Simulation results show that there is a signi cant improvement in sparse approximation accuracy when comparing an adapted wavelet packet basis to a wavelet basis, and a modest improvement in image reconstruction from undersampled k-space data.
Insight, part of a Special Feature on Exploring Resilience in Social-Ecological Systems Shooting the Rapids: Navigating Transitions to Adaptive Governance of Social-Ecological Systems

The case studies of Kristianstads Vattenrike, Sweden; the Northern Highlands Lake District and the Everglades in the USA; the Mae Nam Ping Basin, Thailand; and the Goulburn-Broken Catchment, Australia, were compared to assess the outcome of different actions for transforming social-ecological systems (SESs). The transformations consisted of two phases, a preparation phase and a transition phase, linked by a window of opportunity. Key leaders and shadow networks can prepare a system for change by exploring alternative system configurations and developing strategies for choosing from among possible futures. Key leaders can recognize and use or create windows of opportunity and navigate transitions toward adaptive governance. Leadership functions include the ability to span scales of governance, orchestrate networks, integrate and communicate understanding, and reconcile different problem domains. Successful transformations rely on epistemic and shadow networks to provide novel ideas and ways of governing SESs. We conclude by listing some rules of thumb" that can help build leadership and networks for successful transformations toward adaptive governance of social-ecological systems.
AÇÕES COLETIVAS: DESENVOLVIMENTO PARA ARRANJOS PRODUTIVOS INSERIDOS NO CONTEXTO DO AGRO-NEGÓCIO E TURISMO RURAL

No intuito de se tornarem competitivas, as organizacoes passaram a desenvolver fortes relacionamentos entre si. O que ocorre sao formas de governanca baseadas na cooperacao e complementaridade, como no caso dos arranjos produtivos. Quanto mais coletividade, maior a possibilidade de eficiencia das firmas. Contudo, estas formas sao complexas e necessitam ser mais exploradas. Assim, este estudo investigou quais os fatores determinantes para o desenvolvimento de acoes coletivas no arranjo produtivo do Vale dos Vinhedos, bem como o impacto dessas acoes. Para tanto, realizaram-se entrevistas com figuras-chave do objeto de estudo. Como principais resultados identificaram-se alguns fatores determinantes para o desencadeamento das acoes coletivas e ainda evidenciou-se que estas acoes tiveram um impacto significativo em termos de vantagens competitivas e desenvolvimento regional para todo o contexto do arranjo. ---------------------------------------------The organizations started to develop strong relationships to each other with the intention to became competitive. What happens are governance forms based on cooperation and complementarity, as in the case of the productive arrangements. The more collectivity, larger the possibility of efficiency of the firms. However, these forms are complex and need to be more explored. So, this study investigated which are the decisive factors for the development of collective actions in the productive arrangement of the Vineyards Valley, besides investigating the impact of those actions. For so much, it was took place interviews with key-agents of the study object. As main results it was identified some decisive factors for the development of the collective actions, and also, was still evidenced that these actions had a significant impact in terms of competitive advantages and regional development for the arrangement.
Robust closed-loop control of isometric muscle force using pulsewidth modulation

The design of feedback controllers to accurately and robustly regulate the properties of electrically stimulated muscle is considered. Reliable, precise control is necessary for the development of neuroprosthetic devices to improve gradation and repeatability of force. A digital closed-loop controller has been developed which regulates muscle force by modulating the pulsewidth of a constant-amplitude electrical simulation pulse train. This controller has been evaluated in slow- and fast-twitch muscles (cat soleus and plantaris) in acute experiments. In isometric tests, it was found to regulate muscle force with low sensitivity to modeling errors and disturbances while satisfying stability, repeatability, linearity, and step/ramp response criteria over a wide range of commands. <<ETX>>
The MPG System: A Machine-Independent Efficient Microprogram Generator

A machine-independent high-level microprogramming language, called MPGL, has been developed along with its processing system, called MPG. The MPGL allows the microprogrammer to write microprograms sequentially in a machine-independent fashion. The MPG provides the facility for translating these microprograms into efficient object code, as well as debugging object microprograms.
Evolution of Cretaceous active continental margins and their correlation with other global events

The scenario of the Earth active continental margin evolution is reconstructed here for Early Cretaceous–Senonian times when pulsatory alternated magmatic and orogenic processes occurred. The correlation of these continental marginal manifestations with some global events was undertaken also. The first, Neocomian stage (starting from the Jurassic) was distinguished by the combined development of continental marginal volcanic belts (with extensional conditions in back‐arc regions) and peri‐oceanic island arcs. In the second, Aptian–early Middle Albian stage the mid‐Cretaceous global orogeny took place which resulted in almost complete extinction of subduction zones within the continent–ocean transition as well as in obduction (with metamorphism) of island arc, back‐arc, and oceanic terranes together with microcontinents over continents. This mid‐Cretaceous (120–100 Ma) hypercollision was caused by a sharp increase in the spreading rate and origination of new mid‐oceanic ridges accompanied the breakup of Pangea. Those events provoked an increase in the rate of convergence of oceanic plates and continents, strong compressional stress into peri‐oceanic domains, and fast growth of the continental edges due to fold–thrust terrane rim development. During the third, late Albian–Late Cretaceous stage (100–85 Ma), some decrease of the rapid oceanic crust growth led to the accelerated subduction of oceanic plates under continents. The new convergent plate boundaries with global systems of continental marginal magmatic belts with a very large volume of volcanics were developed. The peculiar events of the Cretaceous history at active continental margins coincided with simultaneous extraordinary global events: fast growth of the oceanic crust, peak of intraplate magmatism, and prolonged lack of the Earth magnetic reversals, and can be considered to be indicators of mantle superplume activity and whole‐mantle convection development during 120–80 Ma.
Simultaneous estimation of transcript abundances and transcript specific fragment distributions of RNA-Seq data with the Mix2 model

Quantification of RNA transcripts with RNA-Seq is inaccurate due to positional fragmentation bias, which is not represented appropriately by current statistical models of RNA-Seq data. Another, less investigated, source of error is the inaccuracy of transcript start and end annotations. This article introduces the Mix2 (rd. “mixquare”) model, which uses a mixture of probability distributions to model the transcript specific positional fragment bias. The parameters of the Mix2 model can be efficiently trained with the EM algorithm and are tied between similar transcripts. Transcript specific shift and scale parameters allow the Mix2 model to automatically correct inaccurate transcript start and end annotations. Experiments are conducted on synthetic data covering 7 genes of different complexity, 4 types of fragment bias and correct as well as incorrect transcript start and end annotations. Abundance estimates obtained by Cufflinks 2.2. 0, PennSeq and the Mix2 model show superior performance of the Mix2 model in the vast majority of test conditions. The Mix2 software is available at http://www.lexogen. com/fileadmin/uploads/bioinfo/mix2model.tgz, subject to the enclosed license. Additional experimental data are available in the supplement.
Frequency of Ice Days at Selected Meteorological Stations in Svalbard

Abstract The paper aims to present research into both the long-term variability in the ice days in Svalbard representing the Atlantic sector of the Arctic, and their relations to atmospheric circulation. Ice days are defined as days with a daily maximum temperature below 0°C (Tmax<0°C). They are considered to be amongst the most important indices of current climate change. All the available data on daily maximum air temperature from three Norwegian stations (Svalbard Airport (Svalbard Lufthavn), Bjørnøya and Hopen) and from the Polish Polar Station in Hornsund (SW Spitsbergen) have been employed. The relevance of atmospheric circulation to the frequency of the occurrence of ice days was evaluated by calculating the Spearman correlation coefficients between the frequency of ice days and three regional circulation indices: zonal westerly circulation index (W), meridional southerly circulation index (S) and index of cyclonicity (C). At all the stations the number of ice days exhibited significant decreasing trends in the period of 1979-2012.
EVOLUTION, CATEGORIZATION AND VALUES

The aim of this paper is to present an evolutionary framework for categorization. Evolution needs an evaluation mechanism to work, and it is argued that primary values that the organism needs for its survival - such as food, mates for reproduction, and shelter - can drive the evolution of categories. Sensory stimulation is needed to build up the cognitive apparatus, but cannot in itself provide the evaluation mechanism for evolution. Categorization constrained by values will be dependent on the availability of sensory information, and its power as predictive of values. As perception and categorization are tied to the actions of the organism, it is argued that the unit of perception should be seen as larger than the usual singl e- dimension stimulus, and evidence is reviewed to support this claim. Covarying stimuli will also provide a much greater pre- dictive power than single-dimension stimuli alone.
Fibroblast Growth Factor Prototype Release and Fibroblast Growth Factor Receptor Signaling

A Brief Introduction to the Fibroblast Growth Factor Gene Family The fibroblast growth factor (FGF) family of genes presently comprise 18 members, including the two prototypes, FGF-1 (acidic) and FGF-2 (basic). Although the FGF prototypes are well described as mediators of a variety of diverse biological responses, such as mesoderm induction, neurogenesis, and angiogenesis in vivo, space constraints prevent a discussion of these activities. Likewise, while although many of the members of the FGF gene family, most notably FGF-1, FGF-2, and FGF-3, are involved in intracellular trafficking between the cytosol and nucleus, it is also not possible to discuss these data and their potential significance. Since this review will focus upon recent advances in FGF receptor signaling and the identification of the pathway for FGF-1 export/release, it is recommended that the reader consult the following citations for this information.1-5
Precompiling ALC TBoxes and Query Answering

Knowledge compilation is a common technique for propositional logic knowledge bases. The idea is to transfo rm a given knowledge base into a special normal form ([11],[6]), for wh ich queries can be answered efficiently. This precompilation st ep is very expensive but it only has to be performed once. We propose to a pply this technique to knowledge bases defined in Description L gics. For this, we introduce a structure called linkless grap h, forALC concepts. Further we present an algorithm, based on path dis solution, which can be used for this precompilation step. We discuss an efficient satisfiability test as well as a subsumption test for pr ecompiled concept descriptions. Finally we show how to extend this app roach in order to precompile Tboxes and to use the precompiled Tbox es for efficient Tbox reasoning.
Learning Methods for Similarity Handling in Phonebook­centric Social Networks

The capabilities of mobile phones enable them to participate in popular social network applications. The phonebooks in the mobile devices represent social relationships, that can be integrated in the social networks. Following we refer to this solution as phonebook­centric social networks. Such a network allows synchronization between the phonebook of the mobile phone and the social network. By the synchronization the goal is to identify the persons listed in the phonebook and the network, it means to find similar entries and keep the data consistent. The detection of those similar members is based on the similarity of the personal data, e.g., similar name, same phone number, e­mail, etc… We implemented a phonebook­centric social network, called Phonebookmark. In this paper we present the semi­automatic similarity handling of Phonebookmark. The similarity detection algorithm collects potential similarities and assigns a score to them. The score expresses how likely a phonebook contact and another member of the network identify the same person. Then the user can decide whether to accept or ignore the proposed similarity. During the first 9 month period users have accepted more than 90% of the proposed similarities which encouraged us to improve the algorithm further. We extended the algorithm with two learning methods. The first extension enables to learn similar names like Katharine and Kate and later this knowledge is used to detect similar names more efficiently. The second extension learns from the similarity resolving decisions of the users and based on this it maintains conditional probabilities of accepting a similarity if certain attributes of the personal data are equal. The extended algorithm still detects at least the same amount similarities but with better accuracy.
Preservation of Ranking Order in the Expression of Human Housekeeping Genes

Housekeeping (HK) genes fulfill the basic needs for a cell to survive and function properly. Their ubiquitous expression, originally thought to be constant, can vary from tissue to tissue, but this variation remains largely uncharacterized and it could not be explained by previously identified properties of HK genes such as short gene length and high GC content. By analyzing microarray expression data for human genes, we uncovered a previously unnoted characteristic of HK gene expression, namely that the ranking order of their expression levels tends to be preserved from one tissue to another. Further analysis by tensor product decomposition and pathway stratification identified three main factors of the observed ranking preservation, namely that, compared to those of non-HK (NHK) genes, the expression levels of HK genes show a greater degree of dispersion (less overlap), stableness (a smaller variation in expression between tissues), and correlation of expression. Our results shed light on regulatory mechanisms of HK gene expression that are probably different for different HK genes or pathways, but are consistent and coordinated in different tissues.
Noise Sampling Method: An ANOVA Approach Allowing Robust Selection of Differentially Regulated Genes Measured by DNA Microarrays

MOTIVATION A crucial step in microarray data analysis is the selection of subsets of interesting genes from the initial set of genes. In many cases, especially when comparing a specific condition to a reference, the genes of interest are those which are differentially expressed. Two common methods for gene selection are: (a) selection by fold difference (at least n fold variation) and (b) selection by altered ratio (at least n standard deviations away from the mean ratio). RESULTS The novel method proposed here is based on ANOVA and uses replicate spots to estimate an empirical distribution of the noise. The measured intensity range is divided in a number of intervals. A noise distribution is constructed for each such interval. Bootstrapping is used to map the desired confidence levels from the noise distribution corresponding to a given interval to the measured log ratios in that interval. If the method is applied on individual arrays having replicate spots, the method can calculate an overall width of the noise distribution which can be used as an indicator of the array quality. We compared this method with the fold change and unusual ratio method. We also discuss the relationship with an ANOVA model proposed by Churchill et al. In silico experiments were performed while controlling the degree of regulation as well as the amount of noise. Such experiments show the performance of the classical methods can be very unsatisfactory. We also compared the results of the 2-fold method with the results of the noise sampling method using pre and post immortalization cell lines derived from the MDAH041 fibroblasts hybridized on Affymetrix GeneChip arrays. The 2-fold method reported 198 genes as upregulated and 493 genes as downregulated. The noise sampling method reported 98 gene upregulated and 240 genes downregulated at the 99.99% confidence level. The methods agreed on 221 genes downregulated and 66 genes upregulated. Fourteen genes from the subset of genes reported by both methods were all confirmed by Q-RT-PCR. Alternative assays on various subsets of genes on which the two methods disagreed suggested that the noise sampling method is likely to provide fewer false positives.