Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Planning for Interacting Durative Actions with Continuous Effects

We consider planning domains with both discrete and continuous changes. Continuous change occurs especially when agents share time-dependent critical resources. In these cases, besides discrete and continuous changes, their interactions should also be taken into consideration. However concurrency of durative actions with interacting continuous effects cannot be exploited by existing temporal planners. To overcome this problem, we propose an action lifting approach and we analyze path sharing problem to illustrate interaction of continuous linear effects in the planning domain.
Serum Levels of Caspase-Cleaved Cytokeratin-18 in Patients with Severe Traumatic Brain Injury Are Associated with Mortality: A Pilot Study

Objective There have been found apoptotic changes in brain tissue samples from animals and humans after a traumatic brain injury (TBI). The protein cytokeratin 18 (CK-18), present in epithelial cells, is cleaved by the action of caspases during apoptosis, and the resulting fragments are released into the blood as caspase-cleaved CK (CCCK)-18. Circulating levels of CCCK-18, as biomarker of apoptosis, have been determined in patients with different processes; however, it has not been explored in TBI patients. Thus, the objective of this study was to determine whether there is an association between serum CCCK-18 levels and mortality and whether such levels could be used as a biomarker to predict outcomes in TBI patients. Methods A prospective, observational, multicenter study carried out in six Spanish Intensive Care Units. We included patients with severe TBI defined as Glasgow Coma Scale (GCS) lower than 9; and were excluded those patients with Injury Severity Score (ISS) in non-cranial aspects higher than 9. We measured serum CCCK-18 levels at admission. The end-point of the study was 30-day mortality. Results Surviving patients (n = 73) showed lower serum CCCK-18 levels (P = 0.003) than non-survivors (n = 27). On ROC analysis, the area under the curve (AUC) for serum CCCK-18 levels as predictor of 30-day mortality was 0.69 (95% CI = 0.59–0.78; P = 0.006). We found in survival analysis that patients with serum CCCK-18 higher than 201 u/L had higher 30-day mortality than patients with lower levels (Hazard ratio = 3.9; 95% CI = 1.81–8.34; P<0.001). Regression analyses showed that serum CCCK-18 levels higher than 201 u/L were associated with 30-day mortality (OR = 8.476; 95% CI = 2.087–34.434; P = 0.003) after controlling for age and GCS. Conclusions The novel finding of our study was that serum CCCK-18 levels are associated with 30-day mortality and could be used as a prognostic biomarker in patients with severe TBI.
Is Tractable Reasoning in Extensions of the Description Logic EL Useful in Practice

Extensions of the description logic EL have recently been proposed as lightweight ontology languages. The most important feature of these extensions is that, despite including powerful expressive means such as general concept inclusion axioms, reasoning can be carried out in polynomial time. In this paper, we consider one of these extensions, EL, and introduce a refinement of the known polynomial-time classification algorithm for this logic, which was implemented in our CEL reasoner. We describe the results of several experiments with CEL on large ontologies from practice, which show that even a relatively straightforward implementation of the described algorithm outperforms highly optimized, state-of-the-art tableau reasoners for expressive description logics.
On fault probabilities and yield models for VLSI neural networks

We investigate the estimation of fault probabilities and yield for very large scale integration (VLSI) implementations of neural computational models. Our analysis is limited to structures that can be mapped directly onto silicon as truly distributed parallel processing systems. Our work improves on the framework suggested by Feltham and Maly and is also applicable to analog or mixed analog/digital VLSI systems.
Reinforcement Learning for Relational MDPs

In this paper we present a new method for reinforcement learning in relational domains. A logical language is employed to abstract over states and actions, thereby decreasing the size of the state-action space significantly. A probabilistic transition model of the abstracted Markov-Decision-Process is estimated to to speed-up learning. We present theoretical and experimental analysis of our new representation. Some insights concerning the problems and opportunities of logical representations for reinforcement learning are obtained in the context of a growing interest in the use of abstraction in reinforcement learning contexts.
Globesity: Is Globalization a Pathway to Obesity?

Obesity has risen dramatically at the same time as globalization has surged, which poses the question of whether the two are related. In this paper we document the association between type of globalization (economic, political or social) and obesity using data from 15 up to 23 different countries for up to 15 years, as well as three primary outcomes: obesity, caloric intake and grams of fat consume and a rich set of controls for micro-mechanisms. Our results are suggestive of a robust association between globalization and both obesity and calorie intake. However, once we control for micro-mechanisms suggested in the literature (e.g. food prices, female labor market participation and income), the impact of economic globalization fades away whilst ‘social globalization’ remains as a having robust and strong effect on the three measures of obesity. A one standard deviation increase in the KOF index of social globalization implies a rise of 3 percentage points in the proportion of obese population. It leads to a rise of 217 kcal and of 23.1 grams of fat consumed, respectively.
Processing of Unattended Information: An Evaluation of Current Explanations

ONLY :l~ure 12. Percentage of words correctly recognized as a function of condition. Condition 2 Ccnc~ete only; Condition 3 Abstract only; Condition Lro~c~a+e anu~ A~s+~act (~vn~~l·-en+ ? ' , v .! " .L ._, v "-' u.i. . n • .:. C.:. .Lu l.J / ~ 74 displays was the same regardless of the experimental condition (processing time was the same when there was no centered word present, when the centered word was concrete, when the centered word was abstract, and when the centered words were either concrete or abstract). The lack of a difference between conditions for word recognition was surprising. It was predicted that concrete words would be remembered more successfully than abstract words and that recall for the condition which consisted of both concrete and abstract words would fall between the concrete only and abstract only recall rates. It should again be noted that the results were in the direction predicted, but that the differences were not large enough to reach significance. There are two possible explanations· for this result. First, the fact that the differences in this experiment did not approach significance was probably due to the fact that the number of subjects participating in this experiment was relatively small. The fewer the number of measurements taken in an experiment, the greater the differences must be in order to be considered significant. If the differences noted here remained consistent (thus, not due to chance) over a larger number of subjects they would have been considered significant. 75 Second, it was established in the first experiment that recognition memory for a list of 20 unrelated words was poor (although significantly greater than chance). In all conditions within the present experiment the word lists consisted of unrelated words. The weak effect exhibited in this experiment was probably due in part to a floor effect. The differences might have been larger if this floor effect had been avoided. One way in which this problem might be overcome in a future experiment would be to present words from consistent categories for all conditions. Moreover, as mentioned eariler, when selecting the stimulus items care was taken to select items that could be classified as either concrete or abstract and to match all test and foil items for frequency and length. In a future study, the effects suggested here might be strenghtened if the stimulus words were selected such that (in addition to the constraints mentioned above) the concrete words were highly concrete and the abstract words were very abstract (this could be done by checking the stimulus words against the Christian et.al. 1978 norms).
Mammalian GCN5 and P/CAF Acetyltransferases Have Homologous Amino-Terminal Domains Important for Recognition of Nucleosomal Substrates

ABSTRACT The yeast transcriptional adapter Gcn5p serves as a histone acetyltransferase, directly linking chromatin modification to transcriptional regulation. Two human homologs of Gcn5p have been reported previously, hsGCN5 and hsP/CAF (p300/CREB binding protein [CBP]-associated factor). While hsGCN5 was predicted to be close to the size of the yeast acetyltransferase, hsP/CAF contained an additional 356 amino-terminal residues of unknown function. Surprisingly, we have found that in mouse, both the GCN5and the P/CAF genes encode proteins containing this extended amino-terminal domain. Moreover, while a shorter version of GCN5 might be generated upon alternative or incomplete splicing of a longer transcript, mRNAs encoding the longer protein are much more prevalent in both mouse and human cells, and larger proteins are detected by GCN5-specific antisera in both mouse and human cell extracts. Mouse GCN5 (mmGCN5) andmmP/CAF genes are ubiquitously expressed, but maximum expression levels are found in different, complementary sets of tissues. Both mmP/CAF and mmGCN5 interact with CBP/p300. Interestingly,mmGCN5 maps to chromosome 11 and cosegregates withBRCA1, and mmP/CAF maps to a central region of chromosome 17. As expected, recombinant mmGCN5 and mmP/CAF both exhibit histone acetyltransferase activity in vitro with similar substrate specificities. However, in contrast to yeast Gcn5p and the previously reported shorter form of hsGCN5, mmGCN5 readily acetylates nucleosomal substrates as well as free core histones. Thus, the unique amino-terminal domains of mammalian P/CAF and GCN5 may provide additional functions important to recognition of chromatin substrates and the regulation of gene expression.
LUIGi: A Goal-Driven Autonomy Agent Reasoning with Ontologies

In this paper we present LUIGi, a goal-driven autonomy (GDA) agent that uses ontological representations. Like other GDA agents, LUIGi reasons about (1) its own expectations when following a course of action, (2) the discrepancies between these expectations and actual situations encountered, (3) explanations for those discrepancies and (4) new goals based on the explanations. Unlike other GDA agents, LUIGi uses ontologies to reason about these four GDA elements enabling inference capabilities relating high-level concepts with low-level chunks of information. We demonstrate LUIGi’s capabilities in the context of a real-time strategy game.
Approach Towards a Natural Language Analysis for Diagnosing Mood Disorders and Comorbid Conditions

Here we propose an approach for developing a diagnosis system for mood disorders, such as depression and bipolar disorder, based on language analysis from speech and text. Our system is based on the Mood State Indicator algorithm (MSI) for real-time analysis of a patient's mental state. MSI is designed to give a quantitative measure of cognitive state based on axiological values and time orientation of lexical features. MSI's multi-layered analytic engine consists of multiple information processing modules to systematically retrieve, parse and process features of a patient's discourse. Gold standard clinical criteria will be used to match language analysis indicators to mood disorder diagnosis.
Necdin Plays a Role in the Serotonergic Modulation of the Mouse Respiratory Network: Implication for Prader-Willi Syndrome

Prader-Willi syndrome is a neurogenetic disease resulting from the absence of paternal expression of several imprinted genes, including NECDIN. Prader-Willi children and adults have severe breathing defects with irregular rhythm, frequent sleep apneas, and blunted respiratory regulations. For the first time, we show that Prader-Willi infants have sleep apneas already present at birth. In parallel, in wild-type and Necdin-deficient mice, we studied the respiratory system with in vivo plethysmography, in vitro electrophysiology, and pharmacology. Because serotonin is known to contribute to CNS development and to affect maturation and function of the brainstem respiratory network, we also investigated the serotonergic system with HPLC, immunohistochemistry, Rabies virus tracing approaches, and primary culture experiments. We report first that Necdin-deficiency in mice induces central respiratory deficits reminiscent of Prader-Willi syndrome (irregular rhythm, frequent apneas, and blunted respiratory regulations), second that Necdin is expressed by medullary serotonergic neurons, and third that Necdin deficiency alters the serotonergic metabolism, the morphology of serotonin vesicles in medullary serotonergic neurons but not the number of these cells. We also show that Necdin deficiency in neonatal mice alters the serotonergic modulation of the respiratory rhythm generator. Thus, we propose that the lack of Necdin expression induces perinatal serotonergic alterations that affect the maturation and function of the respiratory network, inducing breathing deficits in mice and probably in Prader-Willi patients.
Room for improvement in automatic image description: an error analysis

In recent years we have seen rapid and significant progress in automatic image description but what are the open problems in this area? Most work has been evaluated using text-based similarity metrics, which only indicate that there have been improvements, without explaining what has improved. In this paper, we present a detailed error analysis of the descriptions generated by a state-of-the-art attention-based model. Our analysis operates on two levels: first we check the descriptions for accuracy, and then we categorize the types of errors we observe in the inaccurate descriptions. We find only 20% of the descriptions are free from errors, and surprisingly that 26% are unrelated to the image. Finally, we manually correct the most frequently occurring error types (e.g. gender identification) to estimate the performance reward for addressing these errors, observing gains of 0.2--1 BLEU point per type.
Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1

A new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the Shannon limit, is discussed. The turbo-code encoder is built using a parallel concatenation of two recursive systematic convolutional codes, and the associated decoder, using a feedback decoding rule, is implemented as P pipelined identical elementary decoders. <<ETX>>
Distributed ILU(0) and SOR Preconditioners for Unstructured Sparse Linear Systems

There are two common ways of implementing ILU or (S)SOR preconditioned Krylov subspace methods on parallel computers. The rst resorts to multicoloring of the adjacency graph and often results in a parallelism of order N, where N is the dimension of the matrix. This strategy sometimes suuers from the deterioration of the rate of convergence. The second technique exploits the intrinsic parallelism available in the original forward and backward solutions. This approach does not suuer from the deterioration of the convergence rate since the resulting algorithm is mathematically equivalent to the original one. On the other hand, the maximum parallelism is limited by the length of the wavefronts which are often nonuniform. In this paper we consider the implementation of these two approaches on distributed memory computers and compare their performance on the CM-5. We have found that for the problems tested ILU(0) with multicoloring outperforms the other alternatives .
Munc18-1 Tuning of Vesicle Merger and Fusion Pore Properties

The release of hormones and neurotransmitters, mediated by regulated exocytosis, can be modified by regulation of the fusion pore. The fusion pore is considered stable and narrow initially, eventually leading to the complete merger of the vesicle and the plasma membranes. By using the high-resolution patch-clamp capacitance technique, we studied single vesicles and asked whether the Sec1/Munc18 proteins, interacting with the membrane fusion-mediating SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins, affect fusion pore properties. Munc18-1 mutants were transfected into lactotrophs to affect the interaction of Munc18-1 with syntaxin1 (Synt1) (R39C), Rab3A (E466K), and Mints (P242S). Compared with wild-type, Munc18-1 E466K increased the frequency of the fusion event. The latter two mutants increased the fusion pore dwell-time. All the mutants stabilized narrow fusion pores and increased the amplitude of fusion events, likely via preferential fusion of larger vesicles, since overexpression of Munc18-1 R39C did not affect the average size of vesicles, as determined by stimulated emission depletion (STED) microscopy. Single-molecule atomic force microscopy experiments revealed that wild-type Munc18-1, but not Munc18-1 R39C, abrogates the interaction between synaptobrevin2 (Syb2) and Synt1 binary trans-complexes. However, neither form of Munc18-1 affected the interaction of Syb2 with the preformed binary cis-Synt1A-SNAP25B complexes. This indicates that Munc18-1 performs a proofing function by inhibiting tethering of Syb2-containing vesicles solely to Synt1 at the plasmalemma and favoring vesicular tethering to the preformed binary cis-complex of Synt1A-SNAP25B. The association of Munc18-1 with the ternary SNARE complex leads to tuning of fusion pores via multiple and converging mechanisms involving Munc18-1 interactions with Synt1A, Rab3A, and Mints.
Doherty power amplifier behavioral models based on pruned Volterra series

In this paper, an efficient and effective pruned Volterra model is used to describe Doherty power amplifier. Rather than adopting the “black-box” approach, this model is derived from a physically scheme referring to the Doherty power amplifier. To model a Doherty power amplifier with nonlinearities and memory effects, the amplifier is analyzed by two parts in consideration of the influence between two amplifiers, while one is used to model the Class A or AB amplifier and the other to model Class C amplifier. With the Doherty amplifier tested, the proposed behavioral model is validated, and the corresponding experimental results achieve a good agreement with the desire output data.
Enrichment and Molecular Detection of Denitrifying Methanotrophic Bacteria of the NC10 Phylum

ABSTRACT Anaerobic methane oxidation coupled to denitrification was recently assigned to bacteria belonging to the uncultured phylum NC10. In this study, we incubated sediment from a eutrophic ditch harboring a diverse community of NC10 bacteria in a bioreactor with a constant supply of methane and nitrite. After 6 months, fluorescence in situ hybridization showed that NC10 bacteria dominated the resulting population. The enrichment culture oxidized methane and reduced nitrite to dinitrogen gas. We assessed NC10 phylum diversity in the inoculum and the enrichment culture, compiled the sequences currently available for this bacterial phylum, and showed that of the initial diversity, only members of one subgroup had been enriched. The growth of this subgroup was monitored by quantitative PCR and correlated to nitrite-reducing activity and the total biomass of the culture. Together, the results indicate that the enriched subgroup of NC10 bacteria is responsible for anaerobic methane oxidation coupled to nitrite reduction. Due to methodological limitations (a strong bias against NC10 bacteria in 16S rRNA gene clone libraries and inhibition by commonly used stopper material) the environmental distribution and importance of these bacteria could be largely underestimated at present.
Introducing Student Assessments with Evidence of Validity for NYC's CS4All

There are few assessments with strong evidence of validity for collecting data from students studying computer science (CS) education. Many of the assessments focus solely on students' attitudes and beliefs, or on curriculum. With the launch of NYC's CS4All initiative, there is a need for assessments that can be used at scale to measure CS outcomes across curricula and programs. This paper presents scales drawn from Panorama Education for collecting data from students, and the methodology used in creating and modifying those scales. The selected scales were modified, without undermining their evidence of validity, to measure students' perceptions of the pedagogical effectiveness and expectations and rigor of a CS teacher; and students' perceptions of their own interest in CS and engagement in their CS class. Following a discussion of the surveys and their modifications, data from an initial administration of the surveys are presented as a baseline for the community. Overall response data as well as cross-scale correlations are included. The paper concludes with a discussion of findings and how the surveys will be used in the future in NYC.
Assisting cognitively impaired nursing home residents with bathing: effects of two bathing interventions on caregiving.

PURPOSE When cognitively impaired nursing home residents exhibit agitated and aggressive behaviors during bathing, nursing home caregivers are in a unique position to improve residents' experience. This report addresses whether certified nursing assistants (CNAs) who received training in a person-centered approach with showering and with the towel bath showed improved caregiving behaviors (gentleness and verbal support) and experienced greater preparedness (confidence and ease) and less distress (hassles) when assisting residents with bathing. DESIGN AND METHODS We used a crossover design and randomized 15 nursing homes into two treatment groups and a control group of 5 facilities each. In one treatment group, CNAs received person-centered training, first with showering for 6 weeks (Time 1) and then with the towel bath for 6 weeks (Time 2). We reversed the treatment order in the other treatment group. Control group CNAs used usual showering procedures without person-centered training. We collected observational and self-report data at baseline and at the end of Time 1 and Time 2 on five caregiving outcomes. We analyzed data from 37 CNAs assisting 69 residents by using 3x2 repeated measures analyses of variance to compare the three groups on change from baseline. RESULTS Compared with the control group, treatment groups significantly improved in the use of gentleness and verbal support and in the perception of ease. IMPLICATIONS A person-centered approach with showering and with the towel bath improved not only how care is given to residents who become agitated and aggressive during bathing but also how CNAs perceive their experience when bathing these residents.
Remote Sensing Image Fusion Based on Wavelet Techniques

There is incompatibility between spatial characteristic enhancement and spectral information preservation in remote sensing image fusion. We propose an image fusion algorithm to reduce this incompatibility. It is based on Intensity-Hue-Saturation (IHS) and regularization in wavelet domain. For the high-resolution intensity image, the proposed approach assumes a wavelet domain local Gaussian model as prior distribution of the spectral characteristic, an Symmetric Conditional Markov(SCM) model as prior distribution of the spatial correlation, whose parameters are learnt from the analysis of the corresponding Pan wavelet coefficients. The constrained optimization problem is solved with the gradient descent algorithm. Visual and statistical results obtained by using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) images demonstrate that the proposed method can improve the spatial characteristic while preserving the spectral information effectively