Miracle-dz/UniFAR-FTUs huggingface dataset:
Cystathionine-gamma-lyase inhibitor attenuates acute lung injury induced by acute pancreatitis in rats

Introduction Acute pancreatitis (AP) is known to induce injuries to extrapancreatic organs. Because respiratory dysfunction is the main cause of death in patients with severe AP, acute pancreatitis-associated lung injury (APALI) is a great challenge for clinicians. This study aimed to investigate the potential role of hydrogen sulfide (H2S) in the pathogenesis of APALI. Material and methods Fifty-four SD rats were randomly divided into three groups: the AP group of rats that received injection of sodium deoxycholate into the common bile duct, the control group that underwent a sham operation, and the treatment group made by intraperitoneal injection of propargylglycine (PAG), an inhibitor of cystathionine-γ-lyase (CSE), into rats with AP. Histopathology of the lung was examined and the expression of CSE and TNF-α mRNA in lung tissue was detected by real-time polymerase chain reaction. The H2S level in the serum was detected spectrophotometrically. Results The serum concentration of H2S and CSE and TNF-α expression in the lung were increased in AP rats modeled after 3 h and 6 h than in control rats (p < 0.05). Intraperitoneal injection of PAG could reduce the serum concentration of H2S, reduce CSE and TNF-α expression, and alleviate the lung pathology (p < 0.05). Conclusions Taken together, our findings suggest that the H2S/CSE system is crucially involved in the pathological process of APALI and represents a novel target for the therapy of APALI.
New model of SaaS: SaaS with tenancy agency

SaaS is a new delivery model for the software development and application. Providers tend to make their SaaS products achieve higher level of maturity, serves more people, satisfy more different individual requirements, while maintaining efficiency and flexibility. This paper introduces a new SaaS application model called SaaS with tenancy agency. It adds two new layers: tenancy process layer and tenancy agency layer, to traditional SOA architecture. First, the system proposed in this paper splits the business process into unified elements, and handles these elements in the same actuator. The actuator focusing on repeated work reduces processes switching time and promotes efficiency. Second, the system combines these elements to tenancy processes to achieve customization of the process. Third, the system sets one tenancy agency for each group of tenants with similar requirements. In such architecture, agencies avoid being too huge and work with noninterference. Platform has been made to produce and run SaaS in this architecture. SaaS with tenancy agency is proved to be feasible.
Morphology and axonal projection patterns of individual neurons in the cat perigeniculate nucleus.

1. The lateral geniculate nucleus is the primary thalamic relay through which retinal signals pass en route to cortex. This relay is gated and can be suppressed by activity among local inhibitory neurons that use gamma-aminobutyric acid (GABA) as a neurotransmitter. In the cat, a major source of this GABAergic inhibition seems to arise from cells of the perigeniculate nucleus, which lies just dorsal to the A-laminae of the lateral geniculate nucleus. However, the morphological characteristics of perigeniculate cells, and particularly the projection patterns of their axons, have never been fully characterized. We thus examined the morphology of these cells: individually by intracellular injection of horseradish peroxidase (HRP) and en masse with the anterograde tracer Phaseolus vulgaris leucoagglutinin (PHAL). 2. We recorded from 12 perigeniculate cells that we impaled and successfully labeled with HRP. These cells exhibited response properties generally consistent with those described previously. They had long response latencies to stimulation of the optic chiasm and relatively large, often diffuse, receptive fields. The visually evoked responses of most of the cells were dominated by one eye. Compared with cells of the lateral geniculate nucleus, perigeniculate cells had large somata (517 +/- 136 microns 2 in cross-sectional area, mean +/- SD), which were fusiform or multipolar in shape, and dendritic arbors that extended a considerable distance (1,095 +/- 167 microns) parallel to the border between the perigeniculate and lateral geniculate nuclei. Terminal arbors of some dendrites were quite complex and beaded. 3. The axons of six perigeniculate cells were labeled sufficiently well to trace and reconstruct over a considerable distance. Each of these axons formed branches that descended to innervate the lateral geniculate nucleus, and this geniculate innervation was exclusively limited to the A-laminae. Terminal boutons within the A-laminae were nearly all en passant, which gave the axons a beaded appearance. Furthermore, branches of five of these six axons provided local innervation of the perigeniculate nucleus, generally within each labeled cell's own dendritic arbor. Three of the cells also exhibited an axon branch that extended medially and caudally away from the soma, but we were unable to trace these axon branches to their targets. 4. Within the lateral geniculate nucleus, each arbor of perigeniculate axons derived from two main components. One was a narrow, sparse medial component that innervated laminae A and A1. (ABSTRACT TRUNCATED AT 400 WORDS)
The Methodology and Practice of Econometrics

David F. Hendry is a seminal figure in modern econometrics. He has pioneered the LSE approach to econometrics, and his influence is wide ranging. This book is a collection of papers dedicated to him and his work. Many internationally renowned econometricians who have collaborated with Hendry or have been influenced by his research have contributed to this volume, which provides a reflection on the recent advances in econometrics and considers the future progress for the methodology of econometrics. Central themes of the book include dynamic modelling and the properties of time series data, model selection and model evaluation, forecasting, policy analysis, exogeneity and causality, and encompassing. The book strikes a balance between econometric theory and empirical work, and demonstrates the influence that Hendry's research has had on the direction of modern econometrics. Contributors include: Karim Abadir, Anindya Banerjee, Gunnar Bardsen, Andreas Beyer, Mike Clements, James Davidson, Juan Dolado, Jurgen Doornik, Robert Engle, Neil Ericsson, Jesus Gonzalo, Clive Granger, David Hendry, Kevin Hoover, Soren Johansen, Katarina Juselius, Steven Kamin, Pauline Kennedy, Maozu Lu, Massimiliano Marcellino, Laura Mayoral, Grayham Mizon, Bent Nielsen, Ragnor Nymoen, Jim Stock, Pravin Trivedi, Paolo Paruolo, Mark Watson, Hal White, and David Zimmer. Contributors to this volume - Karim Abadir, Imperial College London Anindya Banerjee, University of Birmingham Gunnar Bardsen, Norwegian University of Science and Technology Andreas Beyer, European Central Bank Mike Clements, University of Warwick James Davidson, University of Exeter Selva Demiralp, Koc University Juan Dolado, Universidad Carlos III de Madrid Jurgen Doornik, University of Oxford Robert Engle, University of California, San Diego Neil Ericsson, Board of Governors of the Federal Reserve System Jesus Gonzalo, Universidad Carlos III de Madrid Clive Granger, University of California, San Diego David Hendry, University of Oxford Kevin Hoover, Duke University Soren Johansen, University of Copenhagen Katarina Juselius, University of Copenhagen Steven Kamin, Board of Governors of the Federal Reserve System Pauline Kennedy, Bates White, LLC Maozu Lu, University of Southampton Massimiliano Marcellino, Bocconi University and European University Institute Laura Mayoral, Institut d'Analisi Economica (CSIC) Grayham Mizon, University of Southampton Bent Nielsen, University of Oxford Ragnor Nymoen, University of Oslo Jim Stock, Harvard University and the National Bureau of Economic Research Pravin Trivedi, Indiana University, Bloomington Paolo Paruolo, University of Insubria Stephen J. Perez, California State University Mark Watson, Princeton University and the National Bureau of Economic Research Halbert White, University of California, San Diego David Zimmer, Western Kentucky University
Particle Filter Based on PSO

The main challenge in using (PF) to nonlinear state estimation problem is the particle degeneracy. Resampling operation solves degeneracy to some extent, but it results in the phenomenon of sample impoverishment. Therefore, it cannot achieve the satisfactory accuracy generally with certain number particles by using generic PF algorithm because of the serious impoverishment problem. Here we aim for decreasing the impoverishment of samples set after resampling step. The principle of PF together with its particle degeneracy and sample impoverishment problems are introduced in this paper. Based on the analysis of the causes of sample impoverishment, particle swarm optimization (PSO) which is one of the swarm intelligence algorithms is introduced to PF to ameliorate the diversity of samples set after resampling step. Thus a new algorithm which is called PSO-PF is proposed. From a theoretical analysis, the PSO operation on particles set can overcome sample impoverishment problem largely. And finally, a generic numerical example shows that PSO-PF presents better than generic PF algorithm regarding to accuracy.
Variability in the stellar initial mass function at high mass: coalescence models for starburst clusters

A coalescence model using the observed properties of pre-stellar condensations (PSCs) shows how an initially steep initial mass function (IMF) that might be characteristic of primordial cloud fragmentation can change into a Salpeter IMF or shallower IMF in a cluster of normal density after one dynamical time, even if the PSCs are collapsing on their own dynamical time. The model suggests that top-heavy IMFs in some starburst clusters originate with PSC coalescence.
Biocompatible Anionic Polymeric Microspheres as Priming Delivery System for Effetive HIV/AIDS Tat-Based Vaccines

Here we describe a prime-boost regimen of vaccination in Macaca fascicularis that combines priming with novel anionic microspheres designed to deliver the biologically active HIV-1 Tat protein and boosting with Tat in Alum. This regimen of immunization modulated the IgG subclass profile and elicited a balanced Th1-Th2 type of humoral and cellular responses. Remarkably, following intravenous challenge with SHIV89.6Pcy243, vaccinees significantly blunted acute viremia, as compared to control monkeys, and this control was associated with significantly lower CD4+ T cell depletion rate during the acute phase of infection and higher ability to resume the CD4+ T cell counts in the post-acute and chronic phases of infection. The long lasting control of viremia was associated with the persistence of high titers anti-Tat antibodies whose profile clearly distinguished vaccinees in controllers and viremics. Controllers, as opposed to vaccinated and viremic cynos, exhibited significantly higher pre-challenge antibody responses to peptides spanning the glutamine-rich and the RGD-integrin-binding regions of Tat. Finally, among vaccinees, titers of anti-Tat IgG1, IgG3 and IgG4 subclasses had a significant association with control of viremia in the acute and post-acute phases of infection. Altogether these findings indicate that the Tat/H1D/Alum regimen of immunization holds promise for next generation vaccines with Tat protein or other proteins for which maintenance of the native conformation and activity are critical for optimal immunogenicity. Our results also provide novel information on the role of anti-Tat responses in the prevention of HIV pathogenesis and for the design of new vaccine candidates.
High Presence of Extracellular Hemoglobin in the Periventricular White Matter Following Preterm Intraventricular Hemorrhage

Severe cerebral intraventricular hemorrhage (IVH) in preterm infants continues to be a major clinical problem, occurring in about 15–20% of very preterm infants. In contrast to other brain lesions the incidence of IVH has not been reduced over the last decade, but actually slightly increased. Currently over 50% of surviving infants develop post-hemorrhagic ventricular dilatation and about 35% develop severe neurological impairment, mainly cerebral palsy and intellectual disability. To date there is no therapy available to prevent infants from developing either hydrocephalus or serious neurological disability. It is known that blood rapidly accumulates within the ventricles following IVH and this leads to disruption of normal anatomy and increased local pressure. However, the molecular mechanisms causing brain injury following IVH are incompletely understood. We propose that extracellular hemoglobin is central in the pathophysiology of periventricular white matter damage following IVH. Using a preterm rabbit pup model of IVH the distribution of extracellular hemoglobin was characterized at 72 h following hemorrhage. Evaluation of histology, histochemistry, hemoglobin immunolabeling and scanning electron microscopy revealed presence of extensive amounts of extracellular hemoglobin, i.e., not retained within erythrocytes, in the periventricular white matter, widely distributed throughout the brain. Furthermore, double immunolabeling together with the migration and differentiation markers polysialic acid neural cell adhesion molecule (PSA-NCAM) demonstrates that a significant proportion of the extracellular hemoglobin is distributed in areas of the periventricular white matter with high extracellular plasticity. In conclusion, these findings support that extracellular hemoglobin may contribute to the pathophysiological processes that cause irreversible damage to the immature brain following IVH.
Constructing Multiple Kernel Learning Framework for Blast Furnace Automation

This paper constructs the framework of the reproducing kernel Hilbert space for multiple kernel learning, which provides clear insights into the reason that multiple kernel support vector machines (SVM) outperform single kernel SVM. These results can serve as a fundamental guide to account for the superiority of multiple kernel to single kernel learning. Subsequently, the constructed multiple kernel learning algorithms are applied to model a nonlinear blast furnace system only based on its input-output signals. The experimental results not only confirm the superiority of multiple kernel learning algorithms, but also indicate that multiple kernel SVM is a kind of highly competitive data-driven modeling method for the blast furnace system and can provide reliable indication for blast furnace operators to take control actions.
AN ASPECT WEAVER FOR QUALIFIABLE APPLICATIONS

Aspect Oriented Programming (AOP) offers means to automatically transform some existing base code to endow it with new properties. An aspect language allows the desired transformation to be specified and an aspect weaver reads the specification of the transformation expressed in the aspect language and applies it to the base code. AOP techniques allow systematic changes – insertion of synchronization code, of observability code, of instrumentation code, etc – to be applied automatically to a large code base.
A Clustering Model Inspired by Humoral Immunity

In biological immune system, B-cells secrete large numbers of antibodies to recognize and eliminate the antigens. Inspired by the relationship of B-cells and antibodies, an effective immune model is presented in this paper. As its learning capability, this model can recognize not only the existing antigens but also the antigens that are unknown. The structure of the model and the detailed algorithm are given in this paper. And the validity of the model is proved through an experiment of motor fault data clustering. Keywords-artificial immune system; clustering; B-cell; antibody I. INTRODUCTION Currently, information technology develops very fast. So, huge information is produced, and data mining can transform them into useful knowledge. Clustering is an important domain of data mining. It can find out the distributing rule of data character through comparing the comparability and diversity of data, and help researchers to obtain more profound comprehension and cognition (1). But the traditional clustering algorithm are deficient on clustering precision and convergent speed, such as k-means algorithm, Bayesian learning algorithm, fuzzy C means algorithm (FCM), etc.
Optimal mixing enhancement in 3-D pipe flow

We design a Lyapunov based-boundary feedback controller for achieving mixing in a three-dimensional (3-D) pipe flow governed by Navier-Stokes equations. We show that the control law maximizes a measure related to mixing (that incorporates stretching and folding of material elements), while at the same time minimizing the control effort and the sensing effort. The penalty on sensing results in a static output-feedback control law (rather than full-state feedback). We also derive a lower bound on the gain from the control effort to the mixing measure. Furthermore, we establish input-output-to-state-stability properties for the open-loop system. These results show a form of detectability of mixing in the interior of the pipe from the chosen outputs on the wall. The effectiveness of the optimal control in achieving mixing enhancement is demonstrated in numerical simulations.
Irregular amplitude and frequency of respiratory movements in hemispheric stroke

Abstract Objectives: The aims of the study were to investigate respiratory movement patterns among patients with right versus left hemispheric stroke with emphasis on regularity of respiratory frequency and amplitude of movements during both quiet and voluntary deep breathing and to compare the results with reference values. Materials and methods: Eighteen patients with severe stroke were measured with the Respiratory Movement Measuring Instrument. Respiratory frequencies, movements, regularity of amplitude and frequency were compared with individuals with no neurological disease. Results: The demographics and physical performance were comparable for 8 left and 10 right hemispheric stroke. Deep respiratory movements were significantly decreased (p < 0.001) and frequency significantly increased (p < 0.03 for quiet and p = 0.002 for deep breathing), for the group (n = 18) compared with reference values. Fifty-six percent of our stroke patients had irregular amplitude of deep respiratory movements (p = 0.003), and 33% had irregular frequency (p = 0.058), but none of the individuals with no neurological diseases (p = 0.003). Seventy percent of RHS patients had irregular amplitude of deep respiratory movements, compared with 38% of LHS patients (p = 0.34). Conclusion: Results show significantly decreased amplitude of deep breathing in hemispheric stroke and indicate a possible effect on regularity of range and frequency of respiratory movements.
Temperate Pine Barrens and Tropical Rain Forests Are Both Rich in Undescribed Fungi

Most of fungal biodiversity on Earth remains unknown especially in the unexplored habitats. In this study, we compared fungi associated with grass (Poaceae) roots from two ecosystems: the temperate pine barrens in New Jersey, USA and tropical rain forests in Yunnan, China, using the same sampling, isolation and species identification methods. A total of 426 fungal isolates were obtained from 1600 root segments from 80 grass samples. Based on the internal transcribed spacer (ITS) sequences and morphological characteristics, a total of 85 fungal species (OTUs) belonging in 45 genera, 23 families, 16 orders, and 6 classes were identified, among which the pine barrens had 38 and Yunnan had 56 species, with only 9 species in common. The finding that grass roots in the tropical forests harbor higher fungal species diversity supports that tropical forests are fungal biodiversity hotspots. Sordariomycetes was dominant in both places but more Leotiomycetes were found in the pine barrens than Yunnan, which may play a role in the acidic and oligotrophic pine barrens ecosystem. Equal number of undescribed fungal species were discovered from the two sampled ecosystems, although the tropical Yunnan had more known fungal species. Pine barrens is a unique, unexplored ecosystem. Our finding suggests that sampling plants in such unexplored habitats will uncover novel fungi and that grass roots in pine barrens are one of the major reservoirs of novel fungi with about 47% being undescribed species.
Understanding disability glare: light scatter and retinal illuminance as predictors of sensitivity to contrast.

The presence of a bright light in the visual field has two main effects on the retinal image: reduced contrast and increased retinal illuminance because of scattered light; the latter can, under some conditions, lead to an improvement in retinal sensitivity. The combined effect remains poorly understood, particularly at low light levels. A psychophysical flicker-cancellation test was used to measure the amount and angular distribution of scattered light in the eye for 40 observers. Contrast thresholds were measured using a functional contrast sensitivity test. Pupil-plane glare-source illuminances (i.e., 0, 1.35, and 19.21 lm/m2), eccentricities (5°, 10°, and 15°), and background luminances (1, 2.6, and 26 cd/m2) were investigated. Visual performance was better than predicted, based on a loss of retinal image contrast caused by scattered light, particularly in the mesopic range. Prediction accuracy improved significantly when the expected increase in retinal sensitivity in the presence of scattered light was also incorporated in the model.
Abstract—documents Retrieval in Information Retrieval

Systems (IRS) is generally about understanding of information in the documents concern. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS apply algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieving process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Malay and Arabic and incorporated stemming in our experimental systems in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used in the systems.
A digitally programmable folded cascode OTA with variable load applications

Folded Cascode OTA is widely used in analog and mixed signal domain. It gains special importance in switched capacitor circuits where folded cascode architecture is the default choice for op-amps. In this work, a digitally programmable single ended folded cascode operational transconductance amplifier (OTA) is presented. Observations show that the OTA can be made digitally programmable over a wide range of unity gain frequency with compromise on phase margin. It is also shown that adding additional load branches in parallel allows wide tuning of the DC gain and phase margin. The programmable OTA is thus designed and the pre and post layout simulation results are presented.