Miracle-dz/UniFAR-FTUs huggingface dataset:
Defective placental adhesion in voluntary termination of second-trimester pregnancy and risk of recurrence in subsequent pregnancies

Abstract Objective. To evaluate the prevalence of defective placental adhesion (DPA) in voluntary termination of second-trimester pregnancy and the risk of DPA recurrence in subsequent pregnancies. Methods. We retrospectively reviewed the records of all patients who underwent voluntary second-trimester pregnancy termination in the period between January 2000 and December 2009. In all cases, the fetus and the placenta were submitted to pathological examination accordingly to our clinical protocol. Results. Four hundred twenty-seven cases of voluntary termination of second-trimester pregnancy were included in the study. Ten histologically confirmed cases of placenta accreta were observed (2.3%). Two patients with histological diagnosis of placenta accreta were lost at follow-up. Among the eight remaining patients, six had further pregnancies. Overall, nine pregnancies were recorded, and placenta accreta recurred in one patient. Conclusions. This study shows that DPA occurs in 2.3% of second-trimester voluntary termination of pregnancy; these patients should have an accurate ultrasound examination of the placenta in subsequent pregnancies.
FEATUREHOUSE: Language-independent, automated software composition

Superimposition is a composition technique that has been applied successfully in many areas of software development. Although superimposition is a general-purpose concept, it has been (re)invented and implemented individually for various kinds of software artifacts. We unify languages and tools that rely on superimposition by using the language-independent model of feature structure trees (FSTs). On the basis of the FST model, we propose a general approach to the composition of software artifacts written in different languages, Furthermore, we offer a supporting framework and tool chain, called FEATUREHOUSE. We use attribute grammars to automate the integration of additional languages, in particular, we have integrated Java, C#, C, Haskell, JavaCC, and XML. Several case studies demonstrate the practicality and scalability of our approach and reveal insights into the properties a language must have in order to be ready for superimposition.
Multiplicative nonnegative greph embedding

In this paper, we study the problem of nonnegative graph embedding, originally investigated in [J. Yang et al., 2008] for reaping the benefits from both nonnegative data factorization and the specific purpose characterized by the intrinsic and penalty graphs. Our contributions are two-fold. On the one hand, we present a multiplicative iterative procedure for nonnegative graph embedding, which significantly reduces the computational cost compared with the iterative procedure in [14] involving the matrix inverse calculation of an M-matrix. On the other hand, the nonnegative graph embedding framework is expressed in a more general way by encoding each datum as a tensor of arbitrary order, which brings a group of byproducts, e.g., nonnegative discriminative tensor factorization algorithm, with admissible time and memory cost. Extensive experiments compared with the state-of-the-art algorithms on nonnegative data factorization, graph embedding, and tensor representation demonstrate the algorithmic properties in computation speed, sparsity, discriminating power, and robustness to realistic image occlusions.
Progressive Coding of Surface Light Fields for Efficient Image Based Rendering

Surface light field is a light field parameterized to the surface of a geometric model. Although this multiview object representation enables rendering of objects from arbitrary views, the data size of a surface light field is huge. In this paper, a compression scheme is proposed. Together with compression efficiency, scalability and fast, memory efficient rendering is considered. To enable such functionalities, we base our compression scheme on a factorized representation of surface light field, and utilize a parameterization of the geometric model to a base mesh for application of wavelet transforms for progressive compression and scalable rendering. Experiments were conducted on a real world and synthetic data to study the compression efficiency and the characteristics of our proposed scheme.
Performance improvement of an internally blocking optical packet/burst switch

Optical packet/burst switching is considered a promising technique to improve the performance of optical networks. Key components in these technologies are the optical switching nodes. Some of these node architectures suffer from internal blocking. Synchronous operation allows overcoming most of the problems introduced by this internal blocking. However, in asynchronous networks internal blocking can have a more pronounced effect. In this paper, we propose a windowing technique to improve the performance of internally blocking optical switching nodes in asynchronous operation. Simulations will show significant improvements can be made.
Kernel-Based Models for Reinforcement Learning

Model-based approaches to reinforcement learning exhibit low sample complexity while learning nearly optimal policies, but they are generally restricted to finite domains. Meanwhile, function approximation addresses continuous state spaces but typically weakens convergence guarantees. In this work, we develop a new algorithm that combines the strengths of Kernel-Based Reinforcement Learning, which features instance-based state representation and kernel-based function approximation, and Prioritized Sweeping, which features model-based exploration. The resulting algorithm, Kernel-Based Prioritized Sweeping, empirically converges to good policies in continuous domains with relatively small amounts of data.
MIRU-VNTRplus: a web tool for polyphasic genotyping of Mycobacterium tuberculosis complex bacteria

Harmonized typing of bacteria and easy identification of locally or internationally circulating clones are essential for epidemiological surveillance and disease control. For Mycobacterium tuberculosis complex (MTBC) species, multi-locus variable number tandem repeat analysis (MLVA) targeting mycobacterial interspersed repetitive units (MIRU) has been internationally adopted as the new standard, portable, reproducible and discriminatory typing method. However, no specialized bioinformatics web tools are available for analysing MLVA data in combination with other, complementary typing data. Therefore, we have developed the web application MIRU-VNTRplus (http://www.miru-vntrplus.org). This freely accessible service allows users to analyse genotyping data of their strains alone or in comparison with a reference database of strains representing the major MTBC lineages. Analysis and comparisons of genotypes can be based on MLVA-, spoligotype-, large sequence polymorphism and single nucleotide polymorphism data, or on a weighted combination of these markers. Tools for data exploration include search for similar strains, creation of phylogenetic and minimum spanning trees and mapping of geographic information. To facilitate scientific communication, an expanding genotype nomenclature (MLVA MtbC15-9 type) that can be queried via a web- or a SOAP-interface has been implemented. An extensive documentation guides users through all application functions.
A Transcriptional Program Mediating Entry into Cellular Quiescence

The balance of quiescence and cell division is critical for tissue homeostasis and organismal health. Serum stimulation of fibroblasts is well studied as a classic model of entry into the cell division cycle, but the induction of cellular quiescence, such as by serum deprivation (SD), is much less understood. Here we show that SS and SD activate distinct early transcriptional responses genome-wide that converge on a late symmetric transcriptional program. Several serum deprivation early response genes (SDERGs), including the putative tumor suppressor genes SALL2 and MXI1, are required for cessation of DNA synthesis in response to SD and induction of additional SD genes. SDERGs are coordinately repressed in many types of human cancers compared to their normal counterparts, and repression of SDERGs predicts increased risk of cancer progression and death in human breast cancers. These results identify a gene expression program uniquely responsive to loss of growth factor signaling; members of SDERGs may constitute novel growth inhibitors that prevent cancer.
Assessing the effects of environmental variables on nestling growth using non-linear mixed effect models

In the context of climate change, understanding how animal populations are affected by changing environmental conditions is of increasing importance. This is particularly true in the Arctic where environmental change is occurring faster than the global average (Kattsov et al. 2005, Trenberth and Josey 2007). For raptors, the brood rearing period is particularly sensitive to environmental conditions due to a combination of nestling vulnerability and increased energetic demands from adults (Dawson and Bortolotti 2002, Robinson et al. 2007), and parameters of breeding success are often used to gauge the vulnerability of populations to changes in the environment (Steenhof et al. 1997, Vincenzi and Mangel 2013, Anctil et al. 2014, Kasprzykowski et al. 2014). Although nestling survival is an important and often used parameter, it is binary (either an individual survives or dies) and simple survival can miss the more subtle responses exhibited by nestlings. For example, sibling competition may not result in mortality, but a brood runt—the smallest sibling in a brood— that survives to fledging will likely grow at reduced rates (Podlas and Richner 2013, Sofaer et al. 2013). In this case, the unique condition expeCHAPTER 6
Demonstration of a fundamental quantum logic gate.

We demonstrate the operation of a two-bit "controlled-NOT" quantum logic gate, which, in conjunction with simple single-bit operations, forms a universal quantum logic gate for quantum computation. The two quantum bits are stored in the internal and external degrees of freedom of a single trapped atom, which is first laser cooled to the zero-point energy. Decoherence effects are identified for the operation, and the possibility of extending the system to more qubits appears promising.
A design for testability technique for RTL circuits using control/data flow extraction

We present a technique for extracting functional (control/dataflow) information from register transfer level (RTL) controller/data path circuits and illustrate its use in design for hierarchical testability of these circuits. This testing procedure and design for testability (DFT) technique is general enough to handle RTL control flow intensive circuits like protocol handlers as well as data flow intensive circuits like digital filters. It makes the combined controller-data path highly testable and does not require any external behavioral information. This scheme has the advantages of low area/delay/power overheads (average of 3.2%, 0.9% and 4.1%, respectively, for benchmarks), high fault coverage (over 99% for most cases), very low test generation times (because it is independent of bit-width), and the advantage of at-speed testing. Experiments show a 2-to-4 (1-to-3) orders of magnitude test generation time advantage over an efficient gate-level sequential test generator (combinational test generator that assumes full scan).
Virtual Separation of Concerns - A Second Chance for Preprocessors

Conditional compilation with preprocessors like cpp is a simple but eective means to implement variability. By annotating code fragments with #ifdef and #endif directives, dierent program variants with or without these fragments can be created, which can be used (among others) to implement software product lines. Although, preprocessors are frequently used in practice, they are often criticized for their negative eect on code quality and maintainability. In contrast to modularized implementations, for example using components or aspects, preprocessors neglect separation of concerns, are prone to introduce subtle errors, can entirely obfuscate the source code, and limit reuse. Our aim is to rehabilitate the preprocessor by showing how simple tool support can address these problems and emulate some benets of modularized implementations. At the same time we emphasize unique benets of preprocessors, like simplicity and language independence. Although we do not have a denitive answer on how to implement variability, we want highlight opportunities to improve preprocessors and encourage research toward novel preprocessor-based approaches.
Ieee Transactions on Visualization and Computer Graphics 1 Hierarchical Streamline Bundles

—Effective three-dimensional streamline placement and visualization plays an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.
Improving image luminance appearance through recurrent local intensity adaptation

We propose a new algorithm of automatic adjustment of image luminance to enhance the under-/over-exposed regions of images. Our method is based on recurrent local intensity adaptation. An optimal mapping curve for each pixel is determined by the local adaptation level through a nonlinear recurrent framework. We show that our algorithm efficiently improves the luminance appearance of images and we compare our results with the current state- of- the-art methods.
To personalize or not: a risk management perspective

Personalization techniques have been widely adopted in many recommender systems. However, experiments on real-world datasets show that for some users in certain contexts, personalized recommendations do not necessarily perform better than recommendations that rely purely on popularity. Broadly, this can be interpreted by the fact that the parameters of a personalization model are usually estimated from sparse data; the resulting personalized prediction, despite of its low bias, is often volatile. In this paper, we study the problem further by investigating into the ranking of recommendation lists. From a risk management and portfolio retrieval perspective, there is no difference between the popularity-based and the personalized ranking as both of the recommendation outputs can be represented as the trade-off between expected relevance (reward) and associated uncertainty (risk). Through our analysis, we discover common scenarios and provide a technique to predict whether personalization will fail. Besides the theoretical understanding, our experimental results show that the resulting switch algorithm, which decides whether or not to personalize, outperforms the mainstream recommendation algorithms.
Application of frequency-dependent traveltime tomography to 2D Crosswell seismic field data

We applied Zelt’s new frequency-dependent traveltime tomography (FDTT) method to 2D crosswell seismic field data from an eastern oil field in China. The FDTT uses the frequency content in the seismic waves in both the forward and inverse modeling steps. Although FDTT only uses a 300 Hz frequency to invert the dataset, the degree of matching between the inverted layers from FDTT and that of a sonic well logging curve is high, which shows that FDTT provides a high resolution reconstruction of subsurface structure through the simple use of the first-arrival traveltime data. The case study demonstrates that the FDTT algorithm is practical and can stand up to the complexities of a real 2D crosswell dataset. Additionally, we show that the FDTT method can create a high resolution long wavelength velocity model.
The Effects Of Volcanic Ash On The Strength And Permeability Mortar

Cement replacement materials have been widely used to reduce adverse environmental impacts, increase the strength and durability of concrete, such as fume silica, slag, fly ash or natural pozzolan (volcanic ash). Volcanic ash is material that released from the earth when volcanic eruptions occur. Volcanic ash becomes an important environmental issue because it disturbs the balance of the environment. Volcanic ash is a very fine pyroclastic material, has a characteristic form of diversity. In the field of engineering, the usage of volcanic ash as added ingredients is still very limited, while active volcanoes emit volcanic ash every year. The purpose of this study is to determine the effect of added materials-volcanic ash of Dukono mountain to the mortar mixture. In this research, the test of compressive strength and mortar absorption. This research uses added materialvolcanic ash from Dukono mountain. Preparation of test specimens with FAS value 0.4 with volcanic ash composition 0%, 5%, 10%, 15%, 20% and 25% to the weight of cement. The results of the compressive strength test average mortar with the composition of volcanic ash as added ingredients, increased compressive strength with the addition of volcanic ash composition of 5% and 10% of 21.73 MPa and 30.40 MP. Added volcanic ash of 15%, 20%, and 25% respectively decreased compressive strength of 24.27 MPa, 18.13 MPa, and 16.26 MPa, respectively. The best composition for the usage of volcanic ash as an additive material at 10% to the weight of cement. Keywords—volcanic ash; mortar; compressive stress
Determination of volumetric shrinkage of an expansive soil using digital camera images

Abstract The volume change during drying of compacted expansive soils occurs in the form of reduction in overall volume and development of cracks. Accurate determination of volume of shrunken soil specimens becomes essential to understand the shrinkage behaviour of compacted expansive soils. Mercury displacement method available for the bulk volume measurement of cylindrical small samples suffers from the serious limitations such as the restrictions of using the mercury as it is a hazardous material and the size of specimens is limited to small samples/portions. In the past few years, the digital camera images have been successfully utilised in studying the crack pattern and various parameters associated with reconstituted soils dried from slurry state. Fewer works have been carried out to quantify the cracks in the compacted soils, especially in compacted expansive soils. In this paper, simple methods for the determination of the volume of shrunken soil specimens excluding the volume of cracks are proposed based on the digital camera images captured on thin oedometer shrunken soil specimen along with the vernier calliper method. The results were compared with the mercury displacement method. Cracks which extended from top to bottom of the shrunken specimen during drying assisted in employing these methods. The effect of cracks on shrinkage deformations during second drying cycle and at the end of five drying cycles under a vertical stress of 12.5 kPa was studied.
GUNSAT: A Greedy Local Search Algorithm for Unsatisfiability

Local search algorithms for satisfiability testing are still the best methods for a large number of problems, despite tremendous progresses observed on complete search algorithms over the last few years. However, their intrinsic limit does not allow them to address UNSAT problems. Ten years ago, this question challenged the community without any answer: was it possible to use local search algorithm for UNSAT formulae? We propose here a first approach addressing this issue, that can beat the best resolution-based completemethods. We define the landscape of the search by approximating the number of filtered clauses by resolution proof. Furthermore, we add high-level reasoning mechanism, based on Extended Resolution and Unit Propagation Look-Ahead to make this new and challenging approach possible. Our new algorithm also tends to be the first step on two other challenging problems: obtaining short proofs for UNSAT problems and build a real local-search algorithm for QBF.
An Optimal Replica Placement Algorithm for Symphony P2P Networks

Placing replicas in a P2P network can reduced the number of hops required by a node to search an object. One existing replica placement strategy for structured P2P networks allocates replicas at nodes that are continuously close to the destination. In this paper, we investigate the effectiveness of such an approach. We propose an optimal algorithm to place replicas for an object, in terms of number of hops, in the deterministic P2P network (Chord) and randomized P2P network (Symphony). Particularly, our replica placement algorithm is based on the technique of dynamic programming. We perform several experiments to find the optimal replica placements for a large number of Symphony networks and analyze the results. Our simulation results show that locations of optimal replica placements are not necessarily continuously close to the destination.
Intensification Of Low Energy Nuclear Reactions Using Superwave Excitation

Energetics Technologies (ET) was recently established to investigate possibilities for inducing Low Energy Nuclear Reactions (LENR) using special wave excitation. Four experimental approaches are being pursued: electrolysis, glow- discharge, gas loading in catalyst cells and high-pressure high-temperature cell with ultrasonic wave excitation. The experimental setups developed by ET are described along with preliminary results obtained. A significant amount of excess heat was measured in the first glow discharge experiment. The power generated during the experiment was up to 3.9 times the input power. When driven with waves the excess heat was higher than when driven with DC. A significant amount of excess heat was also measured after the shutdown of the glow discharge; it lasted for approximately 10 hours. The total excess energy generated is estimated to be 6.7 times the input energy. The "heat- after-death" phenomenon was also observed in another glow discharge experiment. Excess heat up to approximately 80% was measured over a period of over 3 months in yet another glow discharge experiment. Driving the electrolytic cells with waves resulted in a faster loading than when driving them with DC of the same average current. The tritium concentration in the electrolyte measured at the end of the experiments was found to be up to more than 100% the pre- experiment level. No excess heat was measured, so far, in the catalyst cells. Successful loading of Pd target with D was obtained in the high-pressure high-temperature gas cell without going through the α+β phase of the Pd-D system.