Miracle-dz/UniFAR-FTUs huggingface dataset:
Vaccination against Neisseria meningitidis Using Three Variants of the Lipoprotein GNA1870

Sepsis and meningitis caused by serogroup B meningococcus are devastating diseases of infants and young adults, which cannot yet be prevented by vaccination. By genome mining, we discovered GNA1870, a new surface-exposed lipoprotein of Neisseria meningitidis that induces high levels of bactericidal antibodies. The antigen is expressed by all strains of N. meningitidis tested. Sequencing of the gene in 71 strains representative of the genetic and geographic diversity of the N. meningitidis population, showed that the protein can be divided into three variants. Conservation within each variant ranges between 91.6 to 100%, while between the variants the conservation can be as low as 62.8%. The level of expression varies between strains, which can be classified as high, intermediate, and low expressors. Antibodies against a recombinant form of the protein elicit complement-mediated killing of the strains that carry the same variant and induce passive protection in the infant rat model. Bactericidal titers are highest against those strains expressing high yields of the protein; however, even the very low expressors are efficiently killed. The novel antigen is a top candidate for the development of a new vaccine against meningococcus.
The PMIP4 contribution to CMIP6 – Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations

Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land-sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last In-terglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.
A neural model of cross-modal association in insects

We developed a computational model of learning in the Mush- room Body, a region of multimodal integration in the insect brain. Using realistic neural dynamics and a biologically-based learning rule (spike tim- ing dependent plasticity), the model is tested as part of an insect brain inspired architecture within a closed loop behavioural task. Replicating in simulation an experiment carried out on bushcrickets, we show the sys- tem can successfully associate visual to auditory cues, so as to maintain a steady heading towards an intermittent sound source.
Continuous pose estimation for stereo vision based on UV disparity applied to visual odometry in urban environments

This paper presents an autocalibration method to determine the pose of a stereo vision system based on knowing the geometry of the ground in front of the cameras. This pose changes considerably while the vehicle is driven, therefore it is good to know constantly the pose of the camera for several applications based on computer vision, such as advanced driver assistance systems, autonomous vehicles or robotics. These constant changes of the pose make interesting to be able to detect constantly the variations in its extrinsic parameters (height, pitch, roll). The validation of the autocalibration method is accomplished by a visual odometry implementation. A study of the improvement of the results of the visual odometry estimation taking into account the changes of the camera pose is presented, demonstrating the advantages of the autocalibration method.
Molecular modeling study for the design of novel acetyl-CoA carboxylase inhibitors using 3D QSAR, molecular docking and dynamic simulations

Acetyl-CoA carboxylase (ACC) enzyme plays an important role in the regulation of biosynthesis and oxidation of fatty acids. ACC is a recognized drug target for the treatment of obesity and diabetes. Combination of ligand and structure-based in silico methods along with activity and toxicity prediction provides best lead compounds in the drug discovery process. In this study, a data-set of 100 ACC inhibitors were used for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity index matrix analysis (CoMSIA) models. The generated contour maps were used for the design of novel ACC inhibitors. CoMFA and CoMSIA models were used for the predication of activity of designed compounds. In silico toxicity risk prediction study was carried out for the designed compounds. Molecular docking and dynamic simulations studies were performed to know the binding mode of designed compounds with the ACC enzyme. The designed compounds showed interactions with key amino acid residues important for catalysis, and good correlation was observed between binding free energy and inhibition of ACC.
In-broker access control : A new access control deployment strategy towards optimal end-to-end performance of information brokerage systems

An XML brokerage system is a distributed XML database system that comprises of data sources and brokers which, respectively, hold XML documents and document distribution information. Databases can be queried through brokers with no schema-relevant or geographical difference being noticed. However, all existing information brokerage systems view or handle query brokering and access control as two orthogonal issues: query brokering is a system issue that concerns costs and performance, while access control is a security issue that concerns information confidentiality. As a result, access control deployment strategies (in terms of where and when to do access control) and the impact of such strategies on end-to-end system performance are (in general) neglected by existing information brokerage systems; and data source side access control deployment is taken-for-granted as the “right” thing to do. In this paper, we challenge this traditional, taken-for-granted access control deployment methodology, and we show that query brokering and access control are not two orthogonal issues because access control deployment strategies can have significant impact on the “whole” system’s end-to-end performance. We propose the first in-broker access control deployment strategy where access control is “pushed” from the boundary of an information brokerage system into the “heart” of the system. We design and evaluate the fist in-broker access control scheme for information brokerage systems. Our experimental results indicate that information brokerage system builders should treat access control as a system issue as well.
From Hyperinflation to Stable Prices: Argentina’s Evidence on Menu Cost Models*

In this article, we analyze how inflation affects firms’ price-setting behavior. For a class of menu cost models, we derive several predictions about how price-setting changes with inflation at very high and at near-zero inflation rates. Then, we present evidence supporting these predictions using product-level data underlying Argentina’s consumer price index from 1988 to 1997—a unique experience where monthly inflation ranged from almost 200% to less than zero. For low inflation rates, we find that (i) the frequency and absolute size of price changes as well as the dispersion of relative prices do not change with inflation, (ii) the frequency and size of price increases and decreases are symmetric around zero inflation, and (iii) aggregate inflation changes are mostly driven by changes in the frequency of price increases and decreases, as opposed to the size of price changes. For high inflation rates, we find that (iv) the elasticity of the frequency of price changes with respect to inflation is close to two-thirds, (v) the frequency of price changes across different products becomes similar, and (vi) the elasticity of the dispersion of relative prices with respect to inflation is one-third. Our findings confirm and extend available evidence for countries that experienced either very high or near-zero inflation. We conclude by showing that a hyperinflation of 500% a year is associated with a cost of approximately 8.5% of aggregate output a year as a result of inefficient price dispersion alone.
RQL: Retrospective Computations over Snapshot Sets

Applications need to analyze the past state of their data to provide auditing and other forms of fact checking. Retrospective snapshot systems that support computations over data store snapshots, allow applications using simple data stores like Berkeley DB or SQLite, to provide past state analysis in a convenient way. Current snapshot systems however, offer no satisfactory support for computations that analyze multiple snapshots. We have developed a Retrospective Query Language (RQL), a simple declarative extension to SQL that allows to specify and run multi-snapshot computations conveniently in a snapshot system, using a small number of simple mechanisms defined in terms of relational constructs familiar to programmers. We describe RQL mechanisms, explain how they translate into SQL computations in a snapshot system, and show how to express a number of common analysis patterns with illustrative examples. We also describe how we implemented RQL in a simple way utilizing SQLite UDF framework in a Berkeley DB data store using Retro page-level incremental snapshot system. Multi-snapshot computations running over page-level incremental snapshots bring up interesting performance issues that have not been studied before. We present the first study defining a performance envelope for multi-snapshot computations over page-level incremental snapshots.
' s personal copy Web robot detection : A probabilistic reasoning approach

In this paper, we introduce a probabilistic modeling approach for addressing the problem of Web robot detection from Web-server access logs. More specifically, we construct a Bayesian network that classifies automatically access log sessions as being crawleror human-induced, by combining various pieces of evidence proven to characterize crawler and human behavior. Our approach uses an adaptive-threshold technique to extract Web sessions from access logs. Then, we apply machine learning techniques to determine the parameters of the probabilistic model. The resulting classification is based on the maximum posterior probability of all classes given the available evidence. We apply our method to real Web-server logs and obtain results that demonstrate the robustness and effectiveness of probabilistic reasoning for crawler detection. 2008 Elsevier B.V. All rights reserved.
Preparation of Nano Zinc Oxide, its Characterization and use in Natural Rubber

Zinc oxide (ZnO) of nanometer particles size was prepared by precipitation method and solid state pyrolytic method. TEM, XRD, and the surface area studies showed that the zinc oxides prepared in the laboratory has a particle size in nanometer range and high surface area. This nano zinc oxide was used as an activator in natural rubber compound. The cure characteristic and mechanical properties were compared with that containing conventional ZnO. It is found that a low dosage of zinc oxide was enough to give equivalent curing and mechanical properties compared to the one containing a higher dosage of conventional zinc oxide.
Topical tranexamic acid versus hot saline for field quality during endoscopic sinus surgery

Objectives This study conducted to evaluate and compare between topical tranexamic acid (TA) and hot saline as an alternative to local vasoconstrictors on bleeding and surgery site quality during endoscopic sinus surgery (FESS). Patients and methods This study was performed on 75 patients with class I and II American society of anesthesiologists (A.S.A.), scheduled for elective FESS under general anesthesia. Patients divided into three groups, each (25 patients), group A: topical tranexamic acid (1000mg diluted in 20ml normal saline) was used during surgery for packing and irrigation, group B: hot saline up to 50°C was used and group C :(control group) normal saline was used. Results The use of local (TA) was associated with significant decrease in estimated blood loss 214.2 ml more than local hot saline which was 216.75 and both is much better than the normal saline which was 272.66. Also (TA) and hot saline showed decrease in the duration of surgery, improve the surgical field quality and blinded surgeon satisfaction as compared with the control group. Conclusion The use of local TA and local hot saline up to 50°C achieved reduction in blood loss, duration of surgery and improved surgical field quality during FESS.
Cognitive Impairment Before Intracerebral Hemorrhage Is Associated With Cerebral Amyloid Angiopathy

Background and Purpose— Although the association between cerebral amyloid angiopathy (CAA) and cognitive impairment is increasingly recognized, it is not clear whether this is because of the impact of recurrent intracerebral hemorrhage (ICH) events, disruptions caused by cerebral small vessel damage, or both. We investigated this by considering whether cognitive impairment before ICH was associated with neuroimaging features of CAA on magnetic resonance imaging. Methods— We studied 166 patients with neuroimaging-confirmed ICH recruited to a prospective multicentre observational study. Preexisting cognitive impairment was determined using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Magnetic resonance imaging markers of cerebral small vessel disease, including CAA, were rated by trained observers according to consensus guidelines. Results— The prevalence of cognitive impairment before ICH was 24.7% (n=41) and, in adjusted analyses, was associated with fulfilling the modified Boston criteria for probable CAA at presentation (odds ratio, 4.01; 95% confidence interval, 1.53–10.51; P=0.005) and a higher composite CAA score (for each point increase, odds ratio, 1.42; 95% confidence interval, 1.03–1.97; P=0.033). We also found independent associations between pre-ICH cognitive decline and the presence of cortical superficial siderosis, strictly lobar microbleeds, and lobar ICH location, but not with other neuroimaging markers, or a composite small vessel disease score. Conclusions— CAA (defined using magnetic resonance imaging markers) is associated with cognitive decline before symptomatic ICH. This provides evidence that small vessel disruption in CAA makes an independent contribution to cognitive impairment, in addition to effects due to brain injury caused directly by ICH. Clinical Trial Registration— URL: https://www.clinicaltrials. gov. Unique identifier: NCT02513316.
New generation emerging technologies for neurorehabilitation and motor assistance

This paper illustrates the application of emerging technologies and human-machine interfaces to the neurorehabilitation and motor assistance fields. The contribution focuses on wearable technologies and in particular on robotic exoskeleton as tools for increasing freedom to move and performing Activities of Daily Living (ADLs). This would result in a deep improvement in quality of life, also in terms of improved function of internal organs and general health status. Furthermore, the integration of these robotic systems with advanced bio-signal driven human-machine interface can increase the degree of participation of patient in robotic training allowing to recognize user's intention and assisting the patient in rehabilitation tasks, thus representing a fundamental aspect to elicit motor learning
Inhibition of Drp1/Fis1 interaction slows progression of amyotrophic lateral sclerosis

Bioenergetic failure and oxidative stress are common pathological hallmarks of amyotrophic lateral sclerosis (ALS), but whether these could be targeted effectively for novel therapeutic intervention needs to be determined. One of the reported contributors to ALS pathology is mitochondrial dysfunction associated with excessive mitochondrial fission and fragmentation, which is predominantly mediated by Drp1 hyperactivation. Here, we determined whether inhibition of excessive fission by inhibiting Drp1/Fis1 interaction affects disease progression. We observed mitochondrial excessive fragmentation and dysfunction in several familial forms of ALS patient‐derived fibroblasts as well as in cultured motor neurons expressing SOD1 mutant. In both cell models, inhibition of Drp1/Fis1 interaction by a selective peptide inhibitor, P110, led to a significant reduction in reactive oxygen species levels, and to improvement in mitochondrial structure and functions. Sustained treatment of mice expressing G93A SOD1 mutation with P110, beginning at the onset of disease symptoms at day 90, produced an improvement in motor performance and survival, suggesting that Drp1 hyperactivation may be an attractive target in the treatment of ALS patients.
HPMA–Copolymer Nanocarrier Targets Tumor-Associated Macrophages in Primary and Metastatic Breast Cancer

Polymeric nanocarriers such as N-(2-hydroxypropyl) methacrylamide (HPMA) copolymers deliver drugs to solid tumors and avoid the systemic toxicity of conventional chemotherapy. Because HPMA copolymers can target sites of inflammation and accumulate within innate immune cells, we hypothesized that HPMA copolymers could target tumor-associated macrophages (TAM) in both primary and metastatic tumor microenvironments. We verified this hypothesis, first in preliminary experiments with isolated bone marrow macrophage cultures in vitro and subsequently in a spontaneously metastatic murine breast cancer model generated from a well-established, cytogenetically characterized 4T1 breast cancer cell line. Using our standardized experimental conditions, we detected primary orthotopic tumor growth at 7 days and metastatic tumors at 28 days after orthotopic transplantation of 4T1 cells into the mammary fat pad. We investigated the uptake of HPMA copolymer conjugated with Alexa Fluor 647 and folic acid (P-Alexa647-FA) and HPMA copolymer conjugated with IRDye 800CW (P-IRDye), following their retroorbital injection into the primary and metastatic tumor-bearing mice. A significant uptake of P-IRDye was observed at all primary and metastatic tumor sites in these mice, and the P-Alexa647-FA signal was found specifically within CD11b+ TAMs costained with pan-macrophage marker CD68. These findings demonstrate, for the first time, a novel capacity of a P-Alexa647-FA conjugate to colocalize to CD11b+CD68+ TAMs in both primary and metastatic breast tumors. This underscores the potential of this HPMA nanocarrier to deliver functional therapeutics that specifically target tumor-promoting macrophage activation and/or polarization during tumor development. Mol Cancer Ther; 16(12); 2701–10. ©2017 AACR.
Stereovision Approach for Obstacle Detection on Non-Planar Roads

This paper will present an obstacle detection system that that relies on the 3D information provided by stereo reconstruction. The 3D features must be separated in road features and obstacle features. Instead of relying on the flatness of the road, the vertical road profile is modeled as a clothoid, and is estimated from the lateral projection of the 3D points. The points above the road are selected for grouping into objects, based on vicinity criteria and the variation of the point density with the distance. The resulted objects are used as measurements for a model-based tracking algorithm. The resulted system is a high-accuracy, far distance obstacle detector, able to function in a large variety of real-world scenarios.
RowAMD Distance: A Novel 2DPCA-Based Distance Computation with Texture-Based Technique for Face Recognition

Although two-dimensional principal component analysis (2DPCA) has been shown to be successful in face recognition system, it is still very sensitive to illumination variations. To reduce the effect of these variations, texture-based techniques are used due to their robustness to these variations . In this paper, we explore several texture-based techniques and determine the most appropriate one to be used with 2DPCA-based techniques for face recognition. We also propose a new distance metric computation in 2DPCA called Row Assembled Matrix Distance (RowAMD). Experiments on Yale Face Database, Extended Yale Face Database B, AR Database and LFW Database reveal that the proposed RowAMD distance computation method outperforms other conventional distance metrics when Local Line Binary Pattern (LLBP) and Multi-scale Block Local Binary Pattern (MB-LBP) are used for face authentication and face iden tiﬁcation, respectively. In addition to this, the results also demonstrate the robustness of the proposed RowAMD with several texture-based techniques.
Anisotropic Oxygen Ion Diffusion in Layered PrBaCo2O5+δ

Oxygen diffusion and surface exchange coefficients have been measured on polycrystalline samples of the double perovskite oxide PrBaCo2O5+δ by the isotope exchange depth profile method, using a time-of-flight SIMS instrument. The measured diffusion coefficients show an activation energy of 1.02 eV, as compared to 0.89 eV for the surface exchange coefficients in the temperature range from 300 to 670 °C. Inhomogeneity was observed in the distribution of the oxygen-18 isotopic fraction from grain to grain in the ceramic samples, which was attributed to anisotropy in the diffusion and exchange of oxygen. By the use of a novel combination of electron back scattered diffraction measurements, time-of-flight, and focused ion beam SIMS, this anisotropy was confirmed by in-depth analysis of single grains of known orientation in a ceramic sample exchanged at 300 °C. Diffusion was shown to be faster in a grain oriented with the surface normal close to 100 and 010 (ab-plane oriented) than a grain with a surface normal.