Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasound-guided single injection infraclavicular brachial plexus block using bupivacaine alone or combined with dexmedetomidine for pain control in upper limb surgery: A prospective randomized controlled trial

Background: Dexmedetomidine, is a selective α2-adrenoceptor agonist that is used as an adjuvant mixed with local anesthetics during regional anesthesia. This study was designed to test the efficacy of adding dexmedetomidine to bupivacaine during placement of infraclavicular brachial plexus blockade (ICB). Methods: Sixty adult patients were divided into 2 equal groups of 30 subjects each. Patients in Group I received an ICB using 30 mL of 0.33% bupivacaine and Group II patients received 30 mL of 0.33% bupivacaine mixed with 0.75 μg/kg of dexmedetomidine. The following brachial plexus nerve block parameters were assessed: block success rate, sensory onset time and duration, motor block onset time and duration, analgesic pain scores using the verbal rating scale (VRS) for pain, duration of analgesia, and amount of supplemental intravenous (IV) morphine required. Results: There was a statistically significant shorter time to onset of sensory blockade (13.2 vs 19.4 min, P=0.003), longer duration of sensory block (179.4 vs 122.7 min, P=0.002), shorter onset time to achieve motor block (15.3 vs 22.2 min, P=0.003), longer duration of motor block (155.5 vs 105.7 min, P=0.002), lower VRS pain scores, prolonged analgesia (403 vs 233 min, P=0.002), and lower morphine rescue requirements for 48 h after surgery (4.9 (0–8.0) vs 13.6 mg (4.0–16.0) mg, P=0.005). All patients recovered without evidence of sensory or motor deficit. Conclusion: Adding dexmedetomidine to bupivacaine during the placement of an ICB provides: (1) enhancement of onset of sensory and motor blockade, (2) prolonged duration of analgesia, (3) increases duration of sensory and motor block, (4) yields lower VRS pain scores, and (5) reduces supplemental opioid requirements.
End-to-End Encryption in Messaging Services and National Security?Case of WhatsApp Messenger

The ubiquity of instant messaging services on mobile devices and their use of end-to-end encryption in safeguarding the privacy of their users have become a concern for some governments. WhatsApp messaging service has emerged as the most popular messaging app on mobile devices today. It uses end-to-end encryption which makes government and secret services efforts to combat organized crime, terrorists, and child pornographers technically impossible. Governments would like a “backdoor” into such apps, to use in accessing messages and have emphasized that they will only use the “backdoor” if there is a credible threat to national security. Users of WhatsApp have however, argued against a “backdoor”; they claim a “backdoor” would not only be an infringement of their privacy, but that hackers could also take advantage of it. In light of this security and privacy conflict between the end users of WhatsApp and government’s need to access messages in order to thwart potential terror attacks, this paper presents the advantages of maintaining E2EE in WhatsApp and why governments should not be allowed a “backdoor” to access users’ messages. This research presents the benefits encryption has on consumer security and privacy, and also on the challenges it poses to public safety and
Meta‐analysis for Surrogacy: Accelerated Failure Time Models and Semicompeting Risks Modeling

Summary There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using metaanalytical methods for quantification of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semicompeting risks setting, where we model the region where the surrogate endpoint occurs before the true endpoint. Several estimation methods and attendant inferential procedures are presented. In addition, between‐ and within‐trial methods for evaluating surrogacy are developed; a novel principal components procedure is developed for quantifying trial‐level surrogacy. The methods are illustrated by application to data from several studies in colorectal cancer.
A Classification System for Diabetic Patients with Machine Learning Techniques

Diabetes mellitus (DM) is a group of metallic disorder characterized by steep levels of blood glucose prolonged over a time. It results the defection in insulin production or improper action of the cells to the insulin produced. It is one of the significant public health care challenge worldwide. Diabetes exists in a body when pancreas does not construct enough hormone insulin or the human body is not being able to use the insulin properly. The diagnosis of diabetes (diagnosis, etiopathophysiology, therapy etc.) need to generate and process the vast amount of data. Data mining techniques have proven its usefulness and effectiveness in order to evaluate the unknown relationships or patterns if exists with such vast data. In the present work, five techniques based on machine learning namely, AdaBoost, LogicBoost, RobustBoost, Naïve Bayes and Bagging have been proposed for the analysis and prediction of DM patients. The proposed techniques are employed on the data set of Pima Indians Diabetes patients. The results computed are found to be very accurate with classification accuracy of 81.77% and 79.69% by bagging and AdaBoost techniques, respectively. Hence, the proposed techniques employed here are highly adorable, effective and efficient in order to predict the DM.
Pathological Factors Combine to Cause Hyperexcitability in Primary Afferent Neurons: Implications for Nociceptive Sensory Processing

Hyperexcitability in primary afferent neurons is necessary and sufficient to cause many forms of chronic pain. Several molecular changes have been linked to primary afferent neuron hyperexcitability, but developing better pain therapies remains challenging because most molecular changes have been studied in isolation. I investigated how hyperexcitability relies on combinations of molecular changes. First, I addressed an important feature of primary afferent neuron hyperexcitability wherein spiking pattern switches from transient spiking to repetitive spiking during sustained somatic depolarization. I measured the susceptibility of neurons to switch their spiking pattern by applying a virtual sodium conductance (gNa) using dynamic clamp. Second, I investigated how the switch from transient to repetitive spiking (i.e. a change in intrinsic excitability) interacted with changes affecting inhibitory synaptic input onto primary afferent neurons. GABA-mediated paradoxical excitation requires a combined shift in the GABA reversal potential (EGABA) and a change in intrinsic excitability. Third, I addressed whether the required combination of changes, initially demonstrated with dynamic clamp
A novel ensemble support vector machine model for land cover classification

Nowadays, support vector machines are widely applied to land cover classification although this method is sensitive to parameter selection and noise samples. AdaBoost is an effective approach to find a highly accurate classifier by combining many weak and accurate classifiers. In this article, a novel ensemble support vector machine model that uses AdaBoost approach is proposed to mitigate the influence of noises and error parameters with focus on application on land cover classification. The key characteristics of this approach are that (1) a novel noise filtering scheme that avoids the noisy examples based on fuzzy clustering and principal component analysis algorithm is proposed to remove both attribute noises and class noises to achieve an optimal clean set and (2) support vector machine classifiers, based on the particle swarm optimization algorithm, are seen to component classifiers. We then combined finally individual prediction through AdaBoost algorithm to induce the final classification results on this new training set. A set of experiments is conducted on land cover classification for testing the performance of the proposed algorithm. Experimental results show that the classification accuracy can be increased using our proposed learning model, which results in the smallest generalization error compared with the other learning methods.
On reducing learning time in context-dependent mappings

An approach to overcoming the slow convergence problems often associated with learning complex nonlinear mappings is presented. The mappings are learned in a context-dependent manner so that complex problems are decomposed into simpler subproblems corresponding to different contexts. While no general conditions for determining applicability the method have been found, its power is illustrated through experiments in controlling simulated robot manipulators in two and three degrees of freedom. The experiments also indicate that the method shows promising scale-up properties.
Investigating the distribution of password choices

The distribution of passwords chosen by users has implications for site security, password-handling algorithms and even how users are permitted to select passwords. Using password lists from four different web sites, we investigate if Zipf's law is a good description of the frequency with which passwords are chosen. We use a number of standard statistics, which measure the security of password distributions, to see if modelling the data using a simple distribution is effective. We then consider how much the password distributions from each site have in common, using password cracking as a metric. This shows that these distributions have enough high-frequency passwords in common to provide effective speed-ups for cracking passwords. Finally, as an alternative to a deterministic banned list, we will show how to stochastically shape the distribution of passwords, by occasionally asking users to choose a different password.
Supernova bounds on Weinberg’s Goldstone bosons

Recently, Weinberg proposed a scenario where Goldstone bosons may be masquerading as fractional cosmic neutrinos. We calculate the energy loss rates through the emission of these Goldstone bosons in a post-collapse supernova core. Invoking the well established emissivity bound from the Supernova 1987A observations and simulations, we find that nuclear bremsstrahlung processes can notably impose a bound on the Goldstone boson coupling to the Standard Model Higgs, g, dependent on the mass of the associated radial field, mr. For mr large enough compared with the temperature in the post-collapse supernova core, our bound is |g| < 0.011(mr/500 MeV) 2 , very competitive to that derived from collider experiments.
Intradermal Infection Model for Pathogenesis and Vaccine Studies of Murine Visceral Leishmaniasis

ABSTRACT The levels of protection found in vaccine studies of murine visceral leishmaniasis are significantly lower than for cutaneous leishmaniasis; whether this is due to the high-challenge murine model employed and/or is a consequence of differences required in tissue-specific local immune responses is not understood. Consequently, an intradermal murine model of visceral leishmaniasis has been explored. Intradermal inoculation established a chronic infection in susceptible mice which was associated with a pattern of parasite clearance with time postinfection in the liver and skin; in contrast, parasite persistence and expansion was observed in lymphoid tissue (spleen and draining lymph node). The course of disease found appears to be similar to those reported for subclinical canine and human visceral leishmaniasis. Clearance of parasites from the skin was correlated with an inflammatory response and the infiltration and activation of CD4+ and CD8+ T cells. In contrast, in lymphoid tissue (lymph node or spleen), the production of Th1/Th2 cytokines (interleukin-4 [IL-4], IL-10, and gamma interferon) appeared to correlate with parasite burden and pathogenesis. In vaccination experiments employing the Leishmania infantum D-13 (p80) antigen, significantly higher levels of protection were found with the intradermal murine model (29 to 7,500-fold more than naive controls) than were found with a low-dose intravenous infection model (9 to 173-fold). Thus, this model should prove useful for further investigation of disease pathogenesis as well as vaccine studies of visceral leishmaniasis.
Production Optimization of E. Coli Fermented Synthetic Spider Silk for Commercial Viability

Spider silk has impressive physical properties in the areas of strength, weight, toughness and elasticity, with commercial use currently limited as large-scale production has not been demonstrated. Transgenic work to synthetically replicate the spider silk proteins via E. coli has successfully been performed. Spider silk based products show promising characteristics, but the economic viability of synthetic spider silk production has not been evaluated. This work presents an analysis of the economic viability and environmental impact associated with the production of synthetic spider silk through E. coli fermentation. System models, validated with experimental data, were leveraged with economic and life cycle modeling to evaluate the sustainability of synthetic spider silk production. Results show protein yield, modeling scale, and processing technologies dramatically impact final silk protein cost as well as the global warming potential.
Long-Term Nicotine Treatment Decreases Striatal α6* Nicotinic Acetylcholine Receptor Sites and Function in Mice

α-Conotoxin MII-sensitive nicotinic acetylcholine receptors (nAChRs) are distinct from other subtypes in their relatively restricted localization to the striatum and some other brain regions. The effect of nicotine treatment on nAChR subtypes has been extensively investigated, with the exception of changes in α-conotoxin MII-sensitive receptor expression. We therefore determined the consequence of long-term nicotine administration on this subtype and its function. Nicotine was given in drinking water to provide a long-term yet intermittent treatment. Consistent with previous studies, nicotine exposure increased 125I-epibatidine and 125I-A85380 (3-[2-(S)-azetidinylmethoxy]pyridine), but not 125I-α-bungarotoxin, receptors in cortex and striatum. We observed an unexpected reduction (30%) in striatal 125I-α-conotoxin MII sites, which occurred because of a decrease in Bmax. This decline was more robust in older (>8-month-old) compared with younger (2–4-month-old) mice, suggesting age is important for nicotine-induced disruption of nAChR phenotype. Immunoprecipitation experiments using nAChR subunit-directed antibodies indicate that alterations in subunit-immunoreactivity with nicotine treatment agree with those in the receptor binding studies. To determine the relationship between striatal nAChR sites and function, we measured nicotine-evoked [3H]dopamine release. A decline was obtained with nicotine treatment that was caused by a selective decrease in α-conotoxin MII-sensitive but not α-conotoxin MII-resistant dopamine release. These results may explain previous findings that nicotine treatment decreased striatal nAChR-mediated dopamine function, despite an increase in [3H]nicotine (α4*) sites. The present data suggest that the α6* nAChR subtype represents a key factor in the control of dopamine release from striatum, which adapts to long-term nicotine treatment by down-regulation of α6* receptor sites and function.
Creating Metric-topological Maps for Large-scale Monocular SLAM

In the last very few years, monocular SLAM approaches based on bundle adjustment are achieving amazing results in terms of accuracy, computational efficiency, and density of the map. When such solutions are applied on large scenarios it is crucial for the system scalability to maintain a map representation that permits efficient map optimization and augmentation. In order to cope with such large maps, we present an on-the-fly partitioning technique which allows abstraction from the metric map to operate more efficiently. The result is a metric-topological arrangement where the areas with highly-connected observations are grouped in submaps weakly interconnected to each other. This is accomplished by progressively cutting a graph representation of the map, where the nodes are keyframes and the arcs between them represent their shared observations. The experimental results indicate that the proposed approach improves the efficiency of monocular SLAM and provides a metric-topological world representation suitable for other robotic tasks.
Fast feature matching for detailed point cloud generation

Structure from motion is a very popular technique for obtaining three-dimensional point cloud-based reconstructions of objects from un-organised sets of images by analysing the correspondences between feature points detected in those images. However, the point clouds stemming from usual feature point extractors such as SIFT are frequently too sparse for reliable surface recovery. In this paper we show that alternate feature descriptors such as A-KAZE, which provide denser coverage of images, yield better results and more detailed point clouds. Unfortunately, the use of a dramatically increased number of points per image poses a computational challenge. We propose a technique based on epipolar geometry restrictions to significantly cut down on processing time and an efficient implementation thereof on a GPU.
Time to spontaneous ductus arteriosus closure in full-term neonates

Objective The mean closure time of the ductus arteriosus (DA) in full-term neonates is presumed to be 1–2 days after birth; however, whether this rate is accurate throughout the neonatal period is still unclear. In addition, the clinical determinants that influence DA closure remain unknown. Methods Echocardiography was performed 1826 times (897 in boys, 929 in girls) in 1442 participants (732 boys, 710 girls). An iE33 colour Doppler echocardiograph supplied by Philips Electronics was employed to examine DA flow. Data regarding sex, birth date, examination date, method of delivery, mother's age, past deliveries, neonatal body weight and body height were also collected. The Statistical Analysis System makes statistical clarification of these queries possible. We examined the persistence of DA in full-term neonates and appropriate for gestational age (AGA) neonates in the early neonatal period using colour Doppler echocardiography, and a subsequent analysis with SAS. Results After performing multivariable analyses, the median DA persistency times were 27.42 and 45.10 h after birth in boys and girls, respectively. A statistically significant sex difference was observed (p<0.0001). Additionally, significant time differences were observed between vaginal and scheduled caesarean deliveries, at 26.97 and 28.93 h, respectively (p=0.0245). No significant differences were observed in the other variables. Conclusions Spontaneous DA closure time curves were clarified for the first time throughout the early neonatal period in full-term and AGA neonates. It was revealed that both sex and delivery method play important roles in time to DA closure.
Analysis of the GTPase motif of FlhF in the control of the number and location of polar flagella in Vibrio alginolyticus

Vibrio alginolyticus normally has a single polar flagellum whose number and placement are regulated positively by FlhF. FlhF is a GTPase and homolog of a signal recognition particle (SRP) protein called Ffh and SRP receptor FtsY. FlhF is located at the cell pole and directs formation of the flagellum. To study the mechanism of FlhF localization, we introduced random mutations into flhF by means of hydroxylamine and isolated mutants that could not generate the flagellum at the cell pole. The novel mutations were only mapped to the GTPase motif of FlhF. The mutant FlhF proteins showed reduced polar localization as compared to the wild type and still could associate with the membrane. These results support the assumption that the GTPase motif of FlhF plays a critical role in the polar localization of this protein during formation of the flagellum.
Graph Model for Chinese Spell Checking

This paper describes our system in the Bake-Off 2013 task of SIGHAN 7. We illustrate that Chinese spell checking and correction can be efficiently tackled with by utilizing word segmenter. A graph model is used to represent the sentence and a single source shortest path (SSSP) algorithm is performed on the graph to correct spell errors. Our system achieves 4 first ranks out of 10 metrics on the standard test set.
Higher-level mechanisms detect facial symmetry

The role of symmetry detection in early visual processing and the sensitivity of biological visual systems to symmetry across a wide range of organisms suggest that symmetry can be detected by low-level visual mechanisms. However, computational and functional considerations suggest that higher-level mechanisms may also play a role in facial symmetry detection. We tested this hypothesis by examining whether symmetry detection is better for faces than comparable patterns, which share low-level properties with faces. Symmetry detection was better for upright faces than for inverted faces (experiment 1) and contrast-reversed faces (experiment 2), implicating high-level mechanisms in facial symmetry detection. In addition, facial symmetry detection was sensitive to spatial scale, unlike low-level symmetry detection mechanisms (experiment 3), and showed greater sensitivity to a 45° deviation from vertical than is found for other aspects of face perception (experiment 4). These results implicate specialized, higher-level mechanisms in the detection of facial symmetry. This specialization may reflect perceptual learning resulting from extensive experience detecting symmetry in faces or evolutionary selection pressures associated with the important role of facial symmetry in mate choice and ‘mind-reading’ or both.
Usefulness of Anticoagulant Therapy in the Prevention of Embolic Complications in Patients with Acute Infective Endocarditis

Background. The use of anticoagulant therapy (ACT) in patients with acute infective endocarditis (IE) remains a controversial issue. Our study attempts to estimate the impact of ACT on the occurrence of embolic complications and the usefulness of ACT in the prevention of embolism in IE patients. Methods. The present authors analyzed 150 patients with left-sided IE. Embolisms including cerebrovascular events (CVE) and the use of ACT were checked at the time of admission and during hospitalization. Results. 57 patients (38.0%) experienced an embolic event. There was no significant difference in the incidence of CVE and in-hospital mortality between patients with and without warfarin use at admission, although warfarin-naïve patients were significantly more likely to have large (>1 cm) and mobile vegetation. In addition, there was no significant difference in the incidence of postadmission embolism and in-hospital death between patients with and without in-hospital ACT. On multivariate logistic regression analysis, ACT at admission was not significantly associated with a lower risk of embolism in patients with IE. Conclusions. The role of ACT in the prevention of embolism was limited in IE patients undergoing antibiotic therapy, although it seems to reduce the embolic potential of septic vegetation before treatment.