Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery and Verification of Head-and-neck Cancer Biomarkers by Differential Protein Expression Analysis Using iTRAQ Labeling, Multidimensional Liquid Chromatography, and Tandem Mass Spectrometry*S

Multidimensional LC-MS/MS has been used for the analysis of biological samples labeled with isobaric mass tags for relative and absolute quantitation (iTRAQ) to identify proteins that are differentially expressed in human head-and-neck squamous cell carcinomas (HNSCCs) in relation to non-cancerous head-and-neck tissues (controls) for cancer biomarker discovery. Fifteen individual samples (cancer and non-cancerous tissues) were compared against a pooled non-cancerous control (prepared by pooling equal amounts of proteins from six non-cancerous tissues) in five sets by on-line and off-line separation. We identified 811 non-redundant proteins in HNSCCs, including structural proteins, signaling components, enzymes, receptors, transcription factors, and chaperones. A panel of proteins showing consistent differential expression in HNSCC relative to the non-cancerous controls was discovered. Some of the proteins include stratifin (14-3-3σ); YWHAZ (14-3-3ζ); three calcium-binding proteins of the S100 family, S100-A2, S100-A7 (psoriasin), and S100-A11 (calgizarrin); prothymosin α (PTHA); l-lactate dehydrogenase A chain; glutathione S-transferase Pi; APC-binding protein EB1; and fascin. Peroxiredoxin2, carbonic anhydrase I, flavin reductase, histone H3, and polybromo-1D (BAF180) were underexpressed in HNSCCs. A panel of the three best performing biomarkers, YWHAZ, stratifin, and S100-A7, achieved a sensitivity of 0.92 and a specificity of 0.91 in discriminating cancerous from non-cancerous head-and-neck tissues. Verification of differential expression of YWHAZ, stratifin, and S100-A7 proteins in clinical samples of HNSCCs and paired and non-paired non-cancerous tissues by immunohistochemistry, immunoblotting, and RT-PCR confirmed their overexpression in head-and-neck cancer. Verification of YWHAZ, stratifin, and S100-A7 in an independent set of HNSCCs achieved a sensitivity of 0.92 and a specificity of 0.87 in discriminating cancerous from non-cancerous head-and-neck tissues, thereby confirming their overexpressions and utility as credible cancer biomarkers.
SOME NOTIONS. AND METHODS ON THE BORDERLINE OF ALGEBRA AND METAMATHEMATICS

The content of this paper is an outline of the general theory of arithmetical classes and a discussion of some of its applications. Roughly speaking, an arithmetical class is any set of algebraic systems whose definition involves no set-theoretical terms; thus, e.g., the set of all groups and that of all lattices are arithmetical classes, while the set of all simple groups and that of all denumerable lattices are not. The tendency to distinguish between those constructions and derivations which involve set-theoretical notions from those which do not involve them is undoubtedly a pronounced trend of modern algebraic research. The theory of arithmetical classes provides this trend with a theoretical framework and exhibits its reach and limitations. The fact that we shall concern ourselves with those algebraic notions which involve no set-theoretical elements by no means implies that we shall avoid set-theoretical apparatus in studying these notions. On the contrary, it will be seen that set-theoretical constructions and methods play an essential part in the development of the general theory of arithmetical classes. The notion of an arithmetical class is of a metamathematical origin ; whether or not a set of algebraic systems is an arithmetical class depends upon the form in which its definition can be expressed. However, it has proved to be possible to characterize this notion in purely mathematical terms and to discuss it by means of normal mathematical methods. The theory of arithmetical classes has thus become a mathematical theory in the usual sense of this term, and in fact it can be regarded as a chapter of universal algebra. The theory concerns arbitrary algebraic systems formed by a nonempty set A, some operations O0, Oi, • • • under which A is closed, some relations Ä 0 , Ri, • • • between elements of A, and possibly some distinguished elements Co, Ci, • • • of A. In the present paper we are interested exclusively in systems with finitely many operations, relations, and distinguished elements (though the set A of all elements of the system may be infinite) ; this restriction, however, is not essential for the major part of our discussion. To simplify the discussion, we formulate definitions and theorems exclusively for systems SI = <A, +>
Wide-Band Collaborative Spectrum Search Strategy for Cognitive Radio Networks

We consider a scenario where n collaborating cognitive radios (CRs) try to jointly detect spectrum opportunities in a wide-band spectrum within a predefined spectrum sensing interval TS. We assume that each CR is equipped with a tunable bandpass filter (BPF) and is able to sense one frequency band (channel) at a time. The sensing interval consists of L sensing slots of length T . During each sensing slot, each of the collaborating CRs is assigned to sense one of the channels and report its observation to the other CRs. The occupancy of each channels is decided after L sensing slots based on a fusion rule that is fitted to a regulatory constraint or a coarse sensing task. We aim to maximize the expected number of identified idle channels by optimally choosing the index of the channel to be sensed by each collaborating CR at each sensing slot. We model this problem in its most general form as a finite horizon Markov decision process. We derive closed-form solutions for an optimal spectrum sensing policy and the associated value functions for the case of two collaborating CRs where individual sensing decisions are fused together according to the OR-rule. We show that the gain due to the optimal sensing policy is more significant when the spectrum utilization is high.
Spectral Analysis for Neural Signals

Introduction This chapter introduces concepts fundamental to spectral analysis and applies spectral analysis to characterize neural signals. Spectral analysis is a form of time series analysis and concerns a series of events or measurements that are ordered in time. The goal of such an analysis is to quantitatively characterize the relationships between events and measurements in a time series. This quantitative characterization is needed to derive statistical tests that determine how time series differ from one another and how they are related to one another. Time series analysis comprises two main branches: time-domain methods and frequency-domain methods. Spectral analysis is a frequency-domain method for which we will use In this chapter, we will focus on relationships within and between one and two time series, known as univariate and bivariate time series. Throughout this discussion, we will illustrate the concepts with experimental recordings of spiking activity and local field potential (LFP) activity. The chapter on Multivariate Neural Data Sets will extend the treatment to consider several simultaneously acquired time series that form a multivariate time series, such as in imaging experiments. The chapter on " Application of Spectral Methods to Representative Data Sets in Electrophysiology and Functional Neuro-imaging " will review some of this material and present additional examples. First we begin by motivating a particular problem in neural signal analysis that frames the examples in this chapter. Second, we introduce signal processing and the Fourier transform and discuss practical issues related to signal sampling and the problem of alias-ing. Third, we present stochastic processes and their characterization through the method of moments. The moments of a stochastic process can be characterized in both the time domains and frequency domains, and we will discuss the relation between these characterizations. Subsequently, we present the problem of scientific inference, or hypothesis testing , in spectral analysis through the consideration of error bars. We finish by considering an application of spectral analysis involving regression.
A Multi-Cancer Mesenchymal Transition Gene Expression Signature Is Associated with Prolonged Time to Recurrence in Glioblastoma

A stage-associated gene expression signature of coordinately expressed genes, including the transcription factor Slug (SNAI2) and other epithelial-mesenchymal transition (EMT) markers has been found present in samples from publicly available gene expression datasets in multiple cancer types, including nonepithelial cancers. The expression levels of the co-expressed genes vary in a continuous and coordinate manner across the samples, ranging from absence of expression to strong co-expression of all genes. These data suggest that tumor cells may pass through an EMT-like process of mesenchymal transition to varying degrees. Here we show that, in glioblastoma multiforme (GBM), this signature is associated with time to recurrence following initial treatment. By analyzing data from The Cancer Genome Atlas (TCGA), we found that GBM patients who responded to therapy and had long time to recurrence had low levels of the signature in their tumor samples (P = 3×10−7). We also found that the signature is strongly correlated in gliomas with the putative stem cell marker CD44, and is highly enriched among the differentially expressed genes in glioblastomas vs. lower grade gliomas. Our results suggest that long delay before tumor recurrence is associated with absence of the mesenchymal transition signature, raising the possibility that inhibiting this transition might improve the durability of therapy in glioma patients.
Hybrid Neural Networks to recognize BodyPostures in Human-Computer

In this paper a novel approach to human posture analysis and recognition using standard image processing techniques as well as hybrid neural information processing is presented. We rst develop a reliable and robust person localization module via a combination of certain salient cues and three-dimensional dynamic neural elds. Then we focus on the view-based recognition of the user's static gestural instructions from a predeened vocabulary based on both a skin color model and statistical normalized moment invariants. The segmentation of the postures occurs by means of the skin color model based on the Mahalanobis metric. From the resulting binary image containing only regions which have been classiied as skin candidates we extract translation and scale invariant moments. These are used as input for two diierent neural classiiers whose results are then compared. To train and test the neural classiiers we gathered the data from ve people performing 18 repetitions of each of ve postures (our vocabulary): stop, go left, go right, hello left and hello right. The system is currently under development with constant updates and new developments. It uses input from a color video camera and is user-independent. The aim is to build a real-time system able to deal with dynamic gestures.
Aspects of a trigger subsystem in an integrated database system

This paper considers the specifications and design of a trigger subsystem in a database management system. The use of triggers as extended assertions and as a means to materialize virtual data objects are discussed. The functional requirements of a trigger subsystem and different implementation issues are studied. We also examine the relationships between a trigger subsystem and the rest of the database system, in particular the authorization and locking subsystems.
Creating Band-Notched Characteristics for Compact UWB Monopole Antennas

In 2002, the FCC in the US authorized the unlicensed use of the ultrawideband (UWB) frequency spectrum for commercial applications in the range from 3.1 to 10.6 GHz with an emission limit of -41.3 dBm/MHz which is near to the thermal noise floor [1]. UWB communication systems operating in such a wide frequency band and low power emission level could easily be interfered by the existing nearby communication systems such as the Wireless Local Area Networks (WLANs) operating in the frequency bands of 2.45-GHz (2.4– 2.484 GHz), 5.25-GHz (5.15–5.35 GHz) and 5.75-GHz (5.725–5.825 GHz) [2] and the Worldwide Interoperability for Microwave Access (WiMAX) systems operating in the 2.35GHz (2.3-2.4 GHz), 2.6-GHz (2.5–2.69 GHz), 3.35-GHz (3.3-3.4 GHz), 3.5-GHz (3.4–3.6 GHz), 3.7-GHz (3.6-3.8 GHz) and 5.8-GHz (5.725–5.85 GHz) bands[3]. Many countries such as the UK, Canada, France, Germany, Argentina and India etc. will allow at least four of these bands in operations [3]. In such cases, the UWB systems could be affected by several interference signals. These interference signal could be suppressed by using RF filtering.
Violent Crime and Immigrant Revitalization and Influx in the South: Contending with a Southern Culture of Violence and Exclusion

Immigrant revitalization has been used to understand the crime reducing benefits of immigrant concentration. Recently, the South, a region described as a one with a distinct appetite for violence and the most violent region in America, has seen dramatic increases in the concentration of immigrants. The Southern Culture of Violence (SCV) Thesis has been used as an explanation for this distinctness. Using negative binomial regression with 1990 and 2000 data from the National Neighborhood Crime Study (NNCS) supplemented with Census data, I examine the impact of immigrant concentration, the change in these concentration levels, and the lagged impact of the former on violent crime rates in the South compared to regions outside of the South. I also examine the effects of immigrant concentration in areas that have had low, average, and high levels of immigration in 1990. I find that immigration has negative effects on violent crime that vary in degree based on the region. I also find some evidence for a lagged effect and stronger effects when focusing on communities with higher levels of immigrant concentration, especially in the South. I discuss how the effect of revitalization may be weakened due to the SCV and the level of receptiveness of immigrants along with other mediating factors. I conclude by suggesting that future studies that more directly examine immigrant feelings of reception, opportunity, and ultimately the cultural conditions in specific regions along with additional studies that more deeply investigates the intersecting roles of immigration, race, crime, and inclusion.
Neurotrophin-3 Is a Survival Factor In Vivo for Early Mouse Trigeminal Neurons

Mice lacking neurotrophin-3 (NT-3) have been shown previously to be born with severe sensory deficits. This study characterizes the developmental course of this deficit in the trigeminal sensory ganglion, which in NT-3 homozygous mutants contains only 35% of the normal number of neurons at birth. At embryonic day 10.5 (E10.5), normal numbers of neurons, as assessed by expression of neurofilament protein and of total cells, are present in the ganglia of mutant homozygotes. During the next 3 d (E10.5–E13.5), virtually all of the deficit develops, after which mutant animals retain only ∼30% the normal number of neurons. Quantification of neuronal and neuronal precursor numbers in normal and mutant animals reveals that neurons are specifically depleted in the absence of NT-3. A deficiency in precursor proliferation is only seen after most of the neuronal deficit has developed. Numbers of apoptotic cells in the ganglia of mutant animals are elevated during this same interval, indicating that the neuronal deficit is caused, in large part, by increased cell death of embryonic neurons. To determine sources of NT-3 in the trigeminal system, we examined the expression pattern of β-galactosidase in mice, in which lacZ has replaced the NT-3 coding exon. E10.5–E11.5 embryos exhibit intense reporter expression throughout the mesenchyme and epithelia of the first branchial arch. β-galactosidase expression in E13.5 embryos is largely confined to the oral epithelium and the mesenchyme underlying the skin. Throughout the E10.5–E13.5 interval, the trigeminal ganglion and its targets in the CNS do not express reporter activity. We conclude that NT-3 acts principally as a peripherally derived survival factor for early trigeminal neurons.
Twitter Trends Detection by Identifying Grammatical Relations

The problem considered in this paper relates to identification of trends in a given area based on analysis of Twitter messages. The approaches currently used for Twitter trends detection are based on n-grams. We propose another approach of trend detection based on identifying trend as grammatical relation and perform the identification of trending relations on the basis of their frequency change dynamics. This paper describes our method, which evaluates grammatical relations in a flow of messages on a particular subject taking into consideration both their frequency and semantic similarity among the pairs of relations. We conducted experiments to compare the outcomes provided by our method with the trends detected by conventional Twitter algorithms. The results confirmed the effectiveness of our method. The trends identified from the application of our method are easier for human interpretation.
Sigma-point Unscented Kalman Filter used for AUV navigation

This paper presents an implementation of the Sigma-point Unscented Kalman Filter (SP-UKF) used in the simulated task of open-water navigation of two types of AUV. The first simulated vehicle is a large cruise-type vehicle modeled after the Instituto Superior Tecnico, Lisbon vehicle Infante. The second is a small, almost fully actuated vehicle with tunnel thrusters modeled after the SSC Pacific, San Diego vehicle CETUS II. The SP-UKF shows itself, after properly taking care of implementation details, to be a robust methodology which allows for efficient and correct navigation, aided by several typical sensors (DVL, USBL hydroacoustic localization systems, AHRS). The influence of currents on the navigation, and the ability of estimating the current components is also researched. The navigation fix is fed back to the low-level control loops aboard each vehicles to achieve sane and rational navigation of the waterspace that follows stably and robustly the command signals.
Sucrose load, calcium-deficiency and dental caries on molars of growing rats

The effects of dietary sucrose feeding, intragastric sucrose feeding and dietary calcium-deficiency on primary dentinogenesis of the pulp-dentin organ and caries progression were examined in an experimental rat model. The possible role of calcium balance and reduced mineralization of dentin organic matrix as a cause of reduced dentin formation in young, fast growing, rats were also studied. During 3-6 weeks of feeding, immediately after weaning at 3 weeks the urinary calcium, phosphorus, potassium and sodium levels and excretion rates were determined. The areas of dentin formed, the width of the predentin layer, serum mineral and insulin levels, and the areas of dentinal caries lesions were quantified at the end of the experiment. Also the occurrence and progression level of caries lesions were measured. In rat pups, dietary sucrose reduced dentin formation both during the lactation and experimental periods, increased urinary Ca2+ excretions, reduced urinary P, K and Na excretions, and enhanced dental caries occurrence and progression, but it did not affect the width of the predentin layer or the serum mineral and insulin levels. Intragastric sucrose reduced dentin formation and increased Ca2+ excretion, but did not affect the width of the predentin layer, serum mineral and insulin levels in the blood or induce dental caries. Dietary calcium-deficiency reduced dentin formation, increased the width of the predentin layer, caused hypocalcemia, and reduced urinary Ca2+ excretion. These results show that sucrose and calcium-deficiency reduce the rate of primary dentinogenesis through different mechanisms. Calcium imbalance or reduced mineralization of the dentin organic matrix does not explain the reduced dentinogenesis in sucrose fed rats. In conclusion, the present findings indicate that a sucrose load reduces dentinogenesis by impairing the synthesis rate of the dentin organic matrix, but also points out the importance of the local sucrose challenge in initiating dental caries.
Low-Power Security Modules Optimized for WSNs

A crucial factor in numerous Wireless Sensor Networks (WSNs) is the security they provide. A promising approach for providing high-levels of security at a low energy cost is the low-power reconfigurable Complex Programmable Logic Devices (CPLDs). This paper presents a pioneering WSN platform which embeds a CPLD in a standard WSN node. This platform, as our realworld experiments demonstrate, accelerates one of the most widely used authentication algorithms by more than 3000 times. Moreover, the proposed system can accelerate by three orders of magnitude the header checksum calculation scheme that needs high processing power. At the same time the overall energy consumption of the new node is reduced up to to 98%, when compared with the consumption of a standard CPU-based WSN node executing those security algorithms in software.
An improved method for the computation of PageRank

The dramatic growth of the web information technology is forcing modern web search engines to look beyond simply the content of pages in providing relevant answers to queries. This paper has a brief description of the original PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by utilizing the link structure of the web. Besides, it gives some analysis of topic bias, absolute equalization and emphasis on old web about the algorithm, which influences the ranking quality of websites. In order to solve these problems, we propose an improved method for the computation of PageRank on the basis of integrated factors. The experiment shows that our improved method outperforms the PageRank algorithm in the quality of the pages returned.
A CNL for requirements as the basis to automate tasks of critical system development

Requirements play a key role in the airborne software development process. They serve as basis for verification and validation (V&V) during the system development. Requirements are in general specified in natural language. In this way, they are prone to misinterpretations and they have limited capacity of automatic processing, which in turn result in additional effort during system development. We propose a Controlled Natural Language (CNL) for specifying system requirements. The CNL specification is a formal representation of the requirements and it is used in an approach to automatically generate both system models and test cases. System models are used to verify the specified behavior of the system, and test cases are used to verify the system's functionality. We developed prototypes to automate the generation of both model and test cases, based on requirements defined in the CNL. A fly-by-wire system is used in the examples of our approach. The initial results show gains of effort.
Generating Workflow Models from OWL-S Service Descriptions with a Partial-Order Plan Construction

In this work we construct partial order plans from a pool of atomic services described in OWL-S. We make extensions to Partial Order Planning to allow multiple conditional effects in action definitions. The purpose is to handle the uncertain behavior of Web services with incomplete initial information. We post-process the partial order plan to auto-generate a workflow model. We developed a method to identify a subset of workflow patterns from the solution plan to create a workflow diagram.