Miracle-dz/UniFAR-FTUs huggingface dataset:
The MUR3 Gene of Arabidopsis Encodes a Xyloglucan Galactosyltransferase That Is Evolutionarily Related to Animal Exostosins Article, publication date, and citation information can be found at www.plantcell.org/cgi/doi/10.1105/tpc.009837.

Xyloglucans are the principal glycans that interlace cellulose microfibrils in most flowering plants. The mur3 mutant of Arabidopsis contains a severely altered structure of this polysaccharide because of the absence of a conserved α-l-fucosyl-(1→2)-β-d-galactosyl side chain and excessive galactosylation at an alternative xylose residue. Despite this severe structural alteration, mur3 plants were phenotypically normal and exhibited tensile strength in their inflorescence stems comparable to that of wild-type plants. The MUR3 gene was cloned positionally and shown to encode a xyloglucan galactosyltransferase that acts specifically on the third xylose residue within the XXXG core structure of xyloglucan. MUR3 belongs to a large family of type-II membrane proteins that is evolutionarily conserved among higher plants. The enzyme shows sequence similarities to the glucuronosyltransferase domain of exostosins, a class of animal glycosyltransferases that catalyze the synthesis of heparan sulfate, a glycosaminoglycan with numerous roles in cell differentiation and development. This finding suggests that components of the plant cell wall and of the animal extracellular matrix are synthesized by evolutionarily related enzymes even though the structures of the corresponding polysaccharides are entirely different from each other.
Space-time block coding and receive diversity for WLAN IEEE 802.11b

In this paper, we investigate time-reversal space-time block codes (TR-STBCs) and receive diversity for complementary code keying (CCK) modulation, which is employed in the wireless local area network (WLAN) standard IEEE 802.11b. The construction of TR-STBCs from orthogonal space-time block codes designed for flat fading channels for an arbitrary number of transmit antennas is discussed. Furthermore, an equivalent single-input single-output (SISO) transmission model for CCK is derived, which combines the effects of space-time coding and multiple receive antennas. For indoor multipath fading channels numerical results are provided for TR-STBCs with two and three transmit antennas, which demonstrate that significant gains can be obtained compared to a SISO transmission. For detection, decision-feedback equalization (DFE) and reduced-state sequence estimation (RSSE) especially tailored for CCK transmission are considered.
A multi-layer perceptron based non-linear mixture model to estimate class abundance from mixed pixels

Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.
Using Process-Level Redundancy to Exploit Multiple Cores for Transient Fault Tolerance

Transient faults are emerging as a critical concern in the reliability of general-purpose microprocessors. As architectural trends point towards multi-threaded multi-core designs, there is substantial interest in adapting such parallel hardware resources for transient fault tolerance. This paper proposes a software-based multi-core alternative for transient fault tolerance using process-level redundancy (PLR). PLR creates a set of redundant processes per application process and systematically compares the processes to guarantee correct execution. Redundancy at the process level allows the operating system to freely schedule the processes across all available hardware resources. PLR's software-centric approach to transient fault tolerance shifts the focus from ensuring correct hardware execution to ensuring correct software execution. As a result, PLR ignores many benign faults that do not propagate to affect program correctness. A real PLR prototype for running single-threaded applications is presented and evaluated for fault coverage and performance. On a 4-way SMP machine, PLR provides improved performance over existing software transient fault tolerance techniques with 16.9% overhead for fault detection on a set of optimized SPEC2000 binaries.
On Penalising Late Arrival of Relevant Documents in Information Retrieval Evaluation with Graded Relevance

Large-scale information retrieval evaluation efforts such as TREC and NTCIR have tended to adhere to binary-relevance evaluation metrics, even when graded relevance data were available. However, the NTCIR-6 Crosslingual Task has finally started adopting graded-relevance metrics, though only as additional metrics. This paper compares three existing graded-relevance metrics that were mentioned in the Call for Participation of the NTCIR-6 Crosslingual Task in terms of the ability to control how severely “late arrival” of relevant documents should be penalised. We argue and demonstrate that Q-measure is more flexible than normalised Discounted Cumulative Gain and generalised Average Precision. We then suggest a brief guideline for conducting a reliable information retrieval evaluation with graded relevance.
Lateral minimally invasive percutaneous osteosynthesis in humeral fractures

Abstract Introduction: The aim of this study is to evaluate retrospectively the functional and radiological results and the immediate and long-term post-operative complications in a series of patients with humeral fracture treated with osteosynthesis with minimally invasive techniques. Materials and methods: Retrospective multi-center study. We evaluated 14 patients (7 females and 7 males aged 48.7 years old on average [ranging from 21 to 73]) with humeral fracture that was subject to lateral minimally invasive osteosynthesis techniques with plates between 2007 and 2013. As stated by the AO classification, fractures were 12A1 (n = 1), 12B1 (n = 1), 12B2 (n = 3), 12C1 (n = 6), 12C2 (n = 1), and 12C3 (n = 2). We performed two lateral approaches, one proximal and the other one distal; the plate was slid through a submuscular canal, and the radial nerve was protected. Results: Average follow-up was 30 years. We got fracture healing in 13 cases (92.85%); average time before fracture healing was 3 months (ranging from 2 to 6). Average shoulder flexion was 174.8o; external rotation, 67.2o; abduction, 173.8o; and internal rotation, 72.1o. The average elbow flexion-extension arch was of 140.5o. Average Constant test was 82.66 marcks. Average DASH was 15.27 marks. Four patients (23.5%) showed radial neuropraxia. Conclusions: Osteosynthesis with percutaneous plating by minimally invasive approach has proved to be an efficient method for the treatment of humeral diaphyseal fractures applying the principle of bridge plating. It is a biological, technically demanding and not-free from complications procedure.
Chest Compression Rates During Cardiopulmonary Resuscitation Are Suboptimal: A Prospective Study During In-Hospital Cardiac Arrest

Background—Recent data highlight a vital link between well-performed cardiopulmonary resuscitation (CPR) and survival after cardiac arrest; however, the quality of CPR as actually performed by trained healthcare providers is largely unknown. We sought to measure in-hospital chest compression rates and to determine compliance with published international guidelines. Methods and Results—We developed and validated a handheld recording device to measure chest compression rate as a surrogate for CPR quality. A prospective observational study of adult cardiac arrests was performed at 3 hospitals from April 2002 to October 2003. Resuscitations were witnessed by trained observers using a customized personal digital assistant programmed to store the exact time of each chest compression, allowing offline calculation of compression rates at serial time points. In 97 arrests, data from 813 minutes during which chest compressions were delivered were analyzed in 30-second time segments. In 36.9% of the total number of segments, compression rates were <80 compressions per minute (cpm), and 21.7% had rates <70 cpm. Higher chest compression rates were significantly correlated with initial return of spontaneous circulation (mean chest compression rates for initial survivors and nonsurvivors, 90±17 and 79±18 cpm, respectively; P=0.0033). Conclusions—In-hospital chest compression rates were below published resuscitation recommendations, and suboptimal compression rates in our study correlated with poor return of spontaneous circulation. CPR quality is likely a critical determinant of survival after cardiac arrest, suggesting the need for routine measurement, monitoring, and feedback systems during actual resuscitation.
A multi-resolution approach to learning with overlapping communities

The recent few years have witnessed a rapid surge of participatory web and social media, enabling a new laboratory for studying human relations and collective behavior on an unprecedented scale. In this work, we attempt to harness the predictive power of social connections to determine the preferences or behaviors of individuals such as whether a user supports a certain political view, whether one likes one product, whether he/she would like to vote for a presidential candidate, etc. Since an actor is likely to participate in multiple different communities with each regulating the actor's behavior in varying degrees, and a natural hierarchy might exist between these communities, we propose to zoom into a network at multiple different resolutions and determine which communities are informative of a targeted behavior. We develop an efficient algorithm to extract a hierarchy of overlapping communities. Empirical results on several large-scale social media networks demonstrate the superiority of our proposed approach over existing ones without considering the multi-resolution or overlapping property, indicating its highly promising potential in real-world applications.
Hybrid spiking models

I review a class of hybrid models of neurons that combine continuous spike-generation mechanisms and a discontinuous ‘after-spike’ reset of state variables. Unlike Hodgkin–Huxley-type conductance-based models, the hybrid spiking models have a few parameters derived from the bifurcation theory; instead of matching neuronal electrophysiology, they match neuronal dynamics. I present a method of after-spike resetting suitable for hardware implementation of such models, and a hybrid numerical method for simulations of large-scale biological spiking networks.
The Electroencephalogram: Its Patterns and Origins

Part 1 The hypothesis and methods of testing it - simulation results: the hypothesis and the oscillator model approaches, methods, and EEG database for testing the hypothesis simulation of EEG patterns. Part 2 Tests of predictions from the hypothesis for normal and abnormal EEGs: the waking EEG the normal EEG during sleep normal and abnormal random slowing in the waking state epileptiform patterns reconstitution of EEGs from extrema and slopes appraisal and revision of the extrema-slopes hypothesis on the basis of tests. Part 3 Appraisal of the hypothesis in relation to anatomy, physiology, and pathophysiology of the EEG - other models - overall appraisal: some aspects of neocortical anatomy the physiological basis of the EEG pathophysiology of the EEG other models of the EEG, and related models comparisons with some other models of the EEG the significance of the extrema-slopes hypothesis - a formulation implications for, and applications to, computerized EEG analysis limitations of the scope of the present work a methodological note on the Wiener Clock hypothesis for the alpha rhythm resume. Part 4 Technological chapters: introduction to technological chapters the oscillator model precision full-wave rectifier, transversal filter, tapped delay line basic measures derived measures photo-optical scanner for data retrieval from EEG ink recordings time-scale converter ("Time Machine") random-noise generators instantaneous envelopes of the EEG and of its first derivative, interfacing with the oscillator model. Appendices: some traditional methods of EEG analysis - on-line real-time analog implementation eliminating or minimizing artifact by paired sampling and by coherent rejection analog adaptive signal processing placement of scalp electrodes.
Composite Polylactic-Methacrylic Acid Copolymer Nanoparticles for the Delivery of Methotrexate

The purpose of this study was to develop poly(lactic acid)-methacrylic acid copolymeric nanoparticles with the potential to serve as nanocarrier systems for methotrexate (MTX) used in the chemotherapy of primary central nervous system lymphoma (PCNSL). Nanoparticles were prepared by a double emulsion solvent evaporation technique employing a 3-Factor Box-Behnken experimental design strategy. Analysis of particle size, absolute zeta potential, polydispersity (Pdl), morphology, drug-loading capacity (DLC), structural transitions through FTIR spectroscopy, and drug release kinetics was undertaken. Molecular modelling elucidated the mechanisms of the experimental findings. Nanoparticles with particle sizes ranging from 211.0 to 378.3 nm and a recovery range of 36.8–86.2 mg (Pdl ≤ 0.5) were synthesized. DLC values were initially low (12 ± 0.5%) but were finally optimized to 98 ± 0.3%. FTIR studies elucidated the comixing of MTX within the nanoparticles. An initial burst release (50% of MTX released in 24 hours) was obtained which was followed by a prolonged release phase of MTX over 84 hours. SEM images revealed near-spherical nanoparticles, while TEM micrographs revealed the presence of MTX within the nanoparticles. Stable nanoparticles were formed as corroborated by the chemometric modelling studies undertaken.
Effects of stress during pregnancy on hepatic glucogenic capacity in rat dams and their fetuses

Stress during pregnancy is associated with metabolic dysfunction in the adult offspring in human and other animals. However, little is known about the metabolic effects of pregnancy stress on the mothers and fetuses during pregnancy itself. This study aimed to determine the consequences of the common experimental procedures of injection and single housing in pregnant rats on fetal and maternal hepatic glucogenic capacities. On day (D) 20 of pregnancy, feto‐placental weights and the glycogen content and activities of phosphoenolpyruvate carboxykinase (PEPCK) and glucose‐6‐phosphatase (G6Pase) of fetal and maternal liver were measured in rats pair or single housed from D1 with or without saline injection from D15 to D19. Housing and saline injection both affected hepatic glucogenic capacity. In maternal liver, saline injection but not housing reduced glycogen content and raised G6Pase activity, whereas housing but not treatment increased PEPCK activity. In fetuses, housing and injection interacted in regulating PEPCK activity and reducing hepatic glycogen content and placental weight. Body weight was decreased and hepatic G6Pase increased by injection but not housing in the fetuses. Single‐housed dams ate less than those pair‐housed near term while saline injection elevated maternal plasma corticosterone concentrations. Thus, single housing and saline injection are both stresses during rat pregnancy that alter feto‐placental weight and hepatic glucogenic capacity of the fetuses and dams near term. Routine experimental procedures per se may, therefore, have consequences for offspring hepatic phenotype as well as modifying the outcomes of dietary and other environmental challenges during pregnancy.
A Review & Analysis of Mindfulness Research in HCI: Framing Current Lines of Research and Future Opportunities

Mindfulness is a term seen with increasing frequency in HCI literature, and yet the term itself is used almost as variously as the number of papers in which it appears. This diversity makes comparing or evaluating HCI approaches around mindfulness or understanding the design space itself a challenging task. We conducted a structured ACM literature search based on the term mindfulness. Our selection process yielded 38 relevant papers, which we analyzed for their definition, motivation, practice, evaluation and technology use around mindfulness. We identify similarities, divergences and areas of interest for each aspect, resulting in a framework composed of four perspectives and seven lines of research. We highlight challenges and opportunities for future HCI research and design.
Hypnosis Modulates Activity in Brain Structures Involved in the Regulation of Consciousness

The notion of consciousness is at the core of an ongoing debate on the existence and nature of hypnotic states. Previously, we have described changes in brain activity associated with hypnosis (Rainville, Hofbauer, Paus, Duncan, Bushnell, & Price, 1999). Here, we replicate and extend those findings using positron emission tomography (PET) in 10 normal volunteers. Immediately after each of 8 PET scans performed before (4 scans) and after (4 scans) the induction of hypnosis, subjects rated their perceived level of mental relaxation and mental absorption, two of the key dimensions describing the experience of being hypnotized. Regression analyses between regional cerebral blood flow (rCBF) and self-ratings confirm the hypothesized involvement of the anterior cingulate cortex (ACC), the thalamus, and the ponto-mesencephalic brainstem in the production of hypnotic states. Hypnotic relaxation further involved an increase in occipital rCBF that is consistent with our previous interpretation that hypnotic states are characterized by a decrease in cortical arousal and a reduction in cross-modality suppression (disinhibition). In contrast, increases in mental absorption during hypnosis were associated with rCBF increases in a distributed network of cortical and subcortical structures previously described as the brain's attentional system. These findings are discussed in support of a state theory of hypnosis in which the basic changes in phenomenal experience produced by hypnotic induction reflect, at least in part, the modulation of activity within brain areas critically involved in the regulation of consciousness.
Abstractions for Narrative Comprehension Tasks

This paper presents ongoing work in investigating the scale at which semantic abstractions are useful in intelligent reasoning about narrative. One method of evaluating narrative reasoning is to use comprehension tests on stories based on question-answering. Recent advances in language processing have led to promising results in general question-answering. However, current systems fail to accurately answer questions when information is not explicitly mentioned in the input story. Speciﬁcally, we are interested in testing whether corpus-based deep learning methods can be extended with classical logic-based approaches to draw inferences beyond ones that are explicitly mentioned in sentences on the corpus. This paper describes a preliminary re-implementation of current methods on the bAbI corpus for question-answering and then presents an algorithm for reasoning about missing information in the input by removing sentences from the corpus.
Antitumor Activity of Gefitinib in Malignant Rhabdoid Tumor Cells In vitro and In vivo

Purpose: Malignant rhabdoid tumor (MRT) is a rare and highly aggressive neoplasm of young children. Current treatments have had only limited success. Epidermal growth factor receptor (EGFR) was found recently to be expressed on MRT cell lines. Gefitinib (trade name Iressa) is an oral and selective EGFR-tyrosine kinase inhibitor and has been demonstrated to be effective in inhibiting the proliferation of cancer cells in vivo as well as in clinical trials. This encouraged us to examine the antitumor effects of gefitinib on MRT cells in vitro and in vivo. Experimental Design: The expression of EGFR in two MRT tumors and two MRT cell lines (MP-MRT-AN and KP-MRT-NS), established from these two tumor tissues, was examined by immunohistochemistry, immunofluorescence, and immunoblot. The effect of gefitinib on EGFR phosphorylation was examined by immunoblot. The effects of gefitinib on cell growth and apoptosis were examined by cell growth assay and terminal deoxynucleotidyl transferase-mediated nick end labeling assay. The in vivo effect of gefitinib was assessed in athymic mice that had been xenografted with MRT cells. Results: The expression of EGFR was detected in both tumor tissues and cell lines. Gefitinib inhibited EGFR-phosphorylation (IC50 < 0.1 μmol/L) and in vitro cell growth (IC50 = approximately 10–12 μmol/L), and a high concentration of gefitinib (20 μmol/L) induced apoptosis in vitro (MP-MRT-AN, 42.9% and KP-MRT-NS, 47.2%). Furthermore, gefitinib at 150 mg/kg had a cytostatic effect on established MRT xenografts (MP-MRT-AN, P = 0.039 and 0.0014; and KP-MRT-NS, P = 0.048 and 0.0086). Conclusions: Our results demonstrate that gefitinib has antitumor effects in MRT cells in vitro and in vivo and, thus, has promise as a novel and therapeutic strategy for MRT.
AN AVIAN INFLUENZA MODEL AND ITS FIT TO HUMAN AVIAN INFLUENZA CASES

Low Pathogenic Avian Influenza (LPAI) virus, which circulates in wild bird populations in mostly benign form, is suspected to have mutated into a highly pathogenic (HPAI) strain after transmission to the domestic birds. HPAI has recently garnered worldwide attention because of the “spillover” infection of this strain from domestic birds to humans primarily those in poultry industry causing significant human fatality and thus creating potentially favorable conditions for another flu pandemic. We use an ordinary differential equation model to describe this complex dynamics of the HPAI virus, which epidemiologically links a number of species in a multi-species community. We include the wild bird population as a periodic source feeding infection to the coupled domestic bird-human system. We also account for mutation between the low and high pathogenic strains. Finally, we fit our model to the actual number of human avian influenza cases obtained from WHO, and estimate the relevant reproduction numbers. We discuss open questions and problems in modeling the complex epidemiology of avian influenza.