Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the digital music library: tune retrieval from acoustic input

Music is traditionally retrieved by title, composer or subjectclassification. It is possible, with current technology, toretrieve music from a database on the basis of a few notes sung orhummed into a microphone. This paper describes the implementationof such a system, and discusses several issues pertaining to musicretrieval. We first describe an interface that transcribes acousticinput into standard music notation. We then analyze string matchingrequirements for ranked retrieval of music and present the resultsof an experiment which tests how accurately people sing well knownmelodies. The performance of several string matching criteria areanalyzed using two folk song databases. Finally, we describe aprototype system which has been developed for retrieval of tunesfrom acoustic input.
A system of classifying microvascular invasion to predict outcome after resection in patients with hepatocellular carcinoma.

BACKGROUND & AIMS Hepatocellular carcinoma (HCC) recurs in approximately 70% of cases after resection. Vascular invasion by tumor cells can be classified as gross or microscopic (microvascular invasion [mVI]) and is a risk factor for recurrence. We examined a large cohort of patients with HCC who were treated by resection to identify features of mVI that correlated with recurrence and survival. METHODS We reviewed the records of all HCC resections performed at the Mount Sinai School of Medicine between January 1990 and March 2006 to identify those with mVI, established by histologic analysis. The numbers and sizes of vessels invaded, invasion of a vessel with a muscular wall, distance from the tumor, and satellite nodules were recorded. RESULTS Of the 384 patients who underwent resection for HCC, 131 (34.1%) met the entry criteria. The median follow-up period was 28.9 months. There were 68 recurrences and 54 deaths. In multivariate analysis, invasion of a vessel with a muscular wall predicted recurrence (hazard ratio, 1.8; P = .02), and invasion of a vessel with a muscular wall (hazard ratio, 2.2; P = .018) and invasion of a vessel that was more than 1 cm from the tumor (hazard ratio, 2.1; P = .015) predicted survival. A risk score that assigned points for the presence of each variable correlated with recurrence (P = .028) and survival (P < .0001). CONCLUSIONS A novel classification system that includes invasion of a vessel with a muscular wall and invasion of a vessel that is more than 1 cm from the tumor can accurately predict risk of recurrence and survival of patients with mVI after resection of HCC.
Diagnosis and management of central hypersomnias

Central hypersomnias are diseases manifested in excessive daytime sleepiness (EDS) not caused by disturbed nocturnal sleep or misaligned circadian rhythms. Central hypersomnias includes narcolepsy with and without cataplexy, recurrent hypersomnia, idiopathic hypersomnia, with and without long sleep time, behaviorally induced insufficient sleep syndrome, hypersomnia and narcolepsy due to medical conditions, and finally hypersomnia induced by substance intake. The Epworth Sleepiness Scale is a subjective tool mostly used for EDS assessment, while the Multiple Sleep Latency Test serves as an objective diagnostic method for narcolepsy and idiopathic hypersomnias. As for symptomatic therapy of EDS, the central nervous system stimulants modafinil and methylphenidate seem to work well in most cases and in narcolepsy and Parkinson’s disease; sodium oxybate also has notable therapeutic value.
A Panel of Novel Detection and Prognostic Methylated DNA Markers in Primary Non–Small Cell Lung Cancer and Serum DNA

Purpose: To establish a novel panel of cancer-specific methylated genes for cancer detection and prognostic stratification of early-stage non–small cell lung cancer (NSCLC). Experimental Design: Identification of differentially methylated regions (DMR) was performed with bumphunter on “The Cancer Genome Atlas (TCGA)” dataset, and clinical utility was assessed using quantitative methylation-specific PCR assay in multiple sets of primary NSCLC and body fluids that included serum, pleural effusion, and ascites samples. Results: A methylation panel of 6 genes (CDO1, HOXA9, AJAP1, PTGDR, UNCX, and MARCH11) was selected from TCGA dataset. Promoter methylation of the gene panel was detected in 92.2% (83/90) of the training cohort with a specificity of 72.0% (18/25) and in 93.0% (40/43) of an independent cohort of stage IA primary NSCLC. In serum samples from the later 43 stage IA subjects and population-matched 42 control subjects, the gene panel yielded a sensitivity of 72.1% (31/41) and specificity of 71.4% (30/42). Similar diagnostic accuracy was observed in pleural effusion and ascites samples. A prognostic risk category based on the methylation status of CDO1, HOXA9, PTGDR, and AJAP1 refined the risk stratification for outcomes as an independent prognostic factor for an early-stage disease. Moreover, the paralog group for HOXA9, predominantly overexpressed in subjects with HOXA9 methylation, showed poor outcomes. Conclusions: Promoter methylation of a panel of 6 genes has potential for use as a biomarker for early cancer detection and to predict prognosis at the time of diagnosis. Clin Cancer Res; 23(22); 7141–52. ©2017 AACR.
RadioGatún, a belt-and-mill hash function

We present an approach to design cryptographic hash functions that builds on and improves the one underlying the Panama hash function. We discuss the properties of the resulting hash functions that need to be investigated and give a concrete design called RadioGatun that is quite competitive with SHA-1 in terms of performance. We are busy performing an analysis of RadioGatun and present in this paper some preliminary results.
An Experimental Comparison of Speed Scaling Algorithms with Deadline Feasibility Constraints

We consider the first, and most well studied, speed scaling problem in the algorithmic literature: where the scheduling quality of service measure is a deadline feasibility constraint, and where the power objective is to minimize the total energy used. Four online algorithms for this problem have been proposed in the algorithmic literature. Based on the best upper bound that can be proved on the competitive ratio, the ranking of the online algorithms from best to worst is: $\qOA$, $\OA$, $\AVR$, $\BKP$. As a test case on the effectiveness of competitive analysis to predict the best online algorithm, we report on an experimental "horse race" between these algorithms using instances based on web server traces. Our main conclusion is that the ranking of our algorithms based on their performance in our experiments is identical to the order predicted by competitive analysis. This ranking holds over a large range of possible power functions, and even if the power objective is temperature.
Isoform-Specific Modulation of Voltage-Gated Na+ Channels by Calmodulin

Calmodulin (CaM) is a calcium-sensing protein that binds to Na+ channels, with unknown functional consequences. Wild-type CaM produced a hyperpolarizing shift in the steady-state availability of expressed skeletal muscle (&mgr;1) but not cardiac (hH1) Na+ channels. Mutant CaM1234 did not alter the voltage dependence or the kinetics of gating of either &mgr;1 or hH1. Mutation of the highly conserved IQ motif in the carboxyl terminus of both isoforms (IQ/AA) slowed the kinetics of current decay and abolished the effect of wild-type CaM on &mgr;1, but did not alter hH1 currents. The IQ/AA mutation eliminated CaM binding to the carboxyl terminus of both &mgr;1 and hH1 channels. Inhibition of Ca2+/CaM kinase (CaM-K) slowed the current decay, the rate of entry into inactivation, and shifted the voltage dependence of hH1 in the depolarizing direction independent of CaM overexpression with no effect on &mgr;1 Na+ channels. CaM signaling modulates Na+ currents in an isoform-specific manner, via direct interaction with skeletal muscle Na+ channels and through CaM-K in the case of the cardiac isoform. The full text of this article is available at http://www.circresaha. org.
Impact of the Union and Difference Operations on the Quality of Information Products

Information derived from relational databases is routinely used for decision making. However, little thought is usually given to the quality of the source data, its impact on the quality of the derived information, and how this in turn affects decisions. To assess quality, one needs a framework that defines relevant metrics that constitute the quality profile of a relation, and provides mechanisms for their evaluation. We build on a quality framework proposed in prior work, and develop quality profiles for the result of the primitive relational operations Difference and Union. These operations have nuances that make both the classification of the resulting records as well as the estimation of the different classes quite difficult to address, and very different from that for other operations. We first determine how tuples appearing in the results of these operations should be classified as accurate, inaccurate or mismember, and when tuples that should appear do not (called incomplete) in the result. Although estimating the cardinalities of these subsets directly is difficult, we resolve this by decomposing the problem into a sequence of drawing processes, each of which follows a hyper-geometric distribution. Finally, we discuss how decisions would be influenced based on the resulting quality profiles.
The Conceptual Mechanism for Viable Organizational Learning Based on Complex System Theory and the Viable System Model.

The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The final research efforts to make is to propose an integrated mechanism for the living learning organization, in which it could adapt to environmental changes and create innovative knowledge continuously.
What Is the Evidence for Physical Therapy Poststroke? A Systematic Review and Meta-Analysis

Background Physical therapy (PT) is one of the key disciplines in interdisciplinary stroke rehabilitation. The aim of this systematic review was to provide an update of the evidence for stroke rehabilitation interventions in the domain of PT. Methods and Findings Randomized controlled trials (RCTs) regarding PT in stroke rehabilitation were retrieved through a systematic search. Outcomes were classified according to the ICF. RCTs with a low risk of bias were quantitatively analyzed. Differences between phases poststroke were explored in subgroup analyses. A best evidence synthesis was performed for neurological treatment approaches. The search yielded 467 RCTs (N = 25373; median PEDro score 6 [IQR 5–7]), identifying 53 interventions. No adverse events were reported. Strong evidence was found for significant positive effects of 13 interventions related to gait, 11 interventions related to arm-hand activities, 1 intervention for ADL, and 3 interventions for physical fitness. Summary Effect Sizes (SESs) ranged from 0.17 (95%CI 0.03–0.70; I2 = 0%) for therapeutic positioning of the paretic arm to 2.47 (95%CI 0.84–4.11; I2 = 77%) for training of sitting balance. There is strong evidence that a higher dose of practice is better, with SESs ranging from 0.21 (95%CI 0.02–0.39; I2 = 6%) for motor function of the paretic arm to 0.61 (95%CI 0.41–0.82; I2 = 41%) for muscle strength of the paretic leg. Subgroup analyses yielded significant differences with respect to timing poststroke for 10 interventions. Neurological treatment approaches to training of body functions and activities showed equal or unfavorable effects when compared to other training interventions. Main limitations of the present review are not using individual patient data for meta-analyses and absence of correction for multiple testing. Conclusions There is strong evidence for PT interventions favoring intensive high repetitive task-oriented and task-specific training in all phases poststroke. Effects are mostly restricted to the actually trained functions and activities. Suggestions for prioritizing PT stroke research are given.
Applying scattering theory to robot audition system: robust sound source localization and extraction

Robot audition by its own ears (microphones) is essential for natural human-robot communication and interface. Since a microphone is embedded in the head of a robot, the head-related transfer function (HRTF) plays an important role in sound source localization and extraction. Usually, from binaural input, the interaural phase difference (IPD) and interaural intensity difference (IID) are calculated, and then the direction is determined by using IPD and IID with HRTF. The problem of HRTF-based sound source localization is that a HRTF should be measured for each robot in an anechoic chamber, because it depends on the shape of robot's head; HRTF should be interpolated to manipulate a moving talker, because it is available only for discrete azimuth and elevation. To cope with these problems of HRTF, we proposed the auditory epipolar geometry as a continuous function of IPD and IID to dispense with HRTF and have developed a real-time multiple-talker tracking system. This auditory epipolar geometry, however, does not give a good approximation to IID of all range and IPD of peripheral areas. In this paper, the scattering theory in physics is employed to take into consideration the diffraction of sounds around robot's head for better approximation of IID and IPD. The resulting system shows that it is efficient for localization and extraction of sound at higher frequency and from side directions.
Packet types: abstract specification of network protocol messages

In writing networking code, one is often faced with the task of interpreting a raw buffer according to a standardized packet format. This is needed, for example, when monitoring network traffic for specific kinds of packets, or when unmarshaling an incoming packet for protocol processing. In such cases, a programmer typically writes C code that understands the grammar of a packet and that also performs any necessary byte-order and alignment adjustments. Because of the complexity of certain protocol formats, and because of the low-level of programming involved, writing such code is usually a cumbersome and error-prone process. Furthermore, code written in this style loses the domain-specific information, viz. the packet format, in its details, making it difficult to maintain.
Design of a robust, high performance standard cell threshold logic family for DSM technology

This paper presents the threshold logic latch (TLL), which provides a high performance, low power alternative to traditional CMOS logic networks. TLL is highly robust, even in deep sub-micron technology nodes. Experimental results obtained from simulation of a commercial 65 nm low power process demonstrate a static noise margin up to an order of magnitude greater than those of existing implementations of threshold logic. Examples of automated synthesis of pipelined multipliers using a combination of standard CMOS and a small number of TLL gates are shown through simulation to improve both area and total power by a factor of up to 1.5 and reduce leakage power by a factor of up to 2.3.
Integer multiplication and division on the HP precision architecture

In recent years, many architectural design efforts have focused on maximizing performance for frequently executed, simple instructions. Although these efforts have resulted in machines with better average price/performance ratios, certain complex instructions and, thus, certain classes of programs which heavily depend on these instructions may suffer by comparison. Integer multiplication and division are one such set of complex instructions. This paper describes how a small set of primitive instructions combined with careful frequency analysis and clever programming allows the Hewlett-Packard Precision Architecture integer multiplication and division implementation to provide adequate performance at little or no hardware cost.
Temporal Probabilistic Logic Programs: State and Revision

There are numerous applications where we have to deal with temporal uncertainty associated with events. The Temporal Probabilistic (TP) Logic Programs should provide support for valid-time indeterminacy of events, by proposing the concept of an indeterminate instant, that is, an interval of time-points (event's time-window) with an associated, lower and upper, probability distribution. In particular, we propose the new semantics, for the TP Logic Programs of Dekhtyar and Subrahmanian. Our semantics, based on the possible world semantics is a generalization of the possible world semantics for (non temporal) Probabilistic Logic Programming, and we define the new syntax for PT-programs, with time variable explicitly represented in all atoms, and show how the standard role of Herbrand interpretations used as possible worlds for probability distributions is coherently extended to Temporal Probabilistic Logic Programming.
First Experimental Results with the Imaging MIMO Radar MIRA-CLE X

MIMO radar for imaging is a quite new and promising research field with a big potential for various applications. Three different imaging radars based on the MIMO principle are currently developed at Fraunhofer FHR. This paper describes the ground based X-band MIMO radar MIRA-CLE X. This radar consists of 16 transmit and 14 receive antennas which are arranged in a special way to synthesize a fully and equally spaced virtual antenna array of 224 elements during signal processing. First image results of MIRA-CLE X are presented and discussed.
The identification and variability of the parasites causing leishmaniasis in HIV-positive patients in Italy

Abstract Between 1988 and 1998, 258 Leishmania strains from patients infected with HIV were characterized by iso-enzyme electrophoresis at the Istituto Superiore di Sanità (ISS) in Rome. Most (227) of the isolates came from 80 Italian patients with visceral leishmaniasis (VL), the rest from cases of Leishmania/HIV co-infection in other Mediterranean countries. Every strain was found to be Leishmania infantum. In Italy, 19 zymodemes of L. infantum were identified, broadly divided into three groups. Over 50% of the Italian patients were infected by the commonest agent of Mediterranean VL in HIV-negative individuals (zymodeme MON-1) whereas the remaining patients were infected by two distinct groups of zymodemes: one usually causing simple, self-resolving cutaneous leishmaniasis in HIV-negative patients, the other consisting of agents detected, so far, only in HIV-positive subjects. This last group, consisting of seven zymodemes, showed re-assortment patterns within electromorphs frequently observed in dermotropic L. infantum zymodemes. A similar grouping was also observed in the isolates from other Mediterranean countries. Basing on general data recorded at the ISS over the last 20 years, accurate identification of the geographical origin of the zymodemes was attempted by careful analysis of the patients' histories, using the iso-enzyme electromorphs as geographical markers. Furthermore, a polymorphism index (no. of zymodemes/no. of patients) was defined for each Leishmania species and geographical region, and used to assess the level of L. infantum zymodeme heterogeneity in Italy, before and after stratification by HIV status. The greatest zymodeme heterogeneity was found in Sicily (southern Italy), with nine zymodemes identified among only 30 HIV-positive patients.
An integrated passive-flow microfluidic biosensor with organic photodiodes for ultra-sensitive pathogen detection in water

This work reports on integrated passive-flow optical microfluidic devices to detect waterborne pathogens in the field. Ring-shaped organic photodiodes were integrated to a capillary-induced flow microfluidic channel for monitoring chemiluminescent sandwich immunoassays enhanced by gold nanoparticles. The integrated device yielded a resolution of 4×104 cells/mL for the detection of Legionella pneumophila, which represented a 25-fold improvement over chemiluminescence detection devices employing no gold-nanoparticle enhancement. This work demonstrates the feasibility of a low-cost but highly sensitive lab-on-a-chip device amenable for point-of-use applications.
A Fast k-Nearest Neighbor Search Using Query-Specific Signature Selection

k-nearest neighbor (k-NN) search aims at finding k points nearest to a query point in a given dataset. k-NN search is important in various applications, but it becomes extremely expensive in a high-dimensional large dataset. To address this performance issue, locality-sensitive hashing (LSH) is suggested as a method of probabilistic dimension reduction while preserving the relative distances between points. However, the performance of existing LSH schemes is still inconsistent, requiring a large amount of search time in some datasets while the k-NN approximation accuracy is low. In this paper, we target on improving the performance of k-NN search and achieving a consistent k-NN search that performs well in various datasets. In this regard, we propose a novel LSH scheme called Signature Selection LSH (S2LSH). First, we generate a highly diversified signature pool containing signature regions of various sizes and shapes. Then, for a given query point, we rank signature regions of the query and select points in the highly ranked signature regions as k-NN candidates of the query. Extensive experiments show that our approach consistently outperforms the state-of-the-art LSH schemes.
An Empirical Study on Sentiment Classification of Chinese Review using Word Embedding

In this article, how word embeddings can be used as features in Chinese sentiment classification is presented. Firstly, a Chinese opinion corpus is built with a million comments from hotel review websites. Then the word embeddings which represent each comment are used as input in different machine learning methods for sentiment classification, including SVM, Logistic Regression, Convolutional Neural Network (CNN) and ensemble methods. These methods get better performance compared with N-gram models using Naive Bayes (NB) and Maximum Entropy (ME). Finally, a combination of machine learning methods is proposed which presents an outstanding performance in precision, recall and F1 score. After selecting the most useful methods to construct the combinational model and testing over the corpus, the final F1 score is 0.920.
Design of Tunable Channel Drop Filter using Hexagonal Photonic Crystal Ring Resonators by FDTD Method

In this paper, we have proposed a new design of two dimensional (2D) photonic crystal (PhC) Tunable channel drop filter (CDF) using ring resonators. The increasing interest in photonic integrated circuits (PIC’s) and the increasing use of alloptical fiber networks as backbones for global communication systems have been based in large part on the extremely wide optical transmission bandwidth provided by dielectric materials. Based on the analysis we present novel photonic crystal channel drop filters. Simulations demonstrate that these filters exhibit ideal transfer characteristics. Dropping efficiency at the resonance of single ring are 92% and quality factor is obtained 1046. The footprint of the proposed structure is about 125. 6μm2; therefore this structure can be used in the future photonic integrated circuits.