Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Information Retrieval with Split-layer Language Models

the increasing prevalence of electronic medical records (EMRs), search technologies for these systems hold signifi- cant promise for improving patient and population care. We present a split-layer language model that embeds linguistic layers from existing NLP systems in retrieving medical docu- ments. On the cohort identification task of the TREC Med- ical Records Track, our approach shows improvement over baselines, with the best performance achieved by mixing in all tested layers of NLP artifacts.
Rapid enzymatic detection of Escherichia coli contamination in polluted river water

Aims: The relationship between the rate of β‐D‐glucuronidase hydrolysis (GLUase‐HR) and the E. coli concentration in rivers differing in the extent of faecal pollution was investigated. It was hypothesized that the rate of GLUase‐HR is a better surrogate parameter for E. coli concentrations than estimated numbers of faecal coliforms (FC).
A theoretical approach for the dislocation reduction of wurtzite InxGa1−xN/GaN heteroepitaxy

This paper reports the numerical estimation of misfit dislocation in wurtzite InxGa1-xN/GaN heterostructure. The misfit strain increases with the increase of lattice mismatch for higher In content. The exponential grading technique has been modelled for the reduction of dislocation. An energy balance model has been modified to evaluate the misfit dislocation density. The dislocation density has been reduced from 68.07*10^9 cm-2 to 0.288*10^6 cm-2 which is tapered in nature and help to promote annihilation and coalescence reactions between threading dislocations without unwanted tangling and pinning events. Finally, a comparative analysis has also been shown between without graded layer having constant composition and exponentially graded layer In0.2Ga0. 8N/GaN.
Global Positioning System Data Analysis: Velocity Ranges and a New Definition of Sprinting for Field Sport Athletes

Dwyer, DB and Gabbett, TJ. Global positioning system data analysis: Velocity ranges and a new definition of sprinting for field sport athletes. J Strength Cond Res 26(3): 818–824, 2012—Global positioning system (GPS) technology has improved the speed, accuracy, and ease of time-motion analyses of field sport athletes. The large volume of numerical data generated by GPS technology is usually summarized by reporting the distance traveled and time spent in various locomotor categories (e.g., walking, jogging, and running). There are a variety of definitions used in the literature to represent these categories, which makes it nearly impossible to compare findings among studies. The purpose of this work was to propose standard definitions (velocity ranges) that were determined by an objective analysis of time-motion data. In addition, we discuss the limitations of the existing definition of a sprint and present a new definition of sprinting for field sport athletes. Twenty-five GPS data files collected from 5 different sports (men's and women's field hockey, men's and women's soccer, and Australian Rules Football) were analyzed to identify the average velocity distribution. A curve fitting process was then used to determine the optimal placement of 4 Gaussian curves representing the typical locomotor categories. Based on the findings of these analyses, we make recommendations about sport-specific velocity ranges to be used in future time-motion studies of field sport athletes. We also suggest that a sprint be defined as any movement that reaches or exceeds the sprint threshold velocity for at least 1 second and any movement with an acceleration that occurs within the highest 5% of accelerations found in the corresponding velocity range. From a practical perspective, these analyses provide conditioning coaches with information on the high-intensity sprinting demands of field sport athletes, while also providing a novel method of capturing maximal effort, short-duration sprints.
NMR of proteins and nucleic acids

Introduction and Survey. THE FOUNDATIONS: STRUCTURE AND NMR OF BIOPOLYMERS. NMR of Amino Acid Residues and Mononucleotides. NMR Spectra of Proteins and Nucleic Acids in Solution. The NMR Assignment Problem in Biopolymers. Two-Dimensional NMR With Proteins and Nucleic Acids. Nuclear Overhauser Enhancement (NOE) in Biopolymers. RESONANCE ASSIGNMENTS AND STRUCTURE DETERMINATION IN PROTEINS. NOE-Observable 1H-1H Distances in Proteins. Sequence-Specific Resonance Assignments in Proteins. Polypeptide Secondary Structures in Proteins by NMR. Three-Dimensional Protein Structures by NMR. RESONANCE ASSIGNMENTS AND STRUCTURE DETERMINATION IN NUCLEIC ACIDS. NOE-Observable 1H-1H Distances in Nucleic Acids. Resonance Assignments in Nucleic Acids Using Scalar Couplings. Nucleic Acid Conformation, 1H-1H Overhauser Effects, and Sequence-Specific Resonance Assignments. WITH NMR TO BIOPOLYMER CONFORMATION AND BEYOND. Conformation of Noncrystalline Proteins and Nucleic Acids. NMR Studies of Intermolecular Interactions with Biopolymers. References. Index.
Secondary Sex Ratio among Women Exposed to Diethylstilbestrol in Utero

Background Diethylstilbestrol (DES), a synthetic estrogen widely prescribed to pregnant women during the mid-1900s, is a potent endocrine disruptor. Previous studies have suggested an association between endocrine-disrupting compounds and secondary sex ratio. Methods Data were provided by women participating in the National Cancer Institute (NCI) DES Combined Cohort Study. We used generalized estimating equations to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the relation of in utero DES exposure to sex ratio (proportion of male births). Models were adjusted for maternal age, child’s birth year, parity, and cohort, and accounted for clustering among women with multiple pregnancies. Results The OR for having a male birth comparing DES-exposed to unexposed women was 1.05 (95% CI, 0.95–1.17). For exposed women with complete data on cumulative DES dose and timing (33%), those first exposed to DES earlier in gestation and to higher doses had the highest odds of having a male birth. The ORs were 0.91 (95% C, 0.65–1.27) for first exposure at ≥ 13 weeks gestation to < 5 g DES; 0.95 (95% CI, 0.71–1.27) for first exposure at ≥ 13 weeks to ≥ 5 g; 1.16 (95% CI, 0.96–1.41) for first exposure at < 13 weeks to < 5 g; and 1.24 (95% CI, 1.04–1.48) for first exposure at < 13 weeks to ≥ 5 g compared with no exposure. Results did not vary appreciably by maternal age, parity, cohort, or infertility history. Conclusions Overall, no association was observed between in utero DES exposure and secondary sex ratio, but a significant increase in the proportion of male births was found among women first exposed to DES earlier in gestation and to a higher cumulative dose.
Dynamic characteristics of musical note for musical instrument classification

The changes of short-term feature in a musical note can reflect the timbre of musical instrument. In this paper, the short-term features of frames in a musical note instead of in a window of fixed length are integrated into a note feature vector, which captures the dynamic characteristics of musical note, by diverse integration methods such as statistic (ST) model, autoregressive (AR) model and modulation model. For musical instrument classification, it is verified that the pitch-frequency cepstral coefficients (PFCCs) as short-term features are better than the mel-frequency cepstral coefficients (MFCCs). We select the PFCCs and the partials amplitudes as short-term feature to generate note features by integration models respectively. In the experience, the Gaussian mixture model (GMM) classifier and Random Forest (RF) classifier are exploited to testify that these note features are useful for musical instrument classification. Results demonstrate that the combination of ST model, univariate AR model and 2-dimension modulation model is exceptionally superior to the short-term feature whether it is based on partials amplitudes or based on PFCCs.
Adaptive Mesh Selection Based on the Equidistribution of the Global Error of Collocation Methods

We describe a mesh selection strategy for the numerical solution of boundary value problems for singular ordinary differential equations. This mesh adaptation procedure is implemented in our MATLAB code sbvp which is based on polynomial collocation. We prove that under realistic assumptions our mesh selection strategy serves to approximately equidistribute the global error of the collocation solution, thus enabling to reach prescribed tolerances efficiently. Moreover, we demonstrate that this strategy yields a favorable performance of the code and compare its computational effort with other implementations of polynomial collocation.
Procedure for audio-assisted browsing of news video using generalized sound recognition

In Casey describes a generalized sound recognition framework based on reduced rank spectra and Minimum-Entropy Priors. This approach enables successful recognition of a wide variety of sounds such as male speech, female speech, music, animal sounds etc. In this work, we apply this recognition framework to news video to enable quick video browsing. We identify speaker change positions in the broadcast news using the sound recognition framework. We combine the speaker change position with color & motion cues from video and are able to locate the beginning of each of the topics covered by the news video. We can thus skim the video by merely playing a small portion starting from each of the locations where one of the principal cast begins to speak. In combination with our motion-based video browsing approach, our technique provides simple automatic news video browsing. While similar work has been done before, our approach is simpler and faster than competing techniques, and provides a rich framework for further analysis and description of content.
A flexible model for resource management in virtual private networks

As IP technologies providing both tremendous capacity and the ability to establish dynamic secure associations between endpoints emerge, Virtual Private Networks (VPNs) are going through dramatic growth. The number of endpoints per VPN is growing and the communication pattern between endpoints is becoming increasingly hard to forecast. Consequently, users are demanding dependable, dynamic connectivity between endpoints, with the network expected to accommodate any traffic matrix, as long as the traffic to the endpoints does not overwhelm the rates of the respective ingress and egress links. We propose a new service interface, termed a hose, to provide the appropriate performance abstraction. A hose is characterized by the aggregate traffic to and from one endpoint in the VPN to the set of other endpoints in the VPN, and by an associated performance guarantee.Hoses provide important advantages to a VPN customer: (i) flexibility to send traffic to a set of endpoints without having to specify the detailed traffic matrix, and (ii) reduction in the size of access links through multiplexing gains obtained from the natural aggregation of the flows between endpoints. As compared with the conventional point to point (or customer-pipe) model for managing QoS, hoses provide reduction in the state information a customer must maintain. On the other hand, hoses would appear to increase the complexity of the already difficult problem of resource management to support QoS. To manage network resources in the face of this increased uncertainty, we consider both conventional statistical multiplexing techniques, and a new resizing technique based on online measurements.To study these performance issues, we run trace driven simulations, using traffic derived from AT&amp;T's voice network, and from a large corporate data network. From the customer's perspective, we find that aggregation of traffic at the hose level provides significant multiplexing gains. From the provider's perspective, we find that the statistical multiplexing and resizing techniques deal effectively with uncertainties about the traffic, providing significant gains over the conventional alternative of a mesh of statically sized customer-pipes between endpoints.
Robust beamforming against direction-of-arrival mismatch via signal-to-interference-plus-noise ratio maximization

In this paper, the problem of adaptive beamforming in the presence of direction-of-arrival (DOA) mismatch is investigated. To develop a robust beamformer against such an imperfection, a new approach is devised by formulating an output signal-to-interference-plus-noise ratio (SINR) maximization problem. In particular, the proposed robust beamforming approach consists of two steps. At first, the standard Capon beamformer (SCB) is applied to find out the sidelobe notches and hence, a set of angles including the interference DOAs and the corresponding response levels can be determined. Next, the output SINR is maximized subject to a number of constraints on the response levels at the region of interest (ROI) and angles determined in the first step. In order to tackle the resulting nonconvex optimization problem, semidefinite relaxation techniques are thus employed to achieve an approximated solution. Simulation results demonstrate that the proposed robust beamformer offers outstanding robustness against DOA mismatch, low sample size as well as the presence of the desired signal in the training samples.
Effects of inhaled nanoparticle-rich diesel exhaust on regulation of testicular function in adult male rats

We investigated the effects of nanoparticle-rich diesel exhaust (NR-DE) on reproductive function. Eight-week-old male F344 rats were divided into 12 experimental groups and exposed to either whole NR-DE at low (15.37 μg/m3, 2.27 × 105 particles/cm3), middle (36.35 μg/m3, 5.11 × 105 particles/cm3), or high (168.84 μg/m3, 1.36 × 106 particles/cm3) concentrations or clean air for 4, 8, or 12 weeks (5 hours/day, 5 days/week). NR-DE exposure for 4 or 8 weeks did not affect body weight; however, body weight was significantly decreased in rats exposed to low- or high- concentration NR-DE for 12 weeks compared to the control group. Relative weights of testes, epididymides, seminal vesicles, and prostate had increased non-significantly in all NR-DE-exposed rats at 4, 8, and 12 weeks. Adrenal gland relative weights were significantly increased at 4 weeks in rats exposed to low-concentration NR-DE. Plasma luteinizing hormone and follicle stimulating hormone concentrations did not change significantly. Plasma testosterone concentrations were significantly increased after exposure to low- or middle-concentration NR-DE for 4 or 8 weeks compared to controls. Plasma immunoreactive (ir-) inhibin concentrations were significantly increased after exposure to high-concentration NR-DE for 4 weeks or middle- or high-concentration NR-DE for 12 weeks compared to controls. Testicular testosterone concentrations were significantly increased at 4, 8, and 12 weeks after exposure to low-concentration NR-DE compared to controls. In contrast, with exposure to low- or high-concentration NR-DE, testicular ir-inhibin concentrations were significantly greater than in controls, but only at 4 weeks. These results suggest that NR-DE inhalation disrupts the endocrine activity of the male reproductive system.
Constructing facial identity surfaces in a nonlinear discriminating space

Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, self-shading and self-occlusion. To address this problem, a multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns from multi-view face images. Kernel Discriminant Analysis is developed to extract the significant non-linear discriminating features which maximise the between-class variance and minimise the within-class variance. By using the kernel technique, this process is equivalent to a Linear Discriminant Analysis in a high-dimensional feature space which can be solved conveniently. The identity surfaces are then constructed from these non-linear discriminating features. Face recognition can be performed dynamically from an image sequence by matching an object trajectory and model trajectories on the identity surfaces.
Capability Annotation of Actions Based on Their Textual Descriptions

Current approaches for semantic management of business processes and services assume and build on semantic models which don't exist in practice. A key and open research problem is how to lift semantic models from existing process and service descriptions. In this paper, we are interested in extracting action capabilities from their textual descriptions. We first introduce a semantic frame-based capability model that features domain-specific functional properties. We presentan approach for retrieving top-k capabilities that match best a natural language description of an action. Our approach has been evaluated using publicly available process and service descriptions.
Deletion Mapping of the Encephalomyocarditis Virus Primary Cleavage Site

ABSTRACT The cotranslational, primary self-cleavage reaction of cardiovirus polyprotein relies on a highly conserved, short segment of amino acids at the 2A-2B protein boundary. The amino terminus of the required element for encephalomyocarditis virus has now been mapped to include Tyr126 of the 2A protein, the 18th amino acid before the cleavage site.
Scaled telemanipulation with communication time delay

This paper proposes a control algorithm of a scaled telemanipulation system with communication time delay. With the proposed algorithm, the motion and force relation between the master manipulator and the slave manipulator can be specified freely by using two scaling factors: a motion scaling factor, and a force scaling factor. The scattering transformation is used to guarantee the passivity of the communication system. The stability of the resultant system is analyzed in view of the passivity and the total stability is guaranteed for an operator and a passive environment with unknown dynamics. The proposed method is experimentally applied to a master slave manipulator and the experimental results illustrate the validity of the system.
Measuring LTE and WiFi coexistence in Unlicensed spectrum

The exponential growth in mobile services demand, along with the scarce licensed spectrum in the sub-6GHz bands, mandate the exploitation of bands other than the traditionally used by mobile broadband technologies. An example of such operation is the opportunistic access of the unlicensed bands by the LTE technology, as a means to increase the delivered end-user capacity and enhancing the overall quality of experience. In this paper, we present some extensive testbed measurements used for modeling the coexistence of LTE and WiFi technologies when operating within the same unlicensed environment. The experiments deal with different bandwidth settings for both the WiFi and LTE technologies, when LTE is operating closely or inside the primary or secondary channels of IEEE 802.11, taking into account the different threshold values for the Clear Channel Assessment functions that WiFi entails. We present exhaustive experimental measurements, collected under a real testbed setup, and present a cognitive algorithm for minimizing the impact of the two technologies to each other.
Quantitative Modeling of Thermo-Optic Effects in Optical Networks-on-Chip

Optical networks-on-chip (ONoCs) is a new promising communication paradigm that upgrades the traditional on-chip networks (NoCs) with the ultra-high communication bandwidth and low latency. Silicon microring resonators (MRRs), as a critical component of ONoCs used to implement the selection and redirection of optical signals, are inherently sensitive to the environmental temperature. The applicability of the ONoCs is essentially restricted by the performance of these optical devices that relies on the thermal conditions of the chip. In this paper, we study the thermo-optic effects of the MRRs quantitatively, build and verify the models of the MRRs based on the finite-difference time-domain (FDTD) method. We present formal relationship models between the temperature of a MRR and its optical losses and resonance wavelength. For the first time, the variation between the two types of MRRs, the parallel microring resonators (PMRs) and the crossing microring resonators (CMRs), are systematically addressed, which greatly improves the accuracy and applicability of the models. The results presented in this paper are systematically verified using professional optics methodology, and can be widely applied for accurate and efficient analysis of the thermo-optic effects in different domains of the ONoC community.
OpenMath: compositionality achieved at last

As a language for exchanging computer-"understandable" representations of mathematical formulas and concepts, OpenMath has a fairly standard syntactic structure for most of the mathematical notions that have so far been formalized in its "Content Dictionaries. " The syntax for most operators is closely related to the well-known and decades-old LISP prefix notation for function application.For syntactic representations of a particular large class of mathematical operators, however, OpenMath takes a very unusual approach when compared with any of the existing Computer Algebra systems, say. This class contains integration and differentiation operators, sums and products, and other generalized quantifiers.In our paper we argue that OpenMath's novel approach to representing generalized quantifiers is superior to the classic representations. In particular, we show that this unusual feature of OpenMath has been designed to adhere to the Compositionality Principle[10], a design principle that classic representations, including older versions of OpenMath, have been violating[12]. Having thus shown the importance of compositionality for the design of modern OpenMath, we then proceed to show that the Compositionality Principle is a fundamental research instrument in the Formal Semantics branch of linguistics[9], and argue that, like the use of this particular guiding principle for improvements in the design of a representation for generalized quantifiers, the study of the underlying structure of natural language as discovered by various branches of linguistics can provide many more suggestions for further improvements to OpenMath and to its sibling, MathML. We give some examples to substantiate our claim.
Implications of ceiling effects in defect predictors

Context: There are many methods that input static code features and output a predictor for faulty code modules. These data mining methods have hit a "performance ceiling"; i.e., some inherent upper bound on the amount of information offered by, say, static code features when identifying modules which contain faults. Objective: We seek an explanation for this ceiling effect. Perhaps static code features have "limited information content"; i.e. their information can be quickly and completely discovered by even simple learners. Method:An initial literature review documents the ceiling effect in other work. Next, using three sub-sampling techniques (under-, over-, and micro-sampling), we look for the lower useful bound on the number of training instances. Results: Using micro-sampling, we find that as few as 50 instances yield as much information as larger training sets. Conclusions: We have found much evidence for the limited information hypothesis. Further progress in learning defect predictors may not come from better algorithms. Rather, we need to be improving the information content of the training data, perhaps with case-based reasoning methods.