Miracle-dz/UniFAR-FTUs huggingface dataset:
Subtree power analysis and species selection for comparative genomics

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. Analysis of a phylogenetic star topology shows theoretically that the optimal species subset is not in general the most evolutionarily diverged subset. We then demonstrate this finding empirically in a study of vertebrate species. Our results suggest that marsupials are prime sequencing candidates.
Relationship Between Clinical Assessments of Function and Measurements From an Upper-Limb Robotic Rehabilitation Device in Cervical Spinal Cord Injury

Upper limb robotic rehabilitation devices can collect quantitative data about the user's movements. Identifying relationships between robotic sensor data and manual clinical assessment scores would enable more precise tracking of the time course of recovery after injury and reduce the need for time-consuming manual assessments by skilled personnel. This study used measurements from robotic rehabilitation sessions to predict clinical scores in a traumatic cervical spinal cord injury (SCI) population. A retrospective analysis was conducted on data collected from subjects using the Armeo Spring (Hocoma, AG) in three rehabilitation centers. Fourteen predictive variables were explored, relating to range-of-motion, movement smoothness, and grip ability. Regression models using up to four predictors were developed to describe the following clinical scores: the GRASSP (consisting of four sub-scores), the ARAT, and the SCIM. The resulting adjusted R^2 value was highest for the GRASSP “Quantitative Prehension” component (0.78), and lowest for the GRASSP “Sensibility” component (0.54). In contrast to comparable studies in stroke survivors, movement smoothness was least beneficial for predicting clinical scores in SCI. Prediction of upper-limb clinical scores in SCI is feasible using measurements from a robotic rehabilitation device, without the need for dedicated assessment procedures.
Nursing perceptions of patient safety climate in the Gaza Strip, Palestine

AIMS This study was undertaken to assess the perception of nurses about patient safety culture and to test whether it is significantly affected by the nurses' position, age, experience and working hours. BACKGROUND Patient safety has sparked the interest of healthcare mangers, yet there is limited knowledge about the current patient safety culture among nurses in the Gaza Strip. METHODS This was a descriptive cross-sectional study, administering the Arabic Safety Attitude Questionnaire (Short Form 2006) to 210 nurses in four public general hospitals. RESULTS Job Satisfaction was the most highly perceived factor affecting patient safety, followed by Perception of Management. Safety culture varied across nursing position, age, work experience and working hours. Nurse Managers had more positive attitudes towards patients than frontline clinicians did. The more experience nurses had, the better their attitudes towards patient safety. Nurses who worked the minimum weekly required hours and who were 35 years and older had better attitudes towards all patient safety dimensions except for Stress Recognition. Nurses with a positive attitude had better collaboration with healthcare professionals than those without a positive attitude. LIMITATION Generalization is limited, as nurses who worked in private and specialized hospitals were excluded. CONCLUSION Evaluation of the safety culture is the essential starting point to identify hindrances or drivers for safe patient care. Job Satisfaction, Perception of Management and Teamwork necessitate reinforcement, while Working Conditions, Stress Recognition and Safety Climate require improvement. IMPLICATIONS FOR NURSING AND HEALTH POLICY Ensuring job satisfaction through adequate staffing levels, providing incentives and maintaining a collegial environment require both strategic planning and institutional policies at the higher administrative level. Creation of a non-punitive and learning environment, promoting open communication and fostering continuous education should be fundamental aspects of hospital management. A policy of mixing experienced nurses with inexperienced nurses should be considered.
Associative memory by recurrent neural networks with delay elements

The synapses of real neural systems seem to have delays. Therefore, it is worthwhile to analyze associative memory models with delayed synapses. Thus, a sequential associative memory model with delayed synapses is discussed, where a discrete synchronous updating rule and a correlation learning rule are employed. Its dynamic properties are analyzed by the statistical neurodynamics. In this paper, we first re-derive the Yanai-Kim theory, which involves macrodynamical equations for the dynamics of the network with serial delay elements. Since their theory needs a computational complexity of /spl Oscr/(L/sup 4/t) to obtain the macroscopic state at time step t where L is the length of delay, it is intractable to discuss the macroscopic properties for a large L limit. Thus, we derive steady state equations using the discrete Fourier transformation, where the computational complexity does not formally depend on L. We show that the storage capacity /spl alpha//sub C/ is in proportion to the delay length L with a large L limit, and the proportion constant is 0.195, i.e., /spl alpha//sub C/=0.195 L. These results are supported by computer simulations.
WAS Control Center: an autonomic performance-triggered tracing environment for Websphere

Studying any aspect of an application server with high availability requirements can become a tedious task when a continuous monitoring of the server status is necessary. The creation of performance-driven autonomic systems can hurry up the analysis of this kind of complex systems. In this paper we present an autonomic performance-driven environment for WebSphere application server that can be used as the basis to construct systems that must monitor the performance of the system. As an applied use of this infrastructure, we present the WAS Control Center which is a deep tracing tool-set for 24/spl times/7 environments. It exploits the benefits of autonomic computing to lighten the costs of highly detailed system tracing on a J2EE application server. The WAS Control Center is helping us in the creation of performance models of the WebSphere application server.
Survivable Information Storage Systems

As society increasingly relies on digitally stored and accessed information, supporting the availability, integrity and confidentiality of this information is crucial. We need systems in which users can securely store critical information, ensuring that it persists, is continuously accessible, cannot be destroyed and is kept confidential. A survivable storage system would provide these guarantees over time and despite malicious compromises of storage node subsets. The PASIS architecture flexibly and efficiently combines proven technologies (decentralized storage system technologies, data redundancy and encoding, and dynamic self-maintenance) for constructing information storage systems whose availability, confidentiality and integrity policies can survive component failures and malicious attacks.
Purification, amplification and characterization of a population of human erythroid progenitors

In humans, studies of the erythroid cell lineage are hampered by difficulties in obtaining sufficient numbers of erythroid progenitors. In fact, these progenitors in bone marrow or peripheral blood are scarce and no specific antibodies are available. We describe a new method which allows proliferation in liquid culture of large numbers of pure normal human erythroid progenitors. CD34+ cells were cultured for 7 d in serum‐free conditions with the cytokine mixture interleukin (IL)‐3/IL‐6/stem cell factor (SCF). This resulted in cell expansion and the appearance of a high proportion of CD36+ cells which were purified on day 7. Methylcellulose clones from these cells were composed of 96.6% late BFU‐E and 3.4% CFU‐GM. These CD36+ cells could be recultured with the same cytokine mixture plus or minus erythropoietin (Epo) for a further 2–7 d. In both conditions further amplification of CD36+ cells was observed, but Epo induced a more dramatic cell expansion. Glycophorin‐positive mature cells appeared only in the presence of Epo, and terminal red cell differentiation was observed after 7 d of secondary culture. Cells obtained from adult CD34+ progenitors mostly contained adult haemoglobin, whereas cord blood‐derived cells contained equal proportions of adult and fetal haemoglobin. Activation of STAT5 and tyrosine phosphorylation of the Epo receptor and JAK2 were observed after Epo stimulation of these cells. This new method represents a straightforward alternative to the procedures previously described for the purification of normal erythroid progenitors and is useful in the study of erythropoietic regulation.
Developmental and Cell Cycle Progression Defects in Drosophila Hybrid Males

Matings between D. melanogaster females and males of sibling species in the D. melanogaster complex yield hybrid males that die prior to pupal differentiation. We have reexamined a previous report suggesting that the developmental defects in these lethal hybrid males reflect a failure in cell proliferation that may be the consequence of problems in mitotic chromosome condensation. We also observed a failure in cell proliferation, but find in contrast that the frequencies of mitotic figures and of nuclei staining for the mitotic marker phosphohistone H3 in the brains of hybrid male larvae are extremely low. We also found that very few of these brain cells in male hybrids are in S phase, as determined by BrdU incorporation. These data suggest that cells in hybrid males are arrested in either the G1 or G2 phases of the cell cycle. The cells in hybrid male brains appear to be particularly sensitive to environmental stress; our results indicate that certain in vitro incubation conditions induce widespread cellular necrosis in these brains, causing an abnormal nuclear morphology noted by previous investigators. We also document that hybrid larvae develop very slowly, particularly during the second larval instar. Finally, we found that the frequency of mitotic figures in hybrid male larvae mutant for Hybrid male rescue (Hmr) is increased relative to lethal hybrid males, although not to wild-type levels, and that chromosome morphology in Hmr− hybrid males is also not completely normal.
HYMAC: Hybrid TDMA/FDMA Medium Access Control Protocol for Wireless Sensor Networks

We describe HyMAC, a new hybrid MAC layer protocol for wireless sensor networks that is, to the best of our knowledge, the first effort to combine the strengths of both TDMA and FDMA schemes in these constrained networks. While allowing the network to operate in an energy-efficient collision-free manner, HyMAC takes advantage of the multiple frequencies provided in the radio component of recent sensor node hardware platforms such as MICAZ, TELOS and FireFly. We show how HyMAC outperforms protocols such as B-MAC, RT-Link and MMSN achieving high throughput and small bounded end- to-end delay suitable for newer types of sensor network applications such as real-time voice streaming.
A Compositional Perspective in Convolution Kernels

Kernel-based learning has been largely adopted in many semantic textual inference tasks. In particular, Tree Kernels (TKs) have been successfully applied in the modeling of syntactic similarity between linguistic instances in Question Answering or Information Extraction tasks. At the same time, lexical semantic information has been studied through the adoption of the so-called Distributional Semantics (DS) paradigm, where lexical vectors are acquired automatically from large-scale corpora. Recently, Compositional Semantics phenomena arising in complex linguistic structures have been studied in an extended paradigm called Distributional Compositional Semantics (DCS), where, for example, algebraic operators on lexical vectors have been defined to account for grammatically typed bi-grams or complex verb or noun phrases. In this paper, a novel kernel called Compositionally Smoothed Partial Tree Kernel is presented to integrate DCS operators into the tree kernel evaluation by also considering complex compositional nodes. Empirical results on well-known NLP tasks show that state-of-the-art performances can be achieved, without resorting to manual feature engineering, thus suggesting that a large set of Web and text mining tasks can be handled successfully by this kernel.
Performance evaluation of forwarding protocols for the RACUN network

In this paper, we discuss the performance of different network protocols for RACUN, a European Defence Agency project with the objective of demonstrating ad hoc underwater networks for multiple purposes related to security. The RACUN network is designed for long-range communications over areas of large size, hence a very important role is played by the network protocols employed. We show that the channel realizations observed in typical scenarios and the physical layer schemes available in the project lead to significant bit error rates. Therefore, the protocols that offer some inherent form of redundancy, as in the case of flooding-based protocols, tend to yield better performance than protocols based on the exchange of signaling traffic. In support of this statement, we simulate two scenarios for the RACUN network over channel realizations that are statistically derived from real channel measurements. Our results provide insight on the advantages and drawbacks of the different packet forwarding strategies, and confirm that flooding-based approaches perform better. In addition, we prove how splitting packets into multiple fragments to match the modem's maximum service data unit significantly limits the performance.
Falsification of temporal properties of hybrid systems using the cross-entropy method

Randomized testing is a popular approach for checking properties of large embedded system designs. It is well known that a uniform random choice of test inputs is often sub-optimal. Ideally, the choice of inputs has to be guided by choosing the right input distributions in order to expose corner-case violations. However, this is also known to be a hard problem, in practice. In this paper, we present an application of the cross-entropy method for adaptively choosing input distributions for falsifying temporal logic properties of hybrid systems. We present various choices for representing input distribution families for the cross-entropy method, ranging from a complete partitioning of the input space into cells to a factored distribution of the input using graphical models. Finally, we experimentally compare the falsification approach using the cross-entropy method to other stochastic and heuristic optimization techniques implemented inside the tool S-Taliro over a set of benchmark systems. The performance of the cross entropy method is quite promising. We find that sampling inputs using the cross-entropy method guided by trace robustness can discover violations faster, and more consistently than the other competing methods considered.
Automatic writer identification using connected-component contours and edge-based features of uppercase Western script

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO/sup 3/s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected components for the uppercase character set. Using a codebook of CO/sup 3/s from an independent training set of 100 writers, the probability-density function (PDF) of CC's was computed for an independent test set containing 150 unseen writers. Results revealed a high-sensitivity of the CO/sup 3/ PDF for identifying individual writers on the basis of a single sentence of uppercase characters. The proposed automatic approach bridges the gap between image-statistics approaches on one end and manually measured allograph features of individual characters on the other end. Combining the CO/sup 3/ PDF with an independent edge-based orientation and curvature PDF yielded very high correct identification rates.
Hierarchical Recognition of Propositional Arguments with Perceptrons

We describe a system for the CoNLL-2004 Shared Task on Semantic Role Labeling (Carreras and Màrquez, 2004a). The system implements a two-layer learning architecture to recognize arguments in a sentence and predict the role they play in the propositions. The exploration strategy visits possible arguments bottom-up, navigating through the clause hierarchy. The learning components in the architecture are implemented as Perceptrons, and are trained simultaneously online, adapting their behavior to the global target of the system. The learning algorithm follows the global strategy introduced in (Collins, 2002) and adapted in (Carreras and Màrquez, 2004b) for partial parsing tasks.
The computational nature of phonological generalizations

This chapter studies the nature of the typology of phonological markedness constraints and the nature of the typology of the transformation from underlying to surface forms from a computational perspective. It argues that there are strong computational laws that constrain the form of these constraints and transformations. These laws are currently stated most clearly in terms of the so-called subregular hierarchies, which have been established for stringsets (for modeling constraints) and are currently being established for string-to-string maps (for modeling the transformations). It is anticipated that future research will reveal equally powerful laws applicable to non-string-based representations. Finally, this chapter argues that these laws arise as a natural consequence of how humans generalize from data.
Dissecting mechanisms of brain aging by studying the intrinsic excitability of neurons

Several studies using vertebrate and invertebrate animal models have shown aging associated changes in brain function. Importantly, changes in soma size, loss or regression of dendrites and dendritic spines and alterations in the expression of neurotransmitter receptors in specific neurons were described. Despite this understanding, how aging impacts intrinsic properties of individual neurons or circuits that govern a defined behavior is yet to be determined. Here we discuss current understanding of specific electrophysiological changes in individual neurons and circuits during aging.
Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.
Automatic Image Completion with Structure Propagation and Texture Synthesis

In this paper, we present a novel automatic image completion solution in a greedy manner inspired by a primal sketch representation model. Firstly, an image is divided into structure (sketchable) components and texture (non-sketchable) components, and the missing structures, such as curves and corners, are predicted by tensor voting. Secondly, the textures along structural sketches are synthesized with the sampled patches of some known structure components. Then, using the texture completion priorities decided by the confidence term, data term and distance term, the similar image patches of some known texture components are found by selecting a point with the maximum priority on the boundary of hole region. Finally, these image patches inpaint the missing textures of hole region seamlessly through graph cuts. The characteristics of this solution include: (1) introducing the primal sketch representation model to guide completion for visual consistency; (2) achieving fully automatic completion. The experiments on natural images illustrate satisfying image completion results.
An Optimal Control Approach to Minimizing Entropy Generation in an Adiabatic Internal Combustion Engine

Entropy generation due to combustion destroys as much as a third of the theoretical maximum work that could have been extracted from the fuel supplied to an engine. In this paper, an optimal control problem is set up to minimize the entropy generation in an adiabatic internal combustion engine. The optimal bang-bang control is shown to be a function of the pressure difference between the instantaneous thermodynamic state of the system and its corresponding equilibrium thermodynamic state. At optimality, the entropy difference between these two thermodynamic states is shown to be a Lyapunov function. Therefore, the equilibrium serves as the attractor for the optimal state trajectory. The results are independent of the underlying reaction mechanism, which may be highly nonlinear
Cardiovascular-Renal Mechanisms in Health and Disease Reactive oxygen species-selective regulation of aortic inflammatory gene expression in Type 2 diabetes

San Martı́n A, Du P, Dikalova A, Lassègue B, Aleman M, Góngora MC, Brown K, Joseph G, Harrison DG, Taylor WR, Jo H, Griendling KK. Reactive oxygen species-selective regulation of aortic inflammatory gene expression in Type 2 diabetes. Am J Physiol Heart Circ Physiol 292: H2073–H2082, 2007. First published January 19, 2007; doi:10.1152/ajpheart.00943. 2006. — Vascular diseases are a major complication of diabetes mellitus (DM), although their etiology is poorly understood. NADPH oxidase-derived reactive oxygen species (ROS) production and inflammation are potential mediators of DM-associated vascular diseases. Using db/db mice as a Type 2 diabetes model, we examined the relationship between NADPH oxidase-derived ROS and vascular inflammation. When compared with control m / mice, aortas from 4and 12-wk-old db/db mice had higher NADPH oxidase activity and increased superoxide levels, leading to NADPH oxidase-dependent impaired vasodilation at 12 wk. Diabetes progression from 4 to 12 wk led to increased Nox1, Nox4, and p22 subunit mRNAs and induced the expression of a group of matrix remodeling-related cytokines: connective tissue growth factor (CTGF), bone morphogenetic protein 4 (BMP-4), and osteopontin (OPN). After 8 wk of treatment with the superoxide scavenger Tempol, 12-wk-old db/db mice had lower superoxide production, reduced plasma glucose and lipids, and lower BMP-4 and OPN protein expression when compared with nontreated mice. No changes were observed with Tempol in CTGF or m / mice. The ability of Tempol to reverse ROS production as well as OPN and BMP-4, but not CTGF, induction suggests that DM-induced vascular inflammation involves both ROS-sensitive and -insensitive pathways.