Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Demultiplexing of Network Packets by Automatic Parsing

Packet filters are a mechanism for efficiently demultiplexing network packets to application endpoints. There is currently no general, formal specification method for packet filters that allows for easy or efficient composition of specifications. In this paper we present an automatic approach that achieves all of these goals. We approach packet filter specification as a language recognition problem: each filter is represented by a context-free grammar, whose language is the set of packets the filter should accept. Thus, packet filters can be formulated through a general, well defined specification; further, the grammar-based approach simplifies filter composition, which is essential where. Read complete abstract on page 2.
Generalized Hyperbolic Distributions in Futures Hedge

Under martingale and joint-normality assumptions, various optimal hedge ratios are identical to the minimum variance hedge ratio. As empirical studies usually reject the joint-normality assumption, we propose the generalized hyperbolic distribution as the joint log-return distribution of the spot and futures. Using the parameters in this distribution, we estimate several most widely-used optimal hedge ratios: minimum variance, maximum Sharpe measure and minimum generalized semivariance. Under mild assumptions on the parameters, we find that these hedge ratios are identical. Empirical studies show that our proposed models fit the TAIEX futures and S & P 500 futures very well. Numerical results for different optimal hedge ratios also verify our theoretical observations. Regarding the equivalence of these three optimal hedge ratios, our analysis suggests that the martingale property plays a much important role than the joint distribution assumption.
A High-Level Reference Model for Reusable Object-Level Coordination Support in Groupware Applications

The success of groupware software largely depends on its capability for being reused in different collaborative scenarios without requiring significant software development efforts or user technical involvement. During the last decade several toolkits, frameworks, and specialized middleware software layers have been proposed as potential solutions to the groupware reusability problem. Those solutions cover common groupware functionality such as group formation and management, group awareness, shared workspace management, etc. This paper is focused on the reusable support to one of these common functionalities: the so-called object-level coordination that deals with multiple participants' sequential or simultaneous access to the same set of shared objects in a collaborative setting. The paper compares existing object-level coordination proposals and analyzes their capabilities and level of reuse. Starting from that analysis, and using a bottom-up approach, the paper also proposes a high-level reference model that identifies the desirable set of required functional elements, as well as their relationships, that reusable object-level coordination support should contain. The purpose of this reference model is twofold: to be used as a comparison framework for analyzing existing or yet-to-come object-level coordination building blocks; and, to be used as a starting point for developing new object-level coordination solutions (or redesigning existing ones) satisfying the whole set of requirements implicitly collected in the model. In addition to detailing the proposed reference model, the paper also illustrates and discusses both potential ways of using it
Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks

Learning an input-output mapping from a set of examples, of the type that many neural networks have been constructed to perform, can be regarded as synthesizing an approximation of a multidimensional function (that is, solving the problem of hypersurface reconstruction). From this point of view, this form of learning is closely related to classical approximation techniques, such as generalized splines and regularization theory. A theory is reported that shows the equivalence between regularization and a class of three-layer networks called regularization networks or hyper basis functions. These networks are not only equivalent to generalized splines but are also closely related to the classical radial basis functions used for interpolation tasks and to several pattern recognition and neural network algorithms. They also have an interesting interpretation in terms of prototypes that are synthesized and optimally combined during the learning stage.
Unsupervised Neural Architecture for Saliency Detection

We propose a novel neural network architecture for visual saliency detections, which utilizes neurophysiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neurophysiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.
Consequences of Delayed Diagnosis in Treatment of Retinoblastoma

Objective: One of the primary factors in managing patients with retinoblastoma is early diagnosis. The main idea of this study was to recognize the consequences of delay in diagnosis on therapy of the disease. Methods: A retrospective review of all children with proven retinoblastoma, who had presented to MAHAK hospital in Tehran, from April 2007 to Dec 2011, was performed. Grouping of intraocular tumors was applied as A to E according to International Classification of Retinoblastoma. Findings : There were 157 (91 boys) children eligible for study. The mean age was 1.21±0.11 years with average delay in diagnosis of 3.4±0.53 months. Classification of D group in both unilateral (93 patients) and bilateral tumors was the largest category. A significant relation (P=0.05) between delayed diagnosis time and tumor grouping was evident. The most frequent symptoms were leukocoria and strabismus. Age was significantly lower in the subgroup of bilateral tumors than in unilateral retinoblastomas (0.6±0.12 year vs 1.6±0.15 years). The diagnosis was delayed in subgroup of extra ocular retinoblastoma more than in intraocular tumors (8.7±2.9 months vs 2.9±0.52 months). Conclusion: The authors recommend early referring of suspected cases to ophthalmologists and pediatric oncologists and to organize educational programs to publisize signs and symptoms of the disease such as leukocoria, strabismus and ocular inflammatory disorders through national media. In conclusion, early diagnosis of retinoblastoma can be the primary factor in managing the patients as the delay in diagnosis accounts for highly advanced disease and poor prognosis.
Extraction of Semantic Relations between Concepts with KNN Algorithms on Wikipedia

This paper presents methods for extraction of semantic relations be- tween words. The methods rely on the k-nearest neighbor algorithms and two semantic similarity measures to extract relations from the abstracts of Wikipe- dia articles. We analyze the proposed methods and evaluate their performance. Precision of the extraction with the best method achieves 83%. We also present an open source system which effectively implements the described algorithms.
Lazy receiver processing (LRP): a network subsystem architecture for server systems

The explosive growth of the Internet, the widespread use of WWW-related applications, and the increased reliance on client-server architectures places interesting new demands on network servers. In particular, the operating system running on such systems needs to manage the machine’s resources in a manner that maximizes and maintains throughput under conditions of high load. We propose and evaluate a new network subsystem architecture that provides improved fairness, stability, and increased throughput under high network load. The architecture is hardware independent and does not degrade network latency or bandwidth under normal load conditions.
Rapid Microarray-Based Method for Monitoring of All Currently Known Single-Nucleotide Polymorphisms Associated with Parasite Resistance to Antimalaria Drugs

ABSTRACT Parasite drug resistance is partly conferred by single-nucleotide polymorphisms (SNPs), and monitoring them has been proposed as an alternative to monitoring drug resistance. Therefore, techniques are required to facilitate analyses of multiple SNPs on an epidemiological scale. We report a rapid and affordable microarray technique for application in epidemiological studies of malaria drug resistance. We have designed a multiwell microarray that is used in conjunction with PCR-amplified target genes implicated in the drug resistance of malaria with subsequent one-tube minisequencing using two fluorochromes. The drug-resistance-associated genes pfdhfr, pfdhps, pfcrt, pfmdr1, and pfATPase were amplified and analyzed for cultured Plasmodium falciparum strains and from field samples. We obtained a specificity of 94%, and comparison of field sample results to those of restriction fragment length polymorphism (RFLP) typing resulted in an overall consistency of >90%, except for pfdhfr51, for which most discrepancies were due to false determinations by RFLP of mixed infections. The system is sufficiently sensitive to assay parasites in clinical malaria cases and in most asymptomatic cases, and it allows high throughput with minimal hands-on time. The cost for the assay has been calculated as 0.27 euros/SNP (US$0.33), which is below the cost incurred with other systems. Due to the simplicity of the approach, newly identified SNPs can be incorporated rapidly. Such a monitoring system also makes it possible to identify the reemergence of drug-susceptible parasites once a drug has been withdrawn.
Persistent effects of a severe drought on Amazonian forest canopy

Recent Amazonian droughts have drawn attention to the vulnerability of tropical forests to climate perturbations. Satellite and in situ observations have shown an increase in fire occurrence during drought years and tree mortality following severe droughts, but to date there has been no assessment of long-term impacts of these droughts across landscapes in Amazonia. Here, we use satellite microwave observations of rainfall and canopy backscatter to show that more than 70 million hectares of forest in western Amazonia experienced a strong water deficit during the dry season of 2005 and a closely corresponding decline in canopy structure and moisture. Remarkably, and despite the gradual recovery in total rainfall in subsequent years, the decrease in canopy backscatter persisted until the next major drought, in 2010. The decline in backscatter is attributed to changes in structure and water content associated with the forest upper canopy. The persistence of low backscatter supports the slow recovery (>4 y) of forest canopy structure after the severe drought in 2005. The result suggests that the occurrence of droughts in Amazonia at 5–10 y frequency may lead to persistent alteration of the forest canopy.
Study on the exponential path tracking control of robot manipulators via direct adaptive methods

The exponential transformation is applied to obtain transformed robot dynamics. This is used to derive several adaptive control algorithms that achieve exponential path tracking. In contrast to the existing composite adaptive control method, where both the tracking error and the prediction error are used and persistent excitation (PE) is required, the proposed strategy requires only the tracking error. This makes the control structure much simpler and easier to implement. The main contribution of this work is the complete removal of the PE requirement as opposed to relaxing it to semi-PE. The fundamental idea introduced for exponential stability analysis is conceptually simple and global results are obtained. <<ETX>>
NUCLEAR-CYTOPLASMIC RELATIONS IN THE MITOSIS OF SEA URCHIN EGGS

Sea urchin eggs were cut into halves. The nucleate and anucleate halves and whole eggs were irradiated with γ-rays and then fertilized with normal sperm. The first mitosis of the diploid half-egg was more delayed than the division of the whole egg. There was a small, but highly significant, delay of the mitosis of the haploid half-egg, thus demonstrating cytoplasmic sensitivity to ionizing radiation. Since the sensitivity of nucleate cells is influenced by cytoplasmic volume, the problem of the role of cytoplasm in repair is considered in relation to these data and other reports in the literature.
Dopaminergic Input to the Inferior Colliculus in Mice

The response of sensory neurons to stimuli can be modulated by a variety of factors including attention, emotion, behavioral context, and disorders involving neuromodulatory systems. For example, patients with Parkinson’s disease (PD) have disordered speech processing, suggesting that dopamine alters normal representation of these salient sounds. Understanding the mechanisms by which dopamine modulates auditory processing is thus an important goal. The principal auditory midbrain nucleus, the inferior colliculus (IC), is a likely location for dopaminergic modulation of auditory processing because it contains dopamine receptors and nerve terminals immunoreactive for tyrosine hydroxylase (TH), the rate-limiting enzyme in dopamine synthesis. However, the sources of dopaminergic input to the IC are unknown. In this study, we iontophoretically injected a retrograde tracer into the IC of mice and then stained the tissue for TH. We also immunostained for dopamine beta-hydroxylase (DBH), an enzyme critical for the conversion of dopamine to norepinephrine, to differentiate between dopaminergic and noradrenergic inputs. Retrogradely labeled neurons that were positive for TH were seen bilaterally, with strong ipsilateral dominance, in the subparafascicular thalamic nucleus (SPF). All retrogradely labeled neurons that we observed in other brain regions were TH-negative. Projections from the SPF were confirmed using an anterograde tracer, revealing TH-positive and DBH-negative anterogradely labeled fibers and terminals in the IC. While the functional role of this dopaminergic input to the IC is not yet known, it provides a potential mechanism for context dependent modulation of auditory processing.
Speech Enhancement Using Spectral Subtraction Based on a Modified Noise Minimum Statistics Estimation

In this paper, we use the spectral subtraction method to reduce non-stationary angle grinder noise of speech signal. Motor based devices generate acoustic noise that often contains a wide-band part plus some limited number of dominant sinusoidal signals. This noise disturbs the audibility of speech signals used for ordinary daily communication. The spectral subtraction requires an estimate of the noise, here, we present a novel approach based on a multi-band minimum statistics. The performance of the proposed algorithm is tested under various working conditions of an angle grinder. Change in angle grinder working condition changes noise statistics,hence, the noise becomes non-stationary. Objective and subjective measures reveal that our proposed algorithm can eliminate the noise well enough, resulting in a minimum speech distortion and musical noise in the processed speech signal.
Frizzled2 signaling regulates growth of high-risk neuroblastomas by interfering with β-catenin-dependent and β-catenin-independent signaling pathways

Frizzled2 (FZD2) is a receptor for Wnts and may activate both canonical and non-canonical Wnt signaling pathways in cancer. However, no studies have reported an association between FZD2 signaling and high-risk NB so far. Here we report that FZD2 signaling pathways are critical to NB growth in MYCN-single copy SK-N-AS and MYCN-amplified SK-N-DZ high-risk NB cells. We demonstrate that stimulation of FZD2 by Wnt3a and Wnt5a regulates β-catenin-dependent and –independent Wnt signaling factors. FZD2 blockade suppressed β-catenin-dependent signaling activity and increased phosphorylation of PKC, AKT and ERK in vitro, consistent with upregulation of β-catenin-independent signaling activity. Finally, FZD2 small interfering RNA knockdown suppressed tumor growth in murine NB xenograft models associated with suppressed β-catenin-dependent signaling and a less vascularized phenotype in both NB xenografts. Together, our study suggests a role for FZD2 in high-risk NB cell growth and provides a potential candidate for therapeutic inhibition in FZD2-expressing NB patients.
Quasi-Resonant DC-Link Inverter With a Reduced Number of Active Elements

In this paper, a new scheme of a parallel quasi-resonant dc-link inverter (PQRDCLI) for electrical drive applications is described. Principles of the soft-switching inverter operation for bidirectional energy transmission are presented. A PQRDCLI analysis with the aid of simulations and experimental tests is carried out. The circuit features relatively simple topological structure and moderate overcurrent stress of components. A robust control strategy of the quasi-resonant circuit operation with an inverter output voltage dv/dt limitation has been achieved.
Dynamically responsive intervention for tremor suppression

The DRIFTS (Dynamically Responsive Intervention For Tremor Suppression) project aims to create wearable active orthoses that suppress upper-limb tremor while allowing natural movement. We present an overview this multidisciplinary project. This project is financially supported by the European Commission's Fifth Framework Programme and aims to create proof-of-concept prototypes of wearable active orthoses for the suppression of upper limb tremor while preserving natural movement. Another major goal of the project is the development of a prototyping and evaluation platform for the future elaboration of wearable ambulatory tremor suppression devices. The prototyping platform will be used to assess the efficacy of available sensing, actuating, and control technologies for tremor suppression.
Clozapine-Induced Obsessive-Compulsive Symptoms in Schizophrenia: A Critical Review

Obsessive-compulsive disorder (OCD) is rarely associated with schizophrenia, whereas 20 to 30% of schizophrenic patients, suffer from comorbid obsessive-compulsive symptoms (OCS). So far no single pathogenetic theory convincingly explained this fact suggesting heterogeneous subgroups. Based on long-term case observations, one hypothesis assumes that second-onset OCS in the course of schizophrenia might be a side effect of second generation antipsychotics (SGA), most importantly clozapine (CLZ). This review summarizes the supporting epidemiological and pharmacological evidence: Estimations on prevalence of OCS increase in more recent cross-sectional studies and in later disease stages. Longitudinal observations report the de novo-onset of OCS under clozapine treatment. This association has not been reported with first generation antipsychotics (FGA) or SGAs with mainly dopaminergic mode of action. Finally, significant correlations of OCS-severity with duration of treatment, dose and serum levels suggest clozapine-induced OCS. However, supposed causal interactions need further verifications. It is also unclear, which neurobiological mechanisms might underlie the pathogenetic process. Detailed genotypic and phenotypic characterizations of schizophrenics with comorbid OCS regarding neurocognitive functioning and activation in sensitive tasks of functional magnetic imaging are needed. Multimodal large-scaled prospective studies are necessary to define patients at risk for second-onset OCS and to improve early detection and therapeutic interventions.
Modulation of Mitochondrial Proteome and Improved Mitochondrial Function by Biventricular Pacing of Dyssynchronous Failing Hearts

Background—Cardiac resynchronization therapy (CRT) improves chamber mechanoenergetics and morbidity and mortality of patients manifesting heart failure with ventricular dyssynchrony; however, little is known about the molecular changes underlying CRT benefits. We hypothesized that mitochondria may play an important role because of their involvement in energy production. Methods and Results—Mitochondria isolated from the left ventricle in a canine model of dyssynchronous or resynchronized (CRT) heart failure were analyzed by a classical, gel-based, proteomic approach. Two-dimensional gel electrophoresis revealed that 31 mitochondrial proteins where changed when controlling the false discovery rate at 30%. Key enzymes in anaplerotic pathways, such as pyruvate carboxylation and branched-chain amino acid oxidation, were increased. These concerted changes, along with others, suggested that CRT may increase the pool of Krebs cycle intermediates and fuel oxidative phosphorylation. Nearly 50% of observed changes pertained to subunits of the respiratory chain. ATP synthase-&bgr; subunit of complex V was less degraded, and its phosphorylation modulated by CRT was associated with increased formation (2-fold, P=0.004) and specific activity (+20%, P=0.05) of the mature complex. The importance of these modifications was supported by coordinated changes in mitochondrial chaperones and proteases. CRT increased the mitochondrial respiratory control index with tightened coupling when isolated mitochondria were reexposed to substrates for both complex I (glutamate and malate) and complex II (succinate), an effect likely related to ATP synthase subunit modifications and complex quantity and activity. Conclusions—CRT potently affects both the mitochondrial proteome and the performance associated with improved cardiac function.
Jena: Implementing the Semantic Web Recommendations Jena: Implementing the Semantic Web Recommendations

The new Semantic Web recommendations for RDF, RDFS and OWL have, at their heart, the RDF graph. Jena2, a second-generation RDF toolkit, is similarly centered on the RDF graph. RDFS and OWL reasoning are seen as graph-to-graph transforms, producing graphs of virtual triples. Rich APIs are provided. The Model API includes support for other aspects of the RDF recommendations, such as containers and reification. The Ontology API includes support for RDFS and OWL, including advanced OWL Full support. Jena includes the de facto reference RDF/XML parser, and provides RDF/XML output using the full range of the rich RDF/XML grammar. N3 I/O is supported. RDF graphs can be stored in-memory or in databases. Jena's query language, RDQL, and the Web API are both offered for the next round of standardization. ABSTRACT The new Semantic Web recommendations for RDF, RDFS and OWL have, at their heart, the RDF graph. Jena2, a second-generation RDF toolkit, is similarly centered on the RDF graph. RDFS and OWL reasoning are seen as graph-to-graph transforms, producing graphs of virtual triples. Rich APIs are provided. The Model API includes support for other aspects of the RDF recommendations, such as containers and reification. The Ontology API includes support for RDFS and OWL, including advanced OWL Full support. Jena includes the de facto reference RDF/XML parser, and provides RDF/XML output using the full range of the rich RDF/XML grammar. N3 I/O is supported. RDF graphs can be stored in-memory or in databases. Jena's query language, RDQL, and the Web API are both offered for the next round of standardization.