Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular phylogeny of elapid snakes and a consideration of their biogeographic history

Evolutionary relationships among the major elapid clades, particularly the taxonomic position of the partially aquatic sea kraits (Laticauda) and the fully aquatic true sea snakes have been the subject of much debate. To discriminate among existing phylogenetic and biogeographic hypotheses, portions of both the 16S rRNA and cytochrome b mitochondrial DNA genes were sequenced from 16 genera and 17 species representing all major elapid snake clades from throughout the world and two non-elapid outgroups. This sequence data yielded 181 informative sites under parsimony. Parsimony analyses of the separate data sets produced trees of broad agreement although less well supported than the single most parsimonious tree resulting from the combined analyses. These results support the following hypotheses: (1) the Afro-Asian cobra radiation forms one or more sister groups to other elapids, (2) American and Asian coral snakes form a clade, corroborating morphological studies, (3) Bungarus forms a sister group to the hydrophiines comprised of Laticauda, terrestrial AustraloPapuan elapids and true sea snakes, (4) Laticauda and true sea snakes do not form a monophyletic group but instead each group shares an independent history with terrestrial Australo-Papuan elapids, corroborating previous studies, (5) a lineage of Melanesian elapids forms the sister group to Laticauda, terrestrial Australian species and true sea snakes. In agreement with previous morphologically based studies, the sequence data suggests that Bungarus and Laticauda represent transitional clades between the elapine ‘palatine erectors’ and hydrophiine ‘palatine draggers’. Both intra and inter-clade genetic distances are considerable, implying that each of the major radiations have had long independent histories. I suggest an African, Asian, or Afro-Asian origin for elapids as a group, with independent Asian origins for American coral snakes and the hydrophiines.
E-correlator: an entropy-based alert correlation system

With the rapid size and complexity growth of computer networks, network supervisors are now facing a new problem, which is to analyze and manage the large amounts of security alerts that can be generated by security devices. Alert correlation systems attempt to solve this problem by finding the similarity and causality relationships between raw alerts and providing high-level view of the network under surveillance. Several alert correlation methods have been proposed recently to detect known attack scenarios. This paper focuses on how to develop an intrusion-alert correlation system according to the information existed in the raw alerts without using any predefined knowledge. For this purpose, first, we define the concept of alert partial entropy to find the alert clusters with the same information. Then, we represent the alert clusters by an intelligible notation called hyper-alerts. The network supervisor can reduce the number of hyper-alerts based on the principle of maximum entropy or by using the concept of hyper-alerts partial entropy. For more visualization, we define the hyper-alerts graph, which provides a global view of intrusion alerts. Our results show that the proposed entropy-based alert correlation system E-correlator can simplify the analysis of large number of alerts. We achieved the promising reduction ratio of 99.98% in LLS_DDOS_1. 0 attack scenario in DARPA2000 dataset while the constructed hyper-alerts have enough information to discover the attacker, the victim, and the attack scenario. Copyright © 2014 John Wiley & Sons, Ltd.
Mechanical thrombectomy for acute ischemic stroke with occlusion of the M2 segment of the middle cerebral artery: a meta-analysis

Background Endovascular thrombectomy has demonstrated benefit for patients with acute ischemic stroke from proximal large vessel occlusion. However, limited evidence is available from recent randomized trials on the role of thrombectomy for M2 segment occlusions of the middle cerebral artery (MCA). Methods We conducted a systematic review and meta-analysis to investigate clinical and radiographic outcomes, rates of hemorrhagic complications, and mortality after M2 occlusion thrombectomy using modern devices, and compared these outcomes against patients with M1 occlusions. Recanalization was defined as Thrombolysis in Cerebral Infarction (TICI) 2b/3 or modified TICI 2b/3. Results A total of 12 studies with 1080 patients with M2 thrombectomy were included in our analysis. Functional independence (modified Rankin Scale 0–2) rate was 59% (95% CI 54% to 64%). Mortality and symptomatic intracranial hemorrhage rates were 16% (95% CI 11% to 23%) and 10% (95% CI 6% to 16%), respectively. Recanalization rates were 81% (95% CI 79% to 84%), and were equally comparable for stent-retriever versus aspiration (OR 1.05; 95% CI 0.91 to 1.21). Successful M2 recanalization was associated with greater rates of favorable outcome (OR 4.22; 95% CI 1.96 to 9.1) compared with poor M2 recanalization (TICI 0–2a). There was no significant difference in recanalization rates for M2 versus M1 thrombectomy (OR 1.05; 95% CI 0.77 to 1.42). Conclusions This meta-analysis suggests that mechanical thrombectomy for M2 occlusions that can be safely accessed is associated with high functional independence and recanalization rates, but may be associated with an increased risk of hemorrhage.
The Measure Hypothesis and Efficiency of Polynomial Time Approximation Schemes

A polyomial time approximation scheme for an optimization problem X is an algorithm A such that for each instance x of X and each ǫ > 0, A computes a (1 + ǫ)-approximate solution to instance x of X in time is O(|x|f(1/ǫ)) for some function f . If the running time of A is instead bounded by g(1/ǫ) · |x|O(1) for some function g, A is called an efficient polynomial time approximation scheme. PTAS denotes the class of all NP optimization problems for which a polytime approximation scheme exists, and EPTAS is the class of all such problems for which an efficient polytime approximation scheme exists. It is an open question whether P 6= NP implies the strictness of the inclusion EPTAS ⊆ PTAS. Bazgan [2] and independently Cesati and Trevisan [5] gave a separation under the stronger assumption FPT 6= W [P ]. In this paper we prove EPTAS ( PTAS under some different assumption, namely existence of NP search problems ΠR with a superpolynomial lower bound for the deterministic time complexity. This assumption is weaker than the NP Machine Hypothesis [15] and hence is implied by the Measure Hypothesis μp(NP ) 6= 0. Furthermore, using a sophisticated combinatorial counting argument we construct a recursive oracle under which our assumption holds but that of Cesati and Trevisan does not hold, implying that using relativizing proof techniques one cannot show that our assumption implies FPT 6= W [P ].
The Priming Effect of Military Service on Creativity Performance

This study investigated the service priming effect on creativity performance. In three experiments, the service priming was manipulated in three ways (Army priming, Air Force priming, and a Neutral condition). Participants' performances on the Chinese Remote Associates Test (CRAT), insight problems, and critical thinking problems were accordingly measured in each experiment. Results showed that the Air Force priming improved creativity and the Army priming enhanced critical thinking. The results suggest that the constructions and processes of these two manipulations are different. In addition, results also suggested that the branch of military service moderates the relationship between the service priming and the performance of creativity.
Mapping Brain Activity Using Wearable EEG Sensors for Mobile Applications

Brain computer interface (BCI) has been used to map brain activity. This mapping is further used for signal classification to generate various control signals. Electroencephalography (EEG) is used to record electrical fields that represent the brain signals and are generated due to the local brain function. EEG recordings for medical diagnosis and prognosis purposes require a specialized laboratory setup. Recently wearable EEG sensor headsets have become commercially available that can be easily setup to record brain activity non invasively. In this paper brain activity mapping using these wearable sensors has been presented. The mapping is performed on a mobile device by connecting the scanner directly to the mobile device over a wireless bluetooth interface. The processing capability of current day smart phones can be effectively used to develop a completely mobile EEG scanner. A limitation of these headsets is the number of sensors available for recording brain signals. Specialized signal processing algorithms can be used to produce clinically acceptable EEG recordings using these headsets. An inherent advantage of using BCI with these wearable sensors is providing support to disabled persons in a non medical facility, e.g. home. It can also be used to provide a platform for remote health monitoring of brain related diseases and rehabilitation of patients.
Analysis of a Temperature-Sensitive Mutant Rotavirus Indicates that NSP2 Octamers Are the Functional Form of the Protein

ABSTRACT Evidence that NSP2 plays a role in packaging and replication comes from studies on tsE(1400), a rotavirus mutant with a temperature-sensitive (ts) lesion in the NSP2 gene. Cells infected with tsE and maintained at nonpermissive temperature contain few replication-assembly factories (viroplasms) or replication intermediates and produce virus particles that are mostly empty. Sequence analysis has indicated that an A152V mutation in NSP2 is responsible for the ts phenotype of tsE. To gain insight into the effect of the mutation on the octameric structure and biochemical activities of tsE NSP2, the protein was expressed in bacteria and purified to homogeneity. Analytical ultracentrifugation showed that tsE NSP2 formed octamers which, like those formed by wild-type (wt) NSP2, undergo conformational change into more compact structures upon binding of nucleotides. However, exposure to Mg2+ and the nonpermissive temperature caused disruption of the tsE octamers and yielded the formation of polydisperse NSP2 aggregates, events not observed with wt octamers. Biochemical analysis showed that the RNA-binding, helix-destabilizing and NTPase activities of tsE NSP2 were significantly less at the nonpermissive temperature than at the permissive temperature. In contrast, these activities for wt NSP2 were higher at the nonpermissive temperature. Our results indicate that the octamer is the fully functional form of NSP2 and the form required for productive virus replication. The propensity of tsE NSP2 to form large aggregates provides a possible explanation for the inability of the protein to support packaging and/or replication in the infected cell at the nonpermissive temperature.
Improved Algorithms for Economic Lot Size Problems

Many problems in inventory control, production planning, and capacity planning can be formulated in terms of a simple economic lot size model proposed independently by A. S. Manne (1958) and by H. M. Wagner and T. M. Whitin (1958). The Manne-Wagner-Whitin model and its variants have been studied widely in the operations research and management science communities, and a large number of algorithms have been proposed for solving various problems expressed in terms of this model, most of which assume concave costs and rely on dynamic programming. In this paper, we show that for many of these concave cost economic lot size problems, the dynamic programming formulation of the problem gives rise to a special kind of array, called a Monge array. We then show how the structure of Monge arrays can be exploited to obtain significantly faster algorithms for these economic lot size problems. We focus on uncapacitated problems, i.e., problems without bounds on production, inventory, or backlogging; capacitated problem.
Comparative analysis of ELISA , nonradioactive molecular hybridization and PCR for the detection of prunus necrotic ringspot virus in herbaceous and Prunus hosts

Three methods were compared for the detection of prunus necrotic ringspot virus in herbaceous and woody plants: DAS-ELISA, nonisotopic dot-blot hybridization and reverse transcriptional polymerase chain reaction (RT-PCR). When purified virus preparations were used, the detection limit of the RT-PCR technique was 1·28 pg mL whereas nonisotopic molecular hybridization and DAS-ELISA allowed detection of 0·8 ng mL and 4 ng mL, respectively. Several sample processing procedures were evaluated for virus detection by the nonisotopic molecular hybridization technique. When a very short and simple sample processing method was used, the detection limit of the nonisotopic molecular hybridization technique was 25 times higher than that of DAS-ELISA and 625 times lower than that of RTPCR. A comparison of the level of virus accumulation in mature fruits and in leaf tissue showed that, on average, 125 times more virus was found in the fruits.
FRAX and Risk of Vertebral Fractures: The Fracture Intervention Trial

The validity of the WHO 10‐yr probability of major osteoporotic fracture model (FRAX) for prediction of vertebral fracture has not been tested. We analyzed how well FRAX for major osteoporotic fractures, with and without femoral neck BMD (FN BMD), predicted the risk of vertebral fracture. We also compared the predictive validity of FRAX, FN BMD, and prevalent vertebral fracture detected by radiographs at baseline alone or in combination to predict future vertebral fracture. We analyzed data from the placebo groups of FIT (3.8‐yr follow‐up, n = 3221) with ORs and areas under receiver operating characteristics (ROC) curves (AUC). FRAX with and without FN BMD predicted incident radiographic vertebral fracture. The AUC was significantly greater for FRAX with FN BMD (AUC = 0.71) than FRAX without FN BMD (AUC = 0.68; p = 0.002). Prevalent vertebral fracture plus age and FN BMD (AUC = 0.76) predicted incident radiographic vertebral fracture as well as a combination of prevalent vertebral fracture and FRAX with FN BMD (AUC = 0.75; p = 0.76). However, baseline vertebral fracture status plus age and FN BMD (AUC = 0.76) predicted incident radiographic vertebral fracture significantly better than FRAX with FN BMD (AUC = 0.71; p = 0.0017). FRAX for major osteoporotic fractures (with and without FN BMD) predicts vertebral fracture. However, once FN BMD and age are known, the eight additional risk factors in FRAX do not significantly improve the prediction of vertebral fracture. A combination of baseline radiographic vertebral fracture, FN BMD, and age is the strongest predictor of future vertebral fracture.
A review of methodologies for natural-language-facilitated human–robot cooperation

Natural-language-facilitated human–robot cooperation refers to using natural language to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, natural-language-facilitated human–robot cooperation research has received increasing attention. Typical natural-language-facilitated human–robot cooperation scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, which can reveal latest methodologies of using natural language to facilitate human–robot cooperation, is missing. In this review, we comprehensively investigated natural-language-facilitated human–robot cooperation methodologies, by summarizing natural-language-facilitated human–robot cooperation research as three aspects (natural language instruction understanding, natural language-based execution plan generation, knowledge-world mapping). We also made in-depth analysis on theoretical methods, applications, and model advantages and disadvantages. Based on our paper review and perspective, future directions of natural-language-facilitated human–robot cooperation research were discussed.
Neural-Based Adaptive Output-Feedback Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems

In this paper, we consider the problem of observer-based adaptive neural output-feedback control for a class of stochastic nonlinear systems with nonstrict-feedback structure. To overcome the design difficulty from the nonstrict-feedback structure, a variable separation approach is introduced by using the monotonically increasing property of system bounding functions. On the basis of the state observer, and by combining the adaptive backstepping technique with radial basis function neural networks' universal approximation capability, an adaptive neural output feedback control algorithm is presented. It is shown that the proposed controller can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in the sense of mean quartic value. Simulation results are provided to show the effectiveness of the proposed control scheme.
Immune Cells Detection of the In Vivo Rejecting Heart in USPIO-Enhanced Magnetic Resonance Imaging

Contrast-enhanced magnetic resonance imaging (MRI) is useful to study the infiltration of immune cells, in particular macrophages. Contrast agents, for example ultra-small superparamagnetic iron oxide (USPIO) particles, administered intravenously into the blood stream will be engulfed by macrophages circulating in the circulation system. When a transplanted heart rejects, macrophages and other immune cells will infiltrate the rejecting tissue. Imaged by T2* weighted MRI, USPIO-labeled macrophages will display dark pixel intensities. Detecting the presence of USPIO particles in the images facilitates the study of heart rejection. We cast the problem of detecting the presence of USPIO-labeled myocardium in the framework of spectral graph theory, and treat our decision function as a level set function on the image. The pixels with positive level set values correspond to the presence of immune cells, and negative to the absence. When the image is modeled by a graph, the spectral analysis of the graph Laplacian provides a basis to represent the level set function. We develop from the Cheeger constant of the graph an objective functional of the level set function. The minimization of the objective leads to the optimal level set function. Experimental results suggest the feasibility of our approach in the study of rejecting hearts
Newton's Method for a Class of Weakly Singular Optimal Control Problems

Newton's method for optimal control of highly nonlinear partial differential equations is analyzed using a 2-norm technique. We consider the case where neither the linearization of the equality constraint e characterizing the differential equation is surjective nor a second order sufficient optimality condition holds for the topology on which e is well defined. Such problems occur, for instance, in optimal control of semilinear elliptic equations or for parameter estimation problems. Despite the above mentioned difficulties, sufficient conditions for second order convergence are obtained.
Milk removal in familiar and unfamiliar surroundings: concentrations of oxytocin, prolactin, cortisol and β–endorphin

Summary Eight cows were machine milked either in an operating theatre or in their familiar barn. During the experiments, milk flow curves were recorded and blood samples were taken for determination of concentrations of oxytocin, prolactin, cortisol and β–endorphin. The milking cluster was attached without udder preparation. After cessation of milk flow, air was blown into the vagina for 2 min. When milk flow had stopped again, 1 i.u. oxytocin and finally 10 i.u. oxytocin were injected to remove the remaining milk. After the start of milking, oxytocin remained basal in unfamiliar, but increased in familiar surroundings. Therefore, during normal milking only 9% of total milk was removed in unfamiliar, whereas 79% was available in familiar surroundings. In response to subsequent vaginal stimulation in the operating theatre, oxytocin increased transiently in five cows and 15–71% of the milk was removed in these animals. In the other three cows in the operating theatre, oxytocin remained basal during vaginal stimulation, and no more milk was available. After injection of 1 i.u. oxytocin, 56 and 11%, and after injection of 10 i.u. oxytocin, 13 and 8% of milk was removed in unfamiliar and familiar surroundings respectively. Concentrations of prolactin increased during the course of milking in both treatments. Premilking concentrations of cortisol and β–endorphin were elevated in unfamiliar as compared with familiar surroundings. During the course of milking, cortisol increased slightly and β–endorphin decreased in unfamiliar, whereas both hormones increased markedly during milking in familiar surroundings. We conclude that disturbed milk removal in unfamiliar surroundings is due to central inhibition of oxytocin release during normal milking and partly also to a response to vaginal stimulation. This blockade is possibly associated with elevated concentrations of β–endorphin.
Predicción de caudales medios diarios en la cuenca del Amazonas aplicando redes neuronales artificiales y el modelo neurodifuso ANFIS

Resumen. El presente artículo muestra los resultados obtenidos al aplicar redes neuronales y el modelo neurodifuso ANFIS para la predicción de caudales medios diarios en una sección de la cuenca del Amazonas. Se aplicaron los pasos que componen la metodología KDD Knowledge Discovery in Databases sobre la información hidrológica recolectada de las estaciones del servicio de observación SO HYBAM y sobre la información climatológica recolectada del Instituto de Investigación Internacional de Clima y Sociedad. La simulación se llevó a cabo en el software Matlab® donde se evaluó el comportamiento de ambos modelos, el estudio mostró que al utilizar técnicas de Inteligencia Artificial se consiguió coeficientes de correlación CC superiores al 97%, un error medio porcentual absoluto MAPE por debajo del 10% y otras 4 métricas que fueron utilizadas en esta investigación. Los resultados muestran que estos modelos pueden etiquetarse como buenos modelos para la predicción, gracias a su capacidad predictiva en comparación con métodos tradicionales del tipo lineal.
An N-gram Based Distributional Test for Authorship Identification

In this paper, a novel method for the authorship identification problem is presented. Based on character level text segmentation we study the disputed text’s N-grams distributions within the authors’ text collections. The distribution that behaves most abnormally is identified using the Kolmogorov Smirnov test and the corresponding Author is selected as the correct one. Our method is evaluated using the test sets of the 2004 ALLC/ACH Ad-hoc Authorship Attribution Competition and its performance is comparable with the best performances of the participants in the competition. The main advantage of our method is that it is a simple, not parametric way for authorship attribution without the necessity of building authors’ profiles from training data. Moreover, the method is language independent and does not require segmentation for languages such as Chinese or Thai. There is also no need for any text preprocessing or higher level processing, avoiding thus the use of taggers, parsers, feature selection strategies, or the use of other language dependent NLP tools.
Management of Choroidal Neovascularization in Uveitis

Choroidal neovascularization is an uncommon but potentially blinding complication of posterior uveitis. In this review, we will examine some of the more common conditions that may be associated with this problem and the varying methods of management of choroidal neovascular membranes (CNVMs) in uveitis. We review current and potential treatment options and acknowledge the need for randomized clinical control trials in the management of this condition.