Miracle-dz/UniFAR-FTUs huggingface dataset:
Metamorphic pressure-temperature paths of eclogites from The North-East Greenland Caledonides

The exhumation of ultrahigh-pressure (UHP) eclogites on Rabbit Ears Island in the North-East Greenland Caledonides needs to be better understood. Two eclogites from this area were studied to reveal their exhumation path using a thermodynamic modeling method along with conventional and Zr-in-rutile thermobarometry. Peak condition was constrained at 3.4 GPa and 920 ̊C, under subsolidus conditions. The eclogites display ample evidence of partial melting, including euhedral neoblasts, cuspate textures, peritectic garnet and graphic intergrowths. The textures demonstrate that phengite and mainly epidote-group minerals (referring to zoisite, clinozoisite and epidote) are the major melted phases. Thermodynamic modeling for a symplectite after omphacite, along with analyzed plagioclase, retrograde clinopyroxene and amphibole yielded another P-T condition at around 1.2 GPa, 800 ̊C. An attempt to model melting of a local, former melt domain, now consisting of peritectic garnet, amphibole and plagioclase, shows that the mineral assemblage crystallized at 1.4 GPa and 740 ̊C. Zrin-rutile thermobarometry on inclusions in garnet yields a temperature estimation of 840 ̊C at 3.4 GPa, which is interpreted to have formed on prograde path. Petrographic textures and thermodynamic modeling suggest that the UHP kyanite eclogites in North-
A Combined Sensitive Matrix Method and Maximum Likelihood Method for Uncertainty Inverse Problems

The uncertainty inverse problems with insufficiency and imprecision in the input and/or output parameters are widely existing and unsolved in the practical engineering. The insufficiency refers to the partly known parameters in the input and/or output, and the imprecision refers to the measurement errors of these ones. In this paper, a combined method is proposed to deal with such problems. In this method, the imprecision of these known parameters can be described by probability distribution with a certain mean value and variance. Sensitive matrix method is first used to transform the insufficient formulation in the input and/or output to a resolvable one, and then the mean values of these unknown parameters can be identified by maximizing the likelihood of the measurements. Finally, to quantify the uncertainty propagation, confidence intervals of the obtained solutions are calculated based on linearization and Monte Carlo methods. Two numerical examples are presented to demonstrate the effectiveness of the present method.
Multicity Outbreak of Carbapenem-Resistant Acinetobacter baumannii Isolates Producing the Carbapenemase OXA-40

ABSTRACT During 2005 we detected a multicity outbreak of infections or colonization due to high-level imipenem-resistant Acinetobacter baumannii (MIC, 64 μg/ml). One hundred isolates from diverse sources were obtained from seven acute-care hospitals and two extended-care facilities; 97% of the isolates belonged to one clone. Susceptibility testing of the first 42 isolates (January to April 2005) revealed broad resistance profiles. Half of the isolates were susceptible to ceftazidime, with many isolates susceptible only to colistin. The level of AmpC β-lactamase expression was stronger in isolates resistant to ceftazidime. PCR and subsequent nucleotide sequencing analysis identified blaOXA-40. The presence of an OXA-40 β-lactamase in these isolates correlated with the carbapenem resistance. By Southern blot analysis, a blaOXA-40-specific probe revealed that the gene was both plasmid and chromosomally located. This is the first time in the United States that such carbapenem resistance in A. baumannii has been attributable to a carbapenemase.
Recovering from Main-Memory Lapses

Recovery activities, like logging, checkpointing and restart, are used to restore a database to a consistent state after a system crash has occurred. Recovery related overhead is particularly troublesome in a mainmemory database where I/O activities are performed for the sole purpose of ensuring data durability. In this paper we present a recovery technique for main-memory databases, whose benefits are as follows. First, disk I/O is reduced by logging to disk only redo records during normal execution. The undo log is normally resident only in main memory, and is garbage collected after transaction commit. Second, our technique reduces lock contention on account of the checkpointer by allowing action consistent checkpointing to do so, the checkpointer writes to disk relevant parts of the undo log. Third, the recovery algorithm makes only a single pass over the log. Fourth, our technique does not require the availability of any special hardware such as non-volatile RAM. Thus our recovery technique combines the benefits of several techniques proposed in the past. The ideas behind our technique can be used to advantage in disk-resident databases aa well. Permission Lo copy without fee all or part of this material is granted provided that the copies are not made or distriluled for dinxt commercial advantage, the VLDB copyright notice and the We of Ihe pullicaGon and its date appear, and notice is given Ihal copying ir by permission of the Very Large Data Base Endowmenk To copy otherwise, or lo republish, requires a fee and/or special permission jkrn Ihe Endowmrrlt. Proceedings of the 19th VLDB Conference Dublin, Ireland, 1993
Simultaneous multispeaker segmentation for automatic meeting recognition

Vocal activity detection is an important technology for both automatic speech recognition and automatic speech understanding. In meetings, participants typically vocalize for only a fraction of the recorded time, and standard vocal activity detection algorithms for close-talk microphones have shown to be ineffective. This is primarily due to the problem of crosstalk, in which a participant's speech appears on other participants' microphones, making it hard to attribute detected speech to its correct speaker. We describe an automatic multichannel segmentation system for meeting recognition, which accounts for both the observed acoustics and the inferred vocal activity states of all participants using joint multi-participant models. Our experiments show that this approach almost completely eliminates the crosstalk problem. Recent improvements to the baseline reduce the development set word error rate, achieved by a state-of-the-art multi-pass speech recognition system, by 62% relative to manual segmentation. We also observe significant performance improvements on unseen data.
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors

We present a scalable Bayesian model for low-rank factorization of massive tensors with binary observations. The proposed model has the following key properties: (1) in contrast to the models based on the logistic or probit likelihood, using a zero-truncated Poisson likelihood for binary data allows our model to scale up in the number of \emph{ones} in the tensor, which is especially appealing for massive but sparse binary tensors; (2) side-information in form of binary pairwise relationships (e.g., an adjacency network) between objects in any tensor mode can also be leveraged, which can be especially useful in "cold-start" settings; and (3) the model admits simple Bayesian inference via batch, as well as \emph{online} MCMC; the latter allows scaling up even for \emph{dense} binary data (i.e., when the number of ones in the tensor/network is also massive). In addition, non-negative factor matrices in our model provide easy interpretability, and the tensor rank can be inferred from the data. We evaluate our model on several large-scale real-world binary tensors, achieving excellent computational scalability, and also demonstrate its usefulness in leveraging side-information provided in form of mode-network(s).
On-site humanoid navigation through hand-in-hand interface

In order to realize humanoid robots that support people in their daily lives, on-site humanoid behavior navigation system which a robot behaviors autonomously as well as a robot reacts to the intentions of a human. This paper proposes new on-site navigation interface method for humanoid robots which a human navigate a humanoid robot hand-in-hand. Previous humanoid researches aim to realize an autonomous intelligence, which is able to survive in a real environment without any help from a person. However to utilize a humanoid robot in a real world, it is necessary to take a robot to various locations or make a robot to manipulate and use various kinds of objects and tools, on-site navigation that a person is able to induce a humanoid behavior. In the experiment the operator takes a humanoid robot to a kitchen and teaches holding a kettle using this interaction kernel, and played back the motion sequence by planning in different environments
Some criteria for error bounds in set optimization

We obtain sufficient and/or necessary conditions for global/local error bounds for the distances to some sets appeared in set optimization studied with both the set approach and vector approach (sublevel sets, constraint sets, sets of all Pareto efficient/ Henig proper efficient/super efficient solutions, sets of solutions corresponding to one Pareto efficient/Henig proper efficient/super efficient value) and sufficient conditions for metric subregulatity of a set-valued map at efficient solutions. All criteria except one are described in terms of the Mordukhovich coderivative and coderivative of convex analysis. Our techniques are based on scalarization by mean of the Hiriart-Urruty signed distance function, on exploiting criteria in terms of subdifferentials for error bounds of a lower semicontinuous function and estimates for subdifferentials of marginal functions. We also consider the single-valued case and provide illustrating examples.
A Packing Approach to Compare Slotted and Non-Slotted Medium Access Control

In multi-hop ad hoc networks, the efficiency of a medium access control protocol under heavy traffic load depends mainly on its ability to schedule a large number of simultaneous non-interfering transmissions. However, as each node has only a local view of the network, it is difficult to globally synchronize transmission times over the whole network. How does the lack of global coordination affect spatial reuse in multi-hop wireless networks? We show that in a de-centralized network the spatial reuse does not benefit from global clock synchronization. On the contrary, we demonstrate that non-slotted protocols using collision avoidance mechanisms can achieve a higher spatial reuse than the corresponding slotted protocols. By means of a simple backoff mechanism, one can thus favor the spontaneous emergence of spatially dense transmission schedules.
Influence of Powder Morphology and Chemical Composition on Metallic Foams produced by SlipReactionFoamSintering (SRFS)‐ Process

The SlipReactionFoamSintering (SRFS)‐ process is a metallurgical method to produce open‐cell metallic foams of iron based materials, steels and nickel based materials. In this process several chemical reactions take place. Through the most influential parameter, the morphology of the metallic powder, different properties of the foam can be adjusted, such as the viscosity of the slip, the cell structure and the mechanical properties. Several examples are presented in this paper. Moreover, the thermal conductivity of three foams is measured with the transient‐heat‐source‐technique.
Modified hemiarthroplasty for four‐part fractures of the proximal humerus

Hemiarthroplasty is used to treat patients with Neer four‐part fractures but the post‐operative complication rate remains high, particularly with regard to shoulder joint instability. This study was aimed at evaluating the efficacy of a modified rotator cuff reconstruction and balance technique by comparing it with conventional rotator cuff restoration surgery for Neer four‐part fractures.
Reduction Theories Elucidate the Origins of Complex Biological Rhythms Generated by Interacting Delay-Induced Oscillations

Time delay is known to induce sustained oscillations in many biological systems such as electroencephalogram (EEG) activities and gene regulations. Furthermore, interactions among delay-induced oscillations can generate complex collective rhythms, which play important functional roles. However, due to their intrinsic infinite dimensionality, theoretical analysis of interacting delay-induced oscillations has been limited. Here, we show that the two primary methods for finite-dimensional limit cycles, namely, the center manifold reduction in the vicinity of the Hopf bifurcation and the phase reduction for weak interactions, can successfully be applied to interacting infinite-dimensional delay-induced oscillations. We systematically derive the complex Ginzburg-Landau equation and the phase equation without delay for general interaction networks. Based on the reduced low-dimensional equations, we demonstrate that diffusive (linearly attractive) coupling between a pair of delay-induced oscillations can exhibit nontrivial amplitude death and multimodal phase locking. Our analysis provides unique insights into experimentally observed EEG activities such as sudden transitions among different phase-locked states and occurrence of epileptic seizures.
Developmentally Sensitive Interaction Effects of Genes and the Social Environment on Total and Subcortical Brain Volumes

Smaller total brain and subcortical volumes have been linked to psychopathology including attention-deficit/hyperactivity disorder (ADHD). Identifying mechanisms underlying these alterations, therefore, is of great importance. We investigated the role of gene-environment interactions (GxE) in interindividual variability of total gray matter (GM), caudate, and putamen volumes. Brain volumes were derived from structural magnetic resonance imaging scans in participants with (N = 312) and without ADHD (N = 437) from N = 402 families (age M = 17.00, SD = 3.60). GxE effects between DAT1, 5-HTT, and DRD4 and social environments (maternal expressed warmth and criticism; positive and deviant peer affiliation) as well as the possible moderating effect of age were examined using linear mixed modeling. We also tested whether findings depended on ADHD severity. Deviant peer affiliation was associated with lower caudate volume. Participants with low deviant peer affiliations had larger total GM volumes with increasing age. Likewise, developmentally sensitive GxE effects were found on total GM and putamen volume. For total GM, differential age effects were found for DAT1 9-repeat and HTTLPR L/L genotypes, depending on the amount of positive peer affiliation. For putamen volume, DRD4 7-repeat carriers and DAT1 10/10 homozygotes showed opposite age relations depending on positive peer affiliation and maternal criticism, respectively. All results were independent of ADHD severity. The presence of differential age-dependent GxE effects might explain the diverse and sometimes opposing results of environmental and genetic effects on brain volumes observed so far.
Antimicrobial Therapy Using Sulfamethoxazole Trimethoprim for Kawasaki Disease Patients Unresponsive to Intravenous Immunoglobulin

Our previous study suggested that the production of superantigens and heat-shock protein 60 by small intestinal bacteria might play a role in Kawasaki disease (KD). We demonstrated that they were all resistant to commonly used antibiotics, except for sulamethoxazole trimethoprim (SMX-TMP). We used SMX-TMP for 7 cases of KD that were unresponsive to intravenous immunoglobulin (IVIG) and studied the antipyretic potency of this treatment. In 6 out of the 7 cases, we demonstrated that antipyretic potency was observed without side effects within 2 days of the initial administration. Antimicrobial therapy using SMX-TMP might represent a novel strategy for cases of KD that are unresponsive to IVIG.
Nonlinear multiplicative dendritic integration in neuron and network models

Neurons receive inputs from thousands of synapses distributed across dendritic trees of complex morphology. It is known that dendritic integration of excitatory and inhibitory synapses can be highly non-linear in reality and can heavily depend on the exact location and spatial arrangement of inhibitory and excitatory synapses on the dendrite. Despite this known fact, most neuron models used in artificial neural networks today still only describe the voltage potential of a single somatic compartment and assume a simple linear summation of all individual synaptic inputs. We here suggest a new biophysical motivated derivation of a single compartment model that integrates the non-linear effects of shunting inhibition, where an inhibitory input on the route of an excitatory input to the soma cancels or “shunts” the excitatory potential. In particular, our integration of non-linear dendritic processing into the neuron model follows a simple multiplicative rule, suggested recently by experiments, and allows for strict mathematical treatment of network effects. Using our new formulation, we further devised a spiking network model where inhibitory neurons act as global shunting gates, and show that the network exhibits persistent activity in a low firing regime.
An Approach towards Record Linkage using Genetic Algorithm along with Hash Algorithm

Several systems that depends on the integrity of the data in order to offer high quality services, such as digital libraries and e-commerce brokers, may be affected due to the existence of duplicates in their warehouse. Due to this, more time is required to retrieve high quality data. Here deduplication or record linkage is computed by using hash algorithm i.e., MD5 and SHA-1 algorithm for finding similarity to detect duplicate records and eliminate them using evolutionary i.e., genetic algorithm. This approach removes the duplicate dataset samples in the system.
Efficient Liver-specific Deletion of a Floxed Human Angiotensinogen Transgene by Adenoviral Delivery of Cre Recombinasein Vivo *

Tissue-specific ablation of gene function is possible in vivo by the Cre-loxP recombinase system. We generated transgenic mice containing a human angiotensinogen gene flanked by loxP sites (hAGTflox). To examine the physiologic consequences of tissue-specific loss of angiotensinogen gene function in vivo, we constructed an adenovirus expressing Cre recombinase. Studies were performed in several independent lines of hAGTflox mice before and after intravenous administration of either Adcre or AdβGal as a control. Systemic administration of Adcre caused a significant decrease in circulating human angiotensinogen and markedly blunted the pressor response to administration of purified recombinant human renin. Southern blot analysis of genomic DNA from various organs revealed that the Cre-mediated deletion was liver-specific. Further analysis revealed the absence of full-length human angiotensinogen mRNA and protein in the liver but not the kidney of Adcre mice, consistent with the liver being the target for adenoviruses administered intravenously. These studies demonstrate that extra-hepatic sources of angiotensinogen do not contribute significantly to the circulating pool of angiotensinogen and provide proof-of-principle that the Cre-loxP system can be used effectively to examine the contribution of the systemic and tissue renin-angiotensin system to normal and pathological regulation of blood pressure.
Computer‐assisted Continuous Infusions of Fentanyl during Cardiac Anesthesia: Comparison with a Manual Method

The design and implementation of a computer-assisted continuous infusion (CACI) system to rapidly attain and maintain a constant plasma fentanyl concentration (PFC), as well as a CACI system that allowed the anesthesiologist to change the plasma level of fentanyl during cardiac anesthesia, were developed. In 30 patients (three groups of 10 patients each) these two automated methods of fentanyl infusion were compared with a manual fentanyl administration method. There was excellent agreement in the measured/predicted PFC ratios with the CACI stable fentanyl level system (ratio = 0.99, n = 91) and in the CACI variable fentanyl level system (ratio = 1.08, n = 79). The stable fentanyl level group of patients received significantly more (P < 0.05) fentanyl than did the other groups. The CACI variable fentanyl level group of patients had greater hemodynamic stability, required significantly (P < 0.05) fewer adjuvant drug interventions and experienced significantly (P < 0.05) fewer hypotensive and hypertensive episodes than the manual, bolus fentanyl (control) group. These data show that a computer-assisted automated infusion of fentanyl is safe and as good as manual methods. CACI has greater potential as a new method of intravenous anesthesia administration.
New variance ratio tests to identify random walk from the general mean reversion model

We develop some properties on the autocorrelation of the k-period returns for the general mean reversion (GMR) process in which the stationary component is not restricted to the AR(l) process but take the form of a general ARMA process. We then derive some properties of the GMR process and three new non-parametric tests comparing the relative variability of returns over different horizons to validate the GMR process as an alternative to random walk. We further examine the asymptotic properties of these tests which can then be applied to identify random walk models from the GMR processes.
Para-active learning

Training examples are not all equally informative. Active learning strategies leverage this observation in order to massively reduce the number of examples that need to be labeled. We leverage the same observation to build a generic strategy for parallelizing learning algorithms. This strategy is effective because the search for informative examples is highly parallelizable and because we show that its performance does not deteriorate when the sifting process relies on a slightly outdated model. Parallel active learning is particularly attractive to train nonlinear models with non-linear representations because there are few practical parallel learning algorithms for such models. We report preliminary experiments using both kernel SVMs and SGD-trained neural networks.
Tracking code patterns over multiple software versions with Herodotos

An important element of understanding a software code base is to identify the repetitive patterns of code it contains and how these evolve over time. Some patterns are useful to the software, and may be modularized. Others are detrimental to the software, such as patterns that represent defects. In this case, it is useful to study the occurrences of such patterns, to identify properties such as when and why they are introduced, how long they persist, and the reasons why they are corrected. To enable studying pattern occurrences over time, we propose a tool, Herodotos, that semi-automatically tracks pattern occurrences over multiple versions of a software project, independent of other changes in the source files. Guided by a user-provided configuration file, Herodotos builds various graphs showing the evolution of the pattern occurrences and computes some statistics. We have evaluated this approach on the history of a representative range of open source projects over the last three years. For each project, we track several kinds of defects that have been found by pattern matching. This tracking is done automatically in 99% of the occurrences. The results allow us to compare the evolution of the selected projects and defect kinds over time.