Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Glioma Neovascularization-related Proteins by Using MALDI-FTMS and Nano-LC Fractionation to Microdissected Tumor Vessels*

The identification of angiogenesis-related proteins is important for the development of new antiangiogenic therapies, and such proteins are potential new biomarkers for gliomas. The aim of this study was to identify proteins that are exclusively present in glioma neovasculature and not in the vasculature of normal brain. We combined advanced proteomics techniques to compare the expression profiles of microdissected blood vessels from glioma with blood vessels of normal control brain samples. We measured the enzymatic generated peptide profiles from these microdissected samples by MALDI-FTMS. Subsequently, the samples were fractionated by nano-LC prior to MALDI-TOF/TOF. This combined approach enabled us to identify four proteins that appeared to be exclusively expressed in the glioma blood vessels. Two of these proteins, fibronectin and colligin 2, were validated on tissue sections using specific antibodies. We found that both proteins are present in active angiogenesis in glioma, other neoplasms, and reactive conditions in which neoangiogenesis takes place. This work proves that gel-free mass spectrometric techniques can be used on relatively small numbers of cells generated by microdissection procedures to successfully identify differentially expressed proteins.
Deep , Consistent and also Useful : Extracting Vistas from Deep Corpora for Shallower Tasks

Annotated corpora are fundamental for NLP, and the trend in their development is to move towards datasets with increasingly detailed linguistic annotation. To cope with the complexity of producing such resources, some approaches rely on a supporting deep processing grammar that provides annotation that is rich and consistent over its morphological, syntactic and semantic layers. However, for some purposes, the deep linguistic corpora thus produced are “too deep” and unwieldy. For instance, if one wishes to obtain a probabilistic constituency parser by learning a model over a treebank, the full extent of the annotation created by a deep grammar is not needed and can even be detrimental to training. In this paper, we report on procedures that, starting from a deep dataset produced by a deep processing grammar, extract a variety of vistas—that is, subsets of the information contained in the full dataset. This allows taking a single base dataset as a starting point and, from it, deliver a variety of corpora that are more streamlined and focused on particular tasks.
Speculation, Returns, Volume and Volatility in Commodities Futures Markets

Our study contributes to the literature in two directions. First, we investigate the behaviour of futures prices returns for different energy and agricultural commodities, over the period 1986-2010. Second, we measure the market vulnerability to financial speculation for energy commodities over the period 1992-2010. We find that financial speculation is poorly significant in modelling returns in commodities futures, while macroeconomic and financial factors are relevant. Spillovers between commodities are present and correlations among commodities volatilities are large and time-varying. A higher degree of vulnerability to financial speculation characterizes the futures market for crude oil in the 2008 crisis.
Spectrofluorimetric Determination of Labetalol Hydrochloride in Pharmaceutical Preparations and Urine Samples

Two simple and sensitive spectrofluorimetric methods have been developed for the determination of labetalol (LBT). In method A, the native fluorescence was measured at 432 nm after excitation at 312 nm. The second method (method B) is based on the formation of a ternary complex between zinc (II), eosin and LBT. The fluorescence intensity of the ternary complex was measured at 452 nm after excitation at 317 nm. Optimum conditions for the determination were also investigated. The linear range and detection limit for method A and B were found to be 1.25-30 µg/ml; 0.24 µg/ml and 0.5-4 µg/ml; 0.08 µg/ml, respectively. The proposed methods are simple, practical and relatively free of interference from coexisting substances. The methods have been applied to assess LBT in commercial tablets and human urine samples with good precision and accuracy.
A Sensemaking Approach to Tablet Users' Accommodating Practices

As mobile devices permeate daily life, several studies investigate how users react when technology falls short of their expectations. In this paper, we deploy a data/frame model to examine sensemaking processes through which users approach their interaction with the tablet under conditions of discomfort. We show that users eventually handle such problematic episodes by adopting one of three identified practices: they choose to defer tasks until the situation changes or abandon the platform altogether; they develop workarounds at different levels of mastery; or they proceed by reframing their expectations for the mobile platform. The paper’s contribution is twofold. Investigating user narratives on interaction, our study explicates the sensemaking processes through which users adopt one of the three practices. On a practical level, its results can inform IT artefact and application design by offering insight on how users proceed in bridging the gap between their expectations and the situation at hand.
Interictal Epileptiform Discharges Do Not Change before Seizures during Sleep

Summary: Purpose: Whether interictal epileptiform discharges (IEDs) increase, decrease, or are unchanged before epileptic seizures has implications for the pathophysiology of epilepsy. Prior studies relating IEDs and seizures have not demonstrated a change in IEDs before seizures. However, they have not controlled for changes in the depth of sleep. Our objective was to test the hypothesis that IEDs are related to seizures during sleep while adjusting for log delta power (LDP), a continuous measure of sleep depth.
Optimal frequencies for inductive powering of fully implantable biosensors for chronic and elderly patients

The paper aims at exploring advantages and drawbacks of using high-frequency inductive links to transmit power wirelessly to implanted biosensors. A system with an external transmitting coil located into a skin patch and a receiving coil embedded into a fully implanted biosensor is simulated. The effects of the geometry of the coils on the optimal working frequencies and on the power gain have been analyzed. For applications dedicated to elderly and chronic patients, attention has been posed to the effects on link efficiency of different implantation sites and possible misalignments between the coils.
Empirical mode decomposition based adaboost-backpropagation neural network method for wind speed forecasting

Wind speed forecasting is a popular research direction in renewable energy and computational intelligence. Ensemble forecasting and hybrid forecasting models are widely used in wind speed forecasting. This paper proposes a novel ensemble forecasting model by combining Empirical mode decomposition (EMD), Adaptive boosting (AdaBoost) and Backpropagation Neural Network (BPNN) together. The proposed model is compared with six benchmark models: persistent, AdaBoost with regression tree, BPNN, AdaBoost-BPNN, EMD-BPNN and EMD-AdaBoost with regression tree. The comparisons undergoes several statistical tests and the tests show that the proposed EMD-AdaBoost- BPNN model outperformed the other models significantly. The forecasting error of the proposed model also shows significant randomness.
Erythroid Krüppel-Like Factor Directly Activates the Basic Krüppel-Like Factor Gene in Erythroid Cells

ABSTRACT The Sp/Krüppel-like factor (Sp/Klf) family is comprised of around 25 zinc finger transcription factors that recognize CACCC boxes and GC-rich elements. We have investigated basic Krüppel-like factor (Bklf/Klf3) and show that in erythroid tissues its expression is highly dependent on another family member, erythroid Krüppel-like factor (Eklf/Klf1). We observe that Bklf mRNA is significantly reduced in erythroid tissues from Eklf-null murine embryos. We find that Bklf is driven primarily by two promoters, a ubiquitously active GC-rich upstream promoter, 1a, and an erythroid downstream promoter, 1b. Transcripts from the two promoters encode identical proteins. Interestingly, both the ubiquitous and the erythroid promoter are dependent on Eklf in erythroid cells. Eklf also activates both promoters in transient assays. Experiments utilizing an inducible form of Eklf demonstrate activation of the endogenous Bklf gene in the presence of an inhibitor of protein synthesis. The kinetics of activation are also consistent with Bklf being a direct Eklf target. Chromatin immunoprecipitation assays confirm that Eklf associates with both Bklf promoters. Eklf is typically an activator of transcription, whereas Bklf is noted as a repressor. Our results support the hypothesis that feedback cross-regulation occurs within the Sp/Klf family in vivo.
The VIRTUS Middleware: An XMPP Based Architecture for Secure IoT Communications

Before a wider adoption of the Internet of Things (IoT) vision occurs, many urgent technological and social challenging issues still need to be addressed, including device interoperability, systems autonomy, privacy and security concerns, which could have a significant impact on several aspects of everyday-life or potential end-user. Due to the very large number of technologies normally in place within the IoT paradigm, some type of middleware layer is employed to enforce seamless integration of devices and data within the same information network. Within such middleware, data must be exchanged respecting strict protection constraints. Both the networking and security issues have driven the design and the development of the VIRTUS Middleware, an IoT middleware relying on the open XMPP protocol to provide secure event- driven communications within an IoT scenario. Leveraging the standard security features provided by XMPP, the middleware offers a reliable and secure communication channel for distributed applications, protected with both authentication (through TLS protocol) and encryption (SASL protocol) mechanisms. The proposed architecture provides the possibility to isolate an instance of VIRTUS, allowing the exchange of data only within a private network. This paper presents an overview of VIRTUS, providing an overall platform description and details regarding its security features.
Consensus Organizing: Building Communities of Mutual Self Interest

Introduction Ch 1. Community Organizing: Conflict and Consensus Ch 2. Evolution of Consensus Organizing Ch 3. Issues Analysis Ch 4. Program Design Ch 5. Cultural Competency in Consensus Organizing Ch 6. Consensus Organizing Strategy and Tactics Ch 7. Developing External Relationships Ch 8. Forming Partnerships Ch 9. Building Personal Relationship Ch 10.Building Institutional Relationships Ch 11. Developing Young Organizers Ch 12. Using Consensus Organizing in Other Professions Ch 13. The Future of Consensus Organizing "Answers" to Reflection Questions Epilogue
Robust and Fast Tracking Algorithm in Video Sequences by Adaptive Window sizing Using a Novel Analysis on Spatiotemporal Gradient Powers

Success of a tracking method depends largely on choosing the suitable window size as soon as the target size changes in image sequences. To achieve this goal, we propose a fast tracking algorithm based on adaptively adjusting tracking window. Firstly, tracking window is divided into four edge subwindows, and a background subwindow around it. Then, by calculating the spatiotemporal gradient power ratios of the target in each subwindow, four proper expansion vectors are associated with any tracking window sides such that the occupancy rate of the target in tracking window should be maintained within a specified range. In addition, since temporal changing of target is evaluated in calculating these vectors, we estimate overall target displacement by sum of expansion vectors. Experimental results using various real video sequences show that the proposed algorithm successfully track an unknown textured target in real time, and is robust to dynamic occlusions in complex noisy backgrounds.
Research and Application of Digital Transmission of Unbonded Elastic Wire Resistance Type Sensor

By analyzing different resistance values, this collector of this article collects signal of the Unbonded Elastic Wire Resistance Type Sensor (UEWRTS in brief) acquisition embedded in the dams, reservoirs and other hydraulic buildings, and monitors the facilities in real time view. The position of embedded sensors can be distinguished by setting the address and code. The analog signal is one-on-one converted to digital signals through high-precision analog-to-digital conversion and amplification chips by digitized transducers. The digital signals are transported to the central server, and the deformation of the structure is estimated by original data in the server. Meanwhile, it extended the transformer’s effective measuring distance from normal analog 200 meters up to digitalized 1200 meters. In situation of multi UEWRTS installed field, all the output of the transformers can be connected in parallel to eliminate the cables to only one RS485-Bus as a twisted-pair cable and a power line. Applications of the transducer in several reservoir dams’ security monitoring system proof that is of high accuracy, reliable, strong anti-interference solution for all the UEWRTS applications of the relative monitoring and measurement projects. The collector has been applied in dam monitoring, and achieved good results
Fault Tolerance in Hadoop for Work Migration

Hadoop is a framework that runs applications on large clusters which are built on numerous hardwares. This framework provides applications with the data motion and fault-tolerance transparently. This framework implements the computational paradigm called MapReduce, which splits the application into various tasks that can be executed or re-executed on any node on the cluster. The MapReduce framework and the Hadoop Distributed File System (HDFS) run on same set of nodes and hence provide very high aggregate bandwidth across the cluster. The MapReduce framework and Hadoop Distributed File System are designed in such a way that the framework automatically handles node failures.
VASP Activation via the Gα13/RhoA/PKA Pathway Mediates Cucurbitacin-B-Induced Actin Aggregation and Cofilin-Actin Rod Formation

Cucurbitacin B (CuB), a potent antineoplastic agent of cucurbitacin triterpenoids, induces rapid disruption of actin cytoskeleton and aberrant cell cycle inhibiting carcinogenesis. However, the underlying molecular mechanism of such anticancer effects remains incompletely understood. In this study, we showed that CuB treatment rapidly induced vasodilator-stimulated phosphoprotein (VASP) phosphorylation (i.e. activation) at the Ser157 residue and generated VASP clumps which were co-localized with amorphous actin aggregates prior to the formation of highly-ordered cofilin-actin rods in melanoma cells. Knockdown of VASP or inhibition of VASP activation using PKA-specific inhibitor H89 suppressed CuB-induced VASP activation, actin aggregation and cofilin-actin rod formation. The VASP activation was mediated by cAMP-independent PKA activation as CuB decreased the levels of cAMP while MDL12330A, an inhibitor of adenylyl cyclase, had weak effect on VASP activation. Knockdown of either Gα13 or RhoA not only suppressed VASP activation, but also ameliorated CuB-induced actin aggregation and abrogated cofilin-actin rod formation. Collectively, our studies highlighted that the CuB-induced actin aggregation and cofilin-actin rod formation was mediated via the Gα13/RhoA/PKA/VASP pathway.
Sources of Real and Nominal Exchange Rate Movements for the Euro

We conducted an analysis on the sources of real and nominal exchange rate movements for the Euro, applying the SVAR methods of Enders and Lee (1997). In particular, our analysis focused on the robustness of the results by considering different combinations of data on nominal exchange rates and price indices. Our results showed that the shape of the impulse response function differs substantially depending on the case. In particular, we found that the important issue of whether the real exchange rate and nominal exchange rate overshoot depends on the index selected.
Dimension Hierarchy Aggregate Cube Implementation for Port MOLAP

In order to facilitate the multi-dimension on-line analysis processing (MOLAP) on multi-dimension data warehouse and to support the port management decision, in this paper, we built the port production data cube with the port data, and then we stored the binary coded hierarchical dimension information with the dimension hierarchy storage tree. Based on that, this paper also proposed to create a dimension hierarchy aggregate cube with the dimension hierarchy aggregate technique. The query performance on multi-dimension port production data cube by dimension hierarchy aggregate cube was compared with the dynamic data cube (DDC), which was stored in array. The result shows that the dimension hierarchy aggregate cube can present the dimension hierarchy relation, and it also had a better query performance.
Open Source Intelligence

Open Source Intelligence can be defined as the retrieval, extraction and analysis of information from publicly available sources. Each of these three processes is the subject of ongoing research resulting in specialised techniques. Today the largest source of open source information is the Internet. Most newspapers and news agencies have web sites with live updates on unfolding events, opinions and perspectives on world events. Most governments monitor news reports to feel the pulse of public opinion, and for early warning and current awareness of emerging crises. The phenomenal growth in knowledge, data and opinions published on the Internet requires advanced software tools which allow analysts to cope with the overflow of information. Malicious use of the Internet has also grown rapidly, particularly on-line fraud, illegal content, virtual stalking, and various scams. These are all creating major challenges to security and law enforcement agencies. The alarming increase in the use of the Internet by extremist and terrorist groups has also emerged. The Joint Research Centre has developed significant experience in Internet content monitoring through its work on media monitoring (EMM) for the European Commission. EMM forms the core of the Commission’s daily press monitoring service, and has also been adopted by the European Council Situation Centre for their ODIN system. This paper will review this growing area of research. A new research topic at the JRC is Web mining and open source intelligence. This applies EMM technology to the wider Internet and not just to news sites. A Google search or user selection is used to identify potential web resources and the extraction and download of all the textual content. This is then followed by automatic change detection, the recognition of places, names and relationships, and further analysis of the resultant large bodies of text. These tools help analysts to process large amounts of documents and derive structured data which is easier to analyse.
DISTRIBUTION OF CARBON STORED IN PANTROPICAL FORESTS FROM FUSION OF FIELD INVENTORY AND REMOTE SENSING DATA

S Saatchi (1) , N. L. Harris 2 , S. Brown 2 , S. Hagen 3 , W. Sales, and M. Lefsky 3 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA. Saatchi@jpl.nasa. gov (2) Winrock International, Ecosystem Services Unit, 2121 Crystal Drive Suite 500, Arlington, VA (3) Applied GeoSolutions, LLC, 87 Packers Falls Road, Durham, NH 03824 (4) Warner College of Natural Resources, Colorado State University, Fort Collins, CO
Detecting ultrasonic signals in a turbulent atmosphere: performance of different codes

Signal coding and pulse compression provide ultrasonic systems with the capability to obtain accurate measurements that are nearly independent of the conditions of operation. This property, together with the high robustness to noise also achieved with these techniques, are making possible the development of high reliability systems intended for outdoor operation. However, these systems must face new problems not found indoors, such as the effect of atmospheric turbulence on the shape of the emitted waveforms. This work presents a comparative analysis of the performance of different codes that are used to encode the signals of an ultrasonic sensory system designed to operate under strong turbulence conditions.
Assessing risks of invasion through gamete performance: farm Atlantic salmon sperm and eggs show equivalence in function, fertility, compatibility and competitiveness to wild Atlantic salmon

Adaptations at the gamete level (a) evolve quickly, (b) appear sensitive to inbreeding and outbreeding and (c) have important influences on potential to reproduce. We apply this understanding to problems posed by escaped farm salmon and measure their potential to reproduce in the wild. Farm Atlantic salmon (Salmo salar) are a threat to biodiversity, because they escape in large numbers and can introgress, dilute or disrupt locally adapted wild gene pools. Experiments at the whole fish level have found farm reproductive potential to be significant, but inferior compared to wild adults, especially for males. Here, we assess reproductive performance at the gamete level through detailed in vitro comparisons of the form, function, fertility, compatibility and competitiveness of farm versus wild Atlantic salmon sperm and eggs, in conditions mimicking the natural gametic microenvironment, using fish raised under similar environmental conditions. Despite selective domestication and reduced genetic diversity, we find functional equivalence in all farm fish gamete traits compared with their wild ancestral strain. Our results identify a clear threat of farm salmon reproduction with wild fish and therefore encourage further consideration of using triploid farm strains with optimized traits for aquaculture and fish welfare, as triploid fish remain reproductively sterile following escape.
Auditing the Organizational Knowledge through a Balanced Scorecard-based Approach ”

A better performing Knowledge Management Systems (KMSs) are even more required today from all organizations. However, no specific strategy seems to be widely consolidated for supporting the assessment process of organizational knowledge; and what specifically appears to be needed is a strategy for individuating more precisely which specific functions must be proficiently performed by a KMS to improve the organizations’ knowledge-management capability. This paper proposes an innovative Knowledge Audit Approach (KAA) which has been particularly developed basing on two main fundamentals: first, the Balanced Scorecard classification scheme of the business objectives and goals; and second, an Intellectual Capital (IC) representation model. Further, here are presented some results obtained by empirically applying the KAA within a public administration body in Southern Italy where a number of e-government best practices were recently carried out.