Miracle-dz/UniFAR-FTUs huggingface dataset:
Change in Growth Differentiation Factor 15, but Not C-Reactive Protein, Independently Predicts Major Cardiac Events in Patients with Non-ST Elevation Acute Coronary Syndrome

Among the numerous emerging biomarkers, high-sensitivity C-reactive protein (hsCRP) and growth-differentiation factor-15 (GDF-15) have received widespread interest, with their potential role as predictors of cardiovascular risk. The concentrations of inflammatory biomarkers, however, are influenced, among others, by physiological variations, which are the natural, within-individual variation occurring over time. The aims of our study are: (a) to describe the changes in hsCRP and GDF-15 levels over a period of time and after an episode of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and (b) to examine whether the rate of change in hsCRP and GDF-15 after the acute event is associated with long-term major cardiovascular adverse events (MACE). Two hundred and Fifty five NSTE-ACS patients were included in the study. We measured hsCRP and GDF-15 concentrations, at admission and again 36 months after admission (end of the follow-up period). The present study shows that the change of hsCRP levels, measured after 36 months, does not predict MACE in NSTEACS-patients. However, the level of GDF-15 measured, after 36 months, was a stronger predictor of MACE, in comparison to the acute unstable phase.
Liquidity, Liquidity Commonality and its Impact on Portfolio Theory

We measure liquidity as a functional of supply and demand schedules, and measure commonality in liquidity as functional covariance. We show that liquidity commonality is due to supply and demand co-movements, through which order types play an important role; order types include market and limit orders. Contrarily, return commonality is mainly caused by order-flow co-movement; order flows include order directions and sizes. Since return commonality and liquidity commonality are caused by different forces, it is possible for stocks to have negative or little correlations in returns but strong positive correlations in liquidity. Both simulation results and empirical evidence from the Australian Stock Exchange support the above statement. Therefore, liquidity commonality poses a problem to diversification strategies based solely on picking stocks that do not correlate in returns. It is in this sense that not only the first moment of liquidity matters to asset pricing, its second moment matters as well.
Artificial-noise-aided secure multi-antenna transmission in slow fading channels with limited feedback

We study secure multi-antenna transmission with limited feedback from the intended receiver and no feedback from the malicious eavesdropper. Our system uses the artificial-noise-aided beamforming approach to enhance secrecy, considering slow fading channels with outage constraints on the reliability performance of legitimate communication and the secrecy performance against eavesdropping. Our analytical results provide conditions on the minimum number of feedback bits and the minimum strength of the intended channel for making secure transmission possible. We observe that strengthening the secrecy outage constraint puts higher requirements on the number of feedback bits and the strength of the intended channel. To maximize the achievable secrecy rate, the optimal transmit power allocation between the information signal and the artificial noise is also derived in closed form.
Causal Multi Quantile Noise Spectrum Estimation for Speech Enhancement

Suppression of additive noise from speech signal is a fundamental problem in audio signal processing. We present in this paper a novel algorithm for single channel speech enhancement. The algorithm consists of two steps: First, estimation of the noise power spectrum with a multi quantile method and second, elimination of the estimated noise from the observed signal by spectral subtraction or Wiener filtering. In this method, instead of a global quantile for all frequency bands, we divide the entire frequency band into three regions and use different quantile in each region. Our simulation results show that the new method has better performance than quantile based noise estimation.
An index-based management scheme with adaptive caching for huge-scale low-cost embedded flash storages

Due to its remarkable access performance, shock resistance, and costs, NAND flash memory is now widely adopted in a variety of computing environments, especially in mobile devices such as smart phones, media players and electronic book readers. For the consideration of costs, low-cost embedded flash storages such as flash memory cards are often employed on such devices. Different from solid-state disks, the RAM buffer equipped on low-cost embedded flash storages are very small, for example, limited under several dozens of kilobytes, despite of the rapidly growing capacity of the storages. The significance of effectively utilizing the very limited on-device RAM buffers of embedded flash storages is therefore highlighted, and a novel design of scalable flash management schemes is needed to tackle the new access constraints of MLC NAND flash memory. In this work, a highly scalable design of the flash translation layer is presented with the considerations of the on-device RAM size, user access patterns, address-mapping-information caching and MLC access constraints. Through a series of experiments, it is verified that, with appropriate settings of cache sizes, the proposed management scheme provides comparable performance results to prior arts with much lower requirements on the on-device RAM. In other words, the proposed scheme suggests a strategy to make better use of the on-device RAM, and is suitable for embedded flash storages.
Computing Near-Optimal Array Cable Layouts for Offshore Wind Farms, including Cable Choice

To harvest the generated power, the turbines of an offshore wind farm are connected to an electrical transformer by cable routes. Typical cable layouts use two cable types distinguished by price and capacity: High capacity is expensive. This work presents a heuristic for computing near-optimal layouts based on the Clarke and Wright savings heuristic for vehicle routing, and the layouts it computes for two real-life offshore wind farms. The computed layouts are 6% more expensive than the optimal layouts, and on average 5% cheaper than the actually installed layouts.
Multiple TreeBanks Integration for Chinese Phrase Structure Grammar Parsing Using Bagging

We describe our method of traditional Phrase Structure Grammar (PSG) parsing in CIPS-Bakeoff2012 Task3. First, bagging is proposed to enhance the baseline performance of PSG parsing. Then we suggest exploiting another TreeBank (CTB7.0) to improve the performance further. Experimental results on the development data set demonstrate that bagging can boost the baseline F1 score from 81.33% to 84.41%. After exploiting the data of CTB7.0, the F1 score reaches 85.03%. Our final results on the official test data set show that the baseline closed system using bagging gets the F1 score of 80.17%. It outperforms the best closed system by nearly 4% which uses a single model. After exploiting the CTB7.0 data, the F1 score reaches 81.16%, demonstrating further increases of about 1%.
Acoustic Model and Language Model Adaptation for a Mobile Dictation Service Acoustic Model and Language Model Adaptation for a Mobile Dictation Service

Automatic speech recognition is the machine-based method of converting speech to text. MobiDic is a mobile dictation service which uses a server-side speech recognition system to convert speech recorded on a mobile phone to readable and editable text notes. In this work, performance of the TKK speech recognition system has been evaluated on law-related speech recorded on a mobile phone with the Mobi-Dic client application. There was mismatch betweeen testing and training data in terms of both of acoustics and language. The background acoustic models were trained on speech recorded on PC microphones. The background language models were trained on texts from journals and news wire services. Because of the special nature of the testing data, main focus has been on using acoustic model and language model adaptation methods to enhance speech recognition performance. Acoustic model adaptation gives the highest and most reliable performance increase. Using the global cMLLR method, word error rate reductions between 15-22% can be reached with only 2 minutes of adaptation data. Regression class cMLLR can give even higher performance boosts if larger sets of audio adaptation data (> 10 min) are available. Language model adaptation was not able to significantly improve performance in this task. The main problems were differences between language adaptation data and language of the law-related speech data.
Automated Testing of Distributed Systems

We present a technique to test servers that interact with clients using the Sun RPC protocol. The technique requires the user to provide two things: a list of RPC calls for the server being tested, and a set of invariants that are required to hold over the RPC communications trace between a set of clients and the server. The technique works by generating random sequences of RPC calls and checking that the invariants holds over the traces. If an invariant is violated, the violating sequence of RPC calls is reported to the user. We report the results of our testing a block server and a lock server.
Repeat reports to the police of missing people: locations and characteristics

The current study focuses on the locations from which people are reported missing repeatedly in a one year period. Some of these locations are individual households but the majority are organisational facilities. Thus, our aim is to highlight issues surrounding the ‘duty of care’ and ‘safeguarding’ responsibilities of agencies in relation to people who go missing from organisational addresses (such as mental health establishments and children’s care homes); specifically in relation to preventing them from going missing in the first place and the responsibility of the organisations helping to locate them.
BIOSARP: biological inspired self-organized secure autonomous routing protocol for wireless sensor network

In multihop wireless sensor networks users or nodes are constantly entering and leaving the network. Classical techniques for network management and control are not conceived to efficiently face such challenges. New mechanisms are required, to work in a self-organized manner. The techniques found in nature promises WSN, to self-adapt the environmental changes and also self-protect itself from the malicious stuff. This paper introduces a biological inspired self-organized secure autonomous routing protocol (BIOSARP). Our proposed protocol is based on ANT Colony System (ACS) for an optimal route decision. The self-optimized routing protocol is further enhanced with artificial Immune System (HIS) inspired autonomous security mechanism. It enhances WSN in securing itself from the abnormalities and most common WSN routing attacks. NS2 based simulation analysis and results of BIOSARP are presented. The comparison of our autonomous protocol with the most recent WSN security mechanisms is further exhibited, in terms of processing time, delivery ratio and energy consumption.
Shotgun identification of protein modifications from protein complexes and lens tissue

Large-scale genomics has enabled proteomics by creating sequence infrastructures that can be used with mass spectrometry data to identify proteins. Although protein sequences can be deduced from nucleotide sequences, posttranslational modifications to proteins, in general, cannot. We describe a process for the analysis of posttranslational modifications that is simple, robust, general, and can be applied to complicated protein mixtures. A protein or protein mixture is digested by using three different enzymes: one that cleaves in a site-specific manner and two others that cleave nonspecifically. The mixture of peptides is separated by multidimensional liquid chromatography and analyzed by a tandem mass spectrometer. This approach has been applied to modification analyses of proteins in a simple protein mixture, Cdc2p protein complexes isolated through the use of an affinity tag, and lens tissue from a patient with congenital cataracts. Phosphorylation sites have been detected with known stoichiometry of as low as 10%. Eighteen sites of four different types of modification have been detected on three of the five proteins in a simple mixture, three of which were previously unreported. Three proteins from Cdc2p isolated complexes yielded eight sites containing three different types of modifications. In the lens tissue, 270 proteins were identified, and 11 different crystallins were found to contain a total of 73 sites of modification. Modifications identified in the crystallin proteins included Ser, Thr, and Tyr phosphorylation, Arg and Lys methylation, Lys acetylation, and Met, Tyr, and Trp oxidations. The method presented will be useful in discovering co- and posttranslational modifications of proteins.
A ME Model Based on Feature Template for Chinese Text Categorization

With entering into information society and the Internet developing rapidly, people could acquire more and more information. How to utilize Internet information efficiently and promptly, has became a hotspot in information technology. Text categorization is an important component to help getting useful message from tremendous amount of vast information. And it assigns new documents to pre-defined categories automatically based on their content. In this paper, we puts forward propose an improving approach to apply ME model to Chinese text categorization, and its main points include constituting feature functions and pre-disposing documents. In order to make the feature items more reasonable, each document is undergone four steps, namely removing html tags, word segmentation, filtering empty words and removing stop words. In addition, feature-template is brought forward, which is combined with feature item’s weight while constituting feature function. The results of experiments show that the performance with ME model based upon the combination of feature-template and weight outperforms that with ME model based upon word -frequency, and both of their performance is better than that of Naïve Bayes and KNN. Key Wor ds: ME model, Feature Template, Chinese Text Categorization
Metformin and salinomycin as the best combination for the eradication of NSCLC monolayer cells and their alveospheres (cancer stem cells) irrespective of EGFR, KRAS, EML4/ALK and LKB1 status

The presence of cancer stem cells (CSCs) is linked to preexisting or acquired drug resistance and tumor relapse. Therefore, targeting both differentiated tumor cells and CSCs was suggested as an effective approach for non-small cell lung cancer (NSCLC) treatment. After screening of chemotherapeutic agents, tyrosine kinase inhibitors (TKIs) or monoclonal antibody in combination with the putative stem cell killer Salinomycin (SAL), we found Metformin (METF), which modestly exerted a growth inhibitory effect on monolayer cells and alveospheres/CSCs of 5 NSCLC cell lines regardless of their EGFR, KRAS, EML4/ALK and LKB1 status, interacted synergistically with SAL to effectively promote cell death. Inhibition of EGFR (AKT, ERK1/2) and mTOR (p70 s6k) signaling with the combination of METF and SAL can be augmented beyond that achieved using each agent individually. Phospho-kinase assay further suggested the multiple roles of this combination in reducing oncogenic effects of modules, such as ß-catenin, Src family kinases (Src, Lyn, Yes), Chk-2 and FAK. Remarkably, significant reduction of sphere formation was seen under combinatorial treatment in all investigated NSCLC cell lines. In conclusion, METF in combination with SAL could be a promising treatment option for patients with advanced NSCLC irrespective of their EGFR, KRAS, EML4/ALK and LKB1 status.
Geometry Textures and Applications †

Geometry textures are a novel geometric representation for surfaces based on height maps. The visualization is done through a graphics processing unit (GPU) ray casting algorithm applied to the whole object. At rendering time, the fine‐scale details (mesostructures) are reconstructed preserving original quality. Visualizing surfaces with geometry textures allows a natural level‐of‐detail (LOD) behaviour. There are numerous applications that can benefit from the use of geometry textures. In this paper, besides a mesostructure visualization survey, we present geometry textures with three possible applications: rendering of solid models, geological surfaces visualization and surface smoothing.
Analyzing campus traffic using the meter-MIB

-- The University of Twente, which is the only campus university in the Netherlands, connects all students living on the campus via 100 Mbit/s switched Ethernet links to the campus network. This student network not only interconnects all students among themselves, but also provides, via a 300 Mbit/s link, access to other parts of the university network as well as the external Internet. Since the 300 Mbit/s link is a potential bottleneck, the university has defined a policy to limit the total amount of traffic a single student is allowed to exchange to 50 Gigabyte per week. To check if students do not exceed this limit, a number of interface MIB variables within the student’s access switches are monitored on a periodic base. Although monitoring these MIB variables is good enough to detect which students exchange more than 50 Gigabyte weekly, the approach fails to reliably determine which students are the top users of the potential bottleneck, which is the 300 Mbit/s link. The question has therefore been raised whether it would be feasible to directly measure all traffic on that link to precisely determine which student is using which portion of the link’s capacity and for what purpose (downloading information from the teaching departments, browsing the Internet etc.). Although NeTraMet, which is an implementation of the IETF’s meter MIB, would in theory be useable for such measurements, it was not clear whether it would be fast enough to analyse each packet on a 300 Mbit/s full-duplex link. This paper therefore discusses the experiments that have been performed to find the limits of Netramet, and investigate whether the tool would be useful to solve real management problems. In our experiments Netramet was running on a standard PC.
Feedback from the First Supernovae in Protogalaxies: The Fate of the Generated Metals

We investigate the chemodynamic effects of multiple supernova (SN) explosions in the central region of primordial galaxies (e.g., M ~ 108 M☉ halo at z ~ 10) using three-dimensional hydrodynamic simulations of the inhomogenous interstellar medium down to parsec scales. We find that the final protogalactic structure and metal distribution depend strongly on the number of SNe. Specifically, 1000 SNe after an instantaneous burst of star formation are sufficient to almost completely blow away the gas in these systems, whereas 100 SN explosions trigger the collapse of the protogalactic cloud, leading to the formation of a cold, dense clumpy disk (n > 300 cm-3) with metallicity Z = 4 × 10-4 Z☉. These results imply that the metallicity of the "second generation" of stars could be Z ~ 10-4 Z☉, and that the environment to form metal-free stars in protogalaxies may be lost relatively quickly (≲107 yr) after the first burst of Z = 0 star formation. The recently discovered ultra-metal-poor star (Christlieb et al.) may represent surviving members of such second-generation star formation.
Frequent and non-frequent pattern detection in big data streams: An experimental simulation in 1 trillion data points

Big data streaming analysis nowadays has become one of the most important topic in the list of data analysts since enormous amount of data are produced daily by the numerous smart devices. The analysis of such data is very important and the detection of frequent or even non-frequent patterns can be critical for many aspects of our lives. In the current paper, we propose a new methodology based on our previous work regarding the detection of all repeated patterns in a string in order to analyze a very big data stream with 1 Trillion digits, composed from 1 thousand subsequences of 1 billion digits each one. More specifically, using the novel data structure, LERP Reduced Suffix Array, and the innovative ARPaD algorithm which allows the detection of all repeated patterns in a string we managed to analyze each one of the 1 billion data points, using 10 computers with standard hardware configuration, in 33 minutes which outperforms to the best of our knowledge any other existing methodology, which is equivalent to data point generation every 2 microseconds.
A recurrent neural network that produces EMG from rhythmic dynamics

from a macaque during free viewing of natural images. To measure the neurons’ tuning to features of the stimulus in this context, we used Gabor-filter ‘energy’ models, modified such that the degree of stimulus tuning (‘response gain’) was a function of time since fixation onset. We also fit similar models to the LFP power in different frequency bands to describe the stimulus-evoked network activity. We found that, in addition to evoking a large, transient response in the spiking activity and LFP, saccades entrained ~10 Hz alpha oscillations in the LFP that persisted throughout the subsequent fixation. By transforming to time coordinates of alpha cycles, we found that these alpha oscillations modulated the response gain of V1 neurons, resulting in a temporal windowing of the stimulus processing following saccades. The stimulus tuning of gamma (35-60 Hz) power was similarly modulated by the alpha rhythm, and the gamma oscillations provided further temporal structure to the spiking activity through spike-phase coupling. These results show that during free viewing, alpha oscillations following saccades create a temporal windowing of V1 activity during fixations, and more generally suggest that stimulus-driven network dynamics may play an important role in shaping feedforward stimulus processing.
A QoS multicast routing protocol for mobile ad-hoc networks

This paper presents a hierarchical QoS multicast routing protocol (HQMRP) for mobile ad-hoc networks. It can provide QoS-sensitive routes in a scalable and flexible way, in the network environment with mobility. In the proposed HQMRP scheme, each local node just only needs to maintain local multicast routing information and/or summary information of other clusters (or domains), but does not requires any global ad hoc network states to be maintained. The HQMRP also allows that an ad-hoc group member can join/leave the multicast group dynamically, and supports multiple QoS constraints. The paper presents the proof of correctness and complexity analysis of the protocol. The performance measures of HQMRP are evaluated using simulation. The studies show that HQMRP can provide an available approach to QoS multicast routing for mobile ad-hoc networks.
Application of AIS in AtoN surveillance service

This paper puts forward a design of an Aid to Navigation (AtoN) wireless surveillance system based on Automatic Identification System (AIS). The system consists of AtoN with AIS, AIS base station and AtoN management center. It can provide such functions as the information gathering, managing of AtoN and the service of navigation assistance. This paper brought forward the whole design including the system work theory, the hardware structure and the software scheme of the system. And it also realized the system software of the AtoN management center. The AtoN wireless surveillance service system will be more efficient with less repair cost and less work of the supervisors. It will bring revolutionary progress in the navigation aids system.