Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Magnetic Resonance Imaging Mismatch Criteria to Select Patients for Endovascular Stroke Therapy

Background and Purpose— The Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution 2 (DEFUSE 2) study has shown that clinical response to endovascular reperfusion differs between patients with and without perfusion–diffusion (perfusion-weighted imaging–diffusion-weighted imaging, PWI–DWI) mismatch: patients with mismatch have a favorable clinical response to reperfusion, whereas patients without mismatch do not. This study examined whether alternative mismatch criteria can also differentiate patients according to their response to reperfusion. Methods— Patients from the DEFUSE 2 study were categorized according to vessel occlusion on magnetic resonance angiography (MRA) and DWI lesion volume criteria (MRA–DWI mismatch) and symptom severity and DWI criteria (clinical–DWI mismatch). Favorable clinical response was defined as an improvement of ≥8 points on the National Institutes of Health Stroke Scale (NIHSS) by day 30 or an NIHSS score of ⩽1 at day 30. We assessed, for each set of criteria, whether the association between reperfusion and favorable clinical response differed according to mismatch status. Results— A differential response to reperfusion was observed between patients with and without MRA–DWI mismatch defined as an internal carotid artery or M1 occlusion and a DWI lesion <50 mL. Reperfusion was associated with good functional outcome in patients who met these MRA–DWI mismatch criteria (odds ratio [OR], 8.5; 95% confidence interval [CI], 2.3–31.3), whereas no association was observed in patients who did not meet these criteria (OR, 0.5; 95% CI, 0.08–3.1; P for difference between the odds, 0.01). No differential response to reperfusion was observed with other variations of the MRA–DWI or clinical–DWI mismatch criteria. Conclusions— The MRA–DWI mismatch is a promising alternative to DEFUSE 2’s PWI–DWI mismatch for patient selection in endovascular stroke trials.
Global distribution of carbon monoxide

This study explores the evolution and distribution of carbon monoxide (CO) using the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory three-dimensional global chemical transport model (GFDL GCTM). The work aims to gain an improved understanding of the global carbon monoxide budget, specifically focusing on the contribution of each of the four source terms to the seasonal variability of CO. The sum of all CO sources in the model is 2.5 Pg CO/yr (1 Pg = 103 Tg), including fossil fuel use (300 Tg CO/yr), biomass burning (748 Tg CO/yr), oxidation of biogenic hydrocarbons (683 Tg CO/yr), and methane oxidation (760 Tg CO/yr). The main sink for CO is destruction by the hydroxyl radical, and we assume a hydroxyl distribution based on three-dimensional monthly varying fields given by Spivakovsky et al. [1990], but we increase this field by 15% uniformly to agree with a methyl chloroform lifetime of 4.8 years [Prinn et al, 1995]. Our simulation produces a carbon monoxide field that agrees well with available measurements from the NOAA/Climate Monitoring and Diagnostics Laboratory global cooperative flask sampling network and from the Jungfraujoch observing station of the Swiss Federal Laboratories for Materials Testing and Research (EMPA) (93% of seasonal-average data points agree within ±25%) and flight data from measurement campaigns of the NASA Global Tropospheric Experiment (79% of regional-average data points agree within ±25%). For all 34 ground-based measurement sites we have calculated the percentage contribution of each CO source term to the total model-simulated distribution and examined how these contributions vary seasonally due to transport, changes in OH concentration, and seasonality of emission sources. CO from all four sources contributes to the total magnitude of CO in all regions. Seasonality, however, is usually governed by the transport and destruction by OH of CO emitted by fossil fuel and/or biomass burning. The sensitivity to the hydroxyl field varies spatially, with a 30% increase in OH yielding decreases in CO ranging from 4–23%, with lower sensitivities near emission regions where advection acts as a strong local sink. The lifetime of CO varies from 10 days over summer continental regions to well over a year at the winter poles, where we define lifetime as the turnover time in the troposphere due to reaction with OH.
A Tutorial of Mobile Ad-Hoc Network (Manet) Routing Protocols

In mobile adhoc network nodes dynamically forms networks, there is no any central infrastructure, thus routing becomes a very important issue. Routing protocols used in mobile ad hoc networks (MANET) must adapt to frequent or continual changes of topology, while simultaneously limiting the impact of following these changes on wireless resources. This paper presents a comprehensive report and a comparative study of the different MANET routing protocols. The performance of such communication between nodes depends on various protocols. we have tendency to survey variety of the recent analysis results in routing space. In the following sections we have a tendency to present various existing routing protocols with their merits and demerits
Soil physical conditions after six years of direct drilling or conventional cultivation on a silt loam soil in New Zealand

Soil physical conditions following six years of cereals planted by direct drilling (DD) or conventional cultivation (ploughing, PL) are compared. Bulk density was higher in the top 200 mm of the DD soil but, with ploughing, bulk density was found to increase sharply and remain higher than DD below this depth. With DD, soil strength was consistently higher at most depths and aggregate stability was also higher. Earthworm numbers were at least 1.5 times greater in the DD plots. Infiltration rates were similar under both systems despite the lower total porosity and air-filled porosity of the DD soil. This was attributed to a more open and continuous network of pores in the DD soil. Root densities measured in the same year as the soil physical conditions were significantly higher in the surface 0-100 mm of the DD soil and also tended to be higher below 200 mm depth. In the sixth year of the trial, there was a significantly greater plant emergence in the DD soil than PL soil, although harvest grain yields were similar for both treatments.
Learning Better Data Representation Using Inference-Driven Metric Learning

We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semi-supervised metric learning algorithms to those generated by previously proposed unsupervised dimensionality reduction methods (e.g., PCA). Through a variety of experiments on different real-world datasets, we find IDML-IT, a semi-supervised metric learning algorithm to be the most effective.
District names speech corpus for Pakistani Languages

This paper presents a speech corpus that is developed for Urdu automatic speech recognition (ASR) system. The corpus comprises of single word utterances fixed vocabulary consisting of district names of Pakistan. The data is recorded over a telephone channel from all over Pakistan to cover six major accents; Punjabi, Urdu, Saraiki, Pashto, Sindhi, and Balochi. The data was collected in challenging acoustic environments; the major issues were silence, background noise and alternate pronunciations, which can affect the performance of the system. In order to address these issues, comprehensive data verification and cleaning guidelines are presented. The proposed process serves as a data preprocessing step for the development of ASR, which is successfully integrated in an Urdu dialog system to provide weather information of Pakistan.
Opinion Analysis of text on the basis of Three Domain Classification

in today's world, everyone is aware of comment analysis. Its better example is if we want to buy gadgets online or we want to watch a movie, we first see comments or ratings of that product or movie. For this, every website asks every customer to give their feedback which is helpful for product success or movie success. From this feedback or opinion the site owner grabs the mood of the customer. That's why every site owner wants a comment from customer. For searching the sentiment of text which is given by customer there are a number of methods available. In the proposed system the sentiment is finding out in semi-supervised manner. By using this system, polarity or domain classification of text is done. In this system, we combine LDA with data expansion method for data preprocessing which is known as LDA preprocessing and then Naïve Bayes dual training and Domain prediction algorithms are used for sentiment evaluation. From this, we will classify the sentence in three domains i.e. positive, negative and neutral.
A self-organizing technique for sensor placement in wireless micro-sensor networks

This paper proposes a self-organizing technique for enhancing the coverage of wireless micro-sensor networks after an initial random placement of sensors. A randomized back-off delay time is introduced to resolve the problem of simultaneous movement of sensors in the neighborhood which leads to unnecessary excessive movement and hence consume more sensors' energy. A sensor node relocates itself when the time calculated through randomized back-off delay computation is reached. The new location of the sensor is determined by a virtual force-directed algorithm where virtual attractive or repulsive forces exerted by other sensors or obstacles are used to guide the sensor to the desired location. The proposed self-organizing algorithm for sensor placement is proved to be effective through simulation.
Simplifying Peer-to-Peer Device Authentication Using Identity-Based Cryptography

Identity-based cryptography (IBC) recently emerged as a major area in cryptographic research and development. This paper discusses the applications of IBC technologies to solve network device authentication problems. From the security as well as administrative perspectives, IBC can provide many advantages compared to conventional authentication methods such as pre-shared keys, public key certificates, and Kerberos. A symmetric authentication protocol is presented to describe how IBC can be used for peer-to-peer device authentication across multiple domains
Registro palinológico de depósitos sedimentares neopleistocênicos do Rio Madeira, Rondônia, Amazônia brasileira

The present paper presents a study of identification of palynological assemblages from a layer of sediment taken from a modern forested area situated in the upper course of the Madeira River, within the region of influence of the AHE Jirau, Rondonia, Brazilian Amazon. Radiometric carbon dating using 14C (AMS method) furnished ages between 41,350 and 43,500 years Before Present (B.P.), or Late Pleistocene, for the studied layer. The results reveal a set of palynomorphs marked by low diversity of pollen families with predominantly tropical forest types showing an upward increase in pollen grains typical of wet environments, probably suggesting the installation of a swamp. No other vegetational change was observed during the period recorded in this study, and in general the data are in agreement to palynological records obtained from other areas of the Amazon forest region that indicate a steady forested environment for the same period.
A fully robust fuzzy extractor

Cryptography traditionally relies on uniformly distributed and precisely reproducible random strings for its secrets, however, it is difficult to create, store, and reliably retrieve such strings. To securely derive cryptographic keys from a noisy input such as biometric data, two primitives are introduced by Y. Dodis et.al.: a secure sketch which allows recovery of a noisy input given a “close” approximation thereof, and a fuzzy extractor which extracts a uniformly distributed string from this noisy input in an error-tolerant manner. Both primitives work by constructing a “public” string which is used to encode the information needed for error-tolerant reconstruction of the original input and subsequent extraction. The public string, when transmitted over an insecure channel or stored in an insecure storage, can be modified by an adversary. A robust secure sketch and a robust fuzzy extractor mean that the public string can be authenticated by a receiver, if the authenticity of public string is verified by using, in some way, recovered string in secure sketch or extracted string in fuzzy extractor, we say that the authentication has circularity in it. In this paper, we propose a fully robust fuzzy extractor based on an error-correcting code, in which the public string can be authenticated by the receiver using his own a part of string that is close to sender's string under some metric, thus the circularity in authentication can be broken fully. The security is proven in standard model.
Postacquisition suppression of large‐vessel BOLD signals in high‐resolution fMRI

Large‐vessel BOLD contamination is a serious impediment to localization of neural activity in high‐resolution fMRI studies. A new method is presented which estimates and removes the fraction of BOLD signal that arises from oriented vessels, such as cerebral and pial veins in a voxel, by measuring their influence on the phase angle of the complex valued fMRI time series. A maximum likelihood estimator based on a linear least‐squares fit of the BOLD signal phase to the BOLD signal magnitude in a voxel is shown to efficiently suppress the BOLD effect from these larger veins, whose activation is not well colocalized with the neural response. In high‐resolution in vivo fMRI data at 4 T, it is estimated that the method is sensitive to the phase changes in the cerebral, larger intracortical, and pial veins. The technique requires no special pulse sequence modifications or acquisition strategies, and is computationally fast and intrinsically robust. Magn Reson Med 47:1–9, 2002. © 2002 Wiley‐Liss, Inc.
Transepithelial migration of Toxoplasma gondii involves an interaction of intercellular adhesion molecule 1 (ICAM‐1) with the parasite adhesin MIC2

Toxoplasma gondii crosses non‐permissive biological barriers such as the intestine, the blood–brain barrier and the placenta thereby gaining access to tissues where it most commonly causes severe pathology. Herein we show that in the process of migration Toxoplasma initially concentrates around intercellular junctions and probably uses a paracellular pathway to transmigrate across biological barriers. Parasite transmigration required viable and actively motile parasites. Interestingly, the integrity of host cell barriers was not altered during parasite transmigration. As intercellular adhesion molecule 1 (ICAM‐1) is upregulated on cellular barriers during Toxoplasma infection, we investigated the role of this receptor in parasite transmigration. Soluble human ICAM‐1 and ICAM‐1 antibodies inhibited transmigration of parasites across cellular barriers implicating this receptor in the process of transmigration. Furthermore, human ICAM‐1 immunoprecipitated the mature form of the parasite adhesin MIC2 present on the parasite surface, indicating that this interaction may contribute to cellular migration. These findings reveal that Toxoplasma exploits the natural cell trafficking pathways in the host to cross cellular barriers and disseminate to deep tissues.
Gestural control of sound synthesis

This paper provides a review of gestural control of sound synthesis in the context of the design and evaluation of digital musical instruments. It discusses research in various areas related to this field and equally focuses on four main topics: analysis of music performers' gestures, gestural capture technologies, real-time sound synthesis methods, and strategies for mapping gesture variables to sound synthesis input parameters. Finally, this approach is illustrated by presenting an application of this research to the control of digital audio effects.
Pick your contexts well: understanding object-sensitivity

Object-sensitivity has emerged as an excellent context abstraction for points-to analysis in object-oriented languages. Despite its practical success, however, object-sensitivity is poorly understood. For instance, for a context depth of 2 or higher, past scalable implementations deviate significantly from the original definition of an object-sensitive analysis. The reason is that the analysis has many degrees of freedom, relating to which context elements are picked at every method call and object creation. We offer a clean model for the analysis design space, and discuss a formal and informal understanding of object-sensitivity and of how to create good object-sensitive analyses. The results are surprising in their extent. We find that past implementations have made a sub-optimal choice of contexts, to the severe detriment of precision and performance. We define a "full-object-sensitive" analysis that results in significantly higher precision, and often performance, for the exact same context depth. We also introduce "type-sensitivity" as an explicit approximation of object-sensitivity that preserves high context quality at substantially reduced cost. A type-sensitive points-to analysis makes an unconventional use of types as context: the context types are not dynamic types of objects involved in the analysis, but instead upper bounds on the dynamic types of their allocator objects. Our results expose the influence of context choice on the quality of points-to analysis and demonstrate type-sensitivity to be an idea with major impact: It decisively advances the state-of-the-art with a spectrum of analyses that simultaneously enjoy speed (several times faster than an analogous object-sensitive analysis), scalability (comparable to analyses with much less context-sensitivity), and precision (comparable to the best object-sensitive analysis with the same context depth).
Diarrheagenic Pathogens in Polymicrobial Infections

During systematic active surveillance of the causes of diarrhea in patients admitted to the Infectious Diseases and Beliaghata General Hospital in Kolkata, India, we looked for 26 known gastrointestinal pathogens in fecal samples from 2,748 patients. Samples from about one-third (29%) of the patients contained multiple pathogens. Polymicrobial infections frequently contained Vibrio cholerae O1 and rotavirus. When these agents were present, some co-infecting agents were found significantly less often (p = 10–5 to 10–33), some were detected significantly more often (p = 10–5 to 10–26), and others were detected equally as often as when V. cholerae O1 or rotavirus was absent. When data were stratified by patient age and season, many nonrandom associations remained statistically significant. The causes and effects of these nonrandom associations remain unknown.
Extraction of Geometric Features with Functional Models

In this contribution, we show how to encode in a convenient and compact way information from images with so called functional graphical models. Those models permit to represent in a coherent mathematical framework features such as interest points , simply connected curves such as line and conic segments, connected regions of homogeneous properties, and compound features such as lines and line pencils. We show also the relevance of functional models for feature extraction, which is realized by minimizing a global model selection function. We apply the framework for encoding/extracting geometrical features thanks to two fast sub-optimal algorithms.
Learning Induces a CDC2-Related Protein Kinase, KKIAMRE

To elucidate molecular mechanisms in learning and memory, we analyzed expression of mRNAs in brains of rabbits undergoing eyeblink conditioning. Infusion of the transcription inhibitor actinomycin D into the cerebellar interpositus nucleus reversibly blocked learning but not performance of the conditioned response. Differential display PCR analysis of cerebellar interpositus RNAs from trained and pseudotrained rabbits identified a 207 bp band that was induced with learning. The fragment was used to isolate a cDNA from a λgt11 rabbit brain library containing a 1698 bp open reading frame. The deduced amino acid sequence contains the KKIAMRE motif, which is conserved among cell division cycle 2 (cdc2)-related kinases. These results suggest that there is a new category of cdc2-related kinases in the brain whose function may be important in learning and memory.
Fibre digestibility, abundance of faecal bacteria and plasma acetate concentrations in overweight adult mares

The purpose of the present study was to compare digestibility of grass hay, faecal and plasma volatile fatty acid (VFA) concentrations, and faecal bacterial abundance in overweight and moderate-condition mares. Five overweight adult mixed-breed mares and five adult mixed-breed mares in moderate condition were housed individually and limit-fed orchard grass (Dactylis glomerata) hay at 20 g/kg body weight (as fed) daily for 14 d. Forage DM and fibre digestibility were determined using AOAC methods; digestible energy was measured using bomb calorimetry; plasma and faecal VFA concentrations were determined by use of GC and MS; faecal Firmicutes, Bacteroidetes, Fibrobacter succinogenes, Ruminococcus flavefaciens and total bacteria abundance was determined by quantitative real-time PCR using previously designed phylum-specific 16S ribosomal RNA gene primers. No differences in hay digestibility, faecal VFA concentrations or faecal bacterial abundance were detected between overweight and moderate-condition mares. Mean plasma acetate concentrations were higher (P = 0·03) in overweight (1·55 (range 1·43–1·65) mmol/l) v. moderate-condition (1·39 (range 1·22–1·47) mmol/l) mares. We conclude that the higher plasma acetate in overweight mares should be further investigated as a potential link between gut microbes and obesity in horses.
How Inhibitory Oscillations Can Train Neural Networks and Punish Competitors

We present a new learning algorithm that leverages oscillations in the strength of neural inhibition to train neural networks. Raising inhibition can be used to identify weak parts of target memories, which are then strengthened. Conversely, lowering inhibition can be used to identify competitors, which are then weakened. To update weights, we apply the Contrastive Hebbian Learning equation to successive time steps of the network. The sign of the weight change equation varies as a function of the phase of the inhibitory oscillation. We show that the learning algorithm can memorize large numbers of correlated input patterns without collapsing and that it shows good generalization to test patterns that do not exactly match studied patterns.
Determination of cloud condensation nuclei production from measured new particle formation events

A semi‐analytical expression has been developed that accurately models the population dynamics of an aerosol growing from the detection limit (3 nm) to a characteristic CCN size (100 nm), quantifying the contributions of size and time‐dependent source and sink terms such as coagulation of smaller particles and scavenging by the pre‐existing aerosol. These model inputs were calculated from measured aerosol size distributions and growth rates acquired during intensive measurement campaigns in Boulder, CO, Atlanta, GA, and Tecamac, Mexico. Twenty CCN formation events from these campaigns were used to test the validity of this model. Measured growth rates ranged from 3–22 nm/h. The modeled and measured CCN production probabilities agreed well with each other, ranging from 1–20%. The pre‐existing CCN number concentration increased on average by a factor of 3.8 as a result of new particle formation.