Miracle-dz/UniFAR-FTUs huggingface dataset:
Canine Plasminogen: Spectral Responses to Changes in 6-Aminohexanoate and Temperature

We studied the near UV absorption spectrum of canine plasminogen. There are 19 tryptophans, 19 phenylalanines and 34 tyrosines in the protein. 4th derivative spectra optimized for either tryptophan or tyrosine give a measure of the polarity of the environments of these two aromatic amino acids. Plasminogen at temperatures between 0 °C and 37 °C exists as a mixture of four conformations: closed-relaxed, open-relaxed, closed-compact, and open-compact. The closed to open transition is driven by addition of ligand to a site on the protein. The relaxed to compact transition is driven by increasing temperature from 0 °C to above 15–20 °C. When the conformation of plasminogen is mainly closed-relaxed, the 4th derivative spectra suggest that the average tryptophan environment is similar to a solution of 20% methanol at the same temperature. Under the same conditions, 4th derivative spectra suggest that the average tyrosine environment is similar to water. These apparent polarities change as the plasminogen is forced to assume the other conformations. We try to rationalize the information based on the known portions of the plasminogen structure.
Providing Balanced Throughput and Fairness Using Random Ranks and Mini Slots at MAC Layer in Ad hoc Networks

Ad hoc networks offer infrastructure free operation, where no entity can provide reliable coordination among nodes. Medium Access Control (MAC) protocols in such a network must overcome the inherent unreliability of the network and provide high throughput and adequate fairness to the different flows of traffic. In this paper, we propose a MAC protocol that can achieve an excellent balance between throughput and fairness. Our protocol utilizes control-message handshake similar to IEEE 802.11. The protocol makes use of granule time slots and sequence of pseudo random numbers to maximize spatial reuse and divide the throughput fairly among nodes. We have demonstrated the performance of this protocol using simulation with fixed topologies. Our simulation results include a detailed comparison between the proposed protocol and existing protocol that has been shown to excel in terms of throughput or fairness.
Simulation of metal surfaces secondary electron emission in multipactor

In this paper a numerical simulation of metal surface secondary electron emission is performed by considering scattering models. Based on the scattering models of corresponding electron energy, the characteristics involving with secondary electron emission yield dependence of the incident energy and incident angle, as well as the emitted-energy spectrum are simulated. The simulation results accord with theoretic model and reported results.
Over-the-Counter Markets

We study how intermediation and asset prices in over-the-counter markets are affected by illiquidity associated with search and bargaining. We compute explicitly the prices at which investors trade with each other as well as marketmakers' bid and ask prices in a dynamic model with strategic agents. Bid-ask spreads are lower if investors can more easily find other investors, or have easier access to multiple marketmakers. With a monopolistic marketmaker, bid-ask spreads are higher if investors have easier access to the marketmaker. We characterize endogenous search and welfare, and discuss empirical implications.
Four path following controllers for rhombic like vehicles

This paper addresses the path following problem of a wheeled mobile robot with rhombic like kinematics (two drivable and steerable wheels) operating in cluttered environments. Four path following controllers are developed to steer the kinematic model of a rhombic like vehicle (RLV) along a desired path: three are based on feedback laws derived at a kinematic level with geometrical inspiration; the fourth is a nonlinear controller built upon a kinematic model of the vehicle using Lyapunov functions. By fully exploiting the kinematic capabilities of this type of vehicles, all the developed controllers are capable of performing under two situations: when both wheels follow the same path, or when each wheel follows a different path. Simulated and experimental results are presented in the paper to illustrate the performance of the controllers. The main conclusions of these controllers are summarized, leading to a possible application in the vehicles that will operate in the remote handling missions of the International Thermonuclear Experimental Reactor (ITER).
Epigenetic regulation of human cis-natural antisense transcripts

Mammalian genomes encode numerous cis-natural antisense transcripts (cis-NATs). The extent to which these cis-NATs are actively regulated and ultimately functionally relevant, as opposed to transcriptional noise, remains a matter of debate. To address this issue, we analyzed the chromatin environment and RNA Pol II binding properties of human cis-NAT promoters genome-wide. Cap analysis of gene expression data were used to identify thousands of cis-NAT promoters, and profiles of nine histone modifications and RNA Pol II binding for these promoters in ENCODE cell types were analyzed using chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Active cis-NAT promoters are enriched with activating histone modifications and occupied by RNA Pol II, whereas weak cis-NAT promoters are depleted for both activating modifications and RNA Pol II. The enrichment levels of activating histone modifications and RNA Pol II binding show peaks centered around cis-NAT transcriptional start sites, and the levels of activating histone modifications at cis-NAT promoters are positively correlated with cis-NAT expression levels. Cis-NAT promoters also show highly tissue-specific patterns of expression. These results suggest that human cis-NATs are actively transcribed by the RNA Pol II and that their expression is epigenetically regulated, prerequisites for a functional potential for many of these non-coding RNAs.
Lagrangian Constrained Clustering

Copyright © by SIAM. Incorporating background knowledge in clustering problems has attracted wide interest. This knowledge can be represented as pairwise instance-level constraints. Existing techniques approach satisfaction of such constraints from a soft (discretionary) perspective, yet there exist scenarios for constrained clustering where satisfying as many constraints as possible. We present a new Lagrangian Constrained Clustering framework (LCC) for clustering in the presence of pairwise constraints which gives high priority to satisfying constraints. LCC is an iterative optimization procedure which incorporates dynamic penalties for violated constraints. Experiments show that LCC can outperform existing constrained clustering algorithms in scenarios which satisfying as many constraints as possible.
Potential use of scotta, the by-product of the ricotta cheese manufacturing process, for the production of fermented drinks

In the present work, the use of scotta as substrate for bacterial fermentation was studied with the objective of obtaining a drink from transformation of this by-product. Scotta retains most of the lactose of the milk and it is normally colonized by a natural microbiota. A treatment was devised to reduce the autochthonous microbial populations in order to reduce competition towards the inoculated bacterial strains. Nine lactic acid bacteria (LAB) were assessed for their capability to develop in scotta. They evidenced different behaviors regarding growth rate, acidification capability and nitrogen consumption. A co-inoculum of three LAB, namely a Streptococcus thermophilus, a Lactobacillus delbrueckii subsp. bulgaricus and a Lb. acidophilus strains, chosen among those giving the best performances in single-strain fermentation trials, gave abundant (close to 109 cfu/ml) and balanced growth and lowered pH to 4·2, a value similar to that of yogurt. These results show that scotta may have potential as a substrate for bacterial growth for the production of a fermented drink. Further studies are needed to optimize the organoleptic aspects of the final product.
Disability, discourse and desire: Analyzing online talk by people with disabilities

Fran Vicary, who has had cerebral palsy from birth, recently claimed in the UK newspaper, The Guardian, that most people with a disability seek to express themselves sexually. Arguing from personal experience, she said the expression of sexual desire is a much contested space for those with disabilities because their sexualities and bodies are controlled by broader public discourses that delegitimize and stigmatize their sexual agency and the possibility of pleasure. It is not surprising then that positive and empowering discourses of disability and sexuality are either invisible or missing. Drawing on discourse analysis, the author examines electronic talk by people with disabilities in a disability specific online community website. His analysis shows their rejection of mainstream discourses positioning them as asexual and the deployment of mainstream discourses, which draw on gender, sexuality and intimacy, as well as the circulation of disability-specific sexual pleasure discourses with sex workers and caregivers. The use of social media in expressing marginalized sexual identities is also discussed.
Simulation time analysis of MATLAB/Simulink and LabVIEW for control applications

Nowadays advanced software programs are actively used in the field for simulation and modeling. LabVIEW and MATLAB/Simulink are both graphical programming languages, allowing a more efficient method to perform and analyze control systems. Therefore, they are the most commonly used software programs for these purposes. Moreover; in some applications - like hardware in the loop systems, flight simulations etc. - simulation time can be vital to achieve more realistic simulation. Therefore, in addition to programming style, simulation performance can be affected by used platform's abilities. In this paper both tools' abilities on some of control applications will be presented with benchmark problems and their performances on simulation of control systems will be analyzed and compared.
A PUZZLE INVOLVING GALACTIC BULGE MICROLENSING EVENTS

We study a sample of 16 microlensed Galactic bulge main-sequence turnoff region stars for which high-dispersion spectra have been obtained with detailed abundance analyses. We demonstrate that there is a very strong and highly statistically significant correlation between the maximum magnification of the microlensed bulge star and the value of the [Fe/H] deduced from the high resolution spectrum of each object. Physics demands that this correlation, assuming it to be real, be the result of some sample bias. We suggest several possible explanations, but are forced to reject them all, and are left puzzled. To obtain a reliable metallicity distribution in the Galactic bulge based on microlensed dwarf stars, it will be necessary to resolve this issue through the course of additional observations.
Methodological Issues in the Psychology of Religion: Toward Another Paradigm?

Recent evaluations have identified the psychology of religion as a field in crisis and have called for a new multilevel interdisciplinary paradigm. However, a critical meta-perspective on methods reveals a broad range of methodologies, each appropriate for particular levels of complexity in the psychology of religion. No single methodology is appropriate for every level, nor can higher levels of complexity be explained by data from lower levels. The authors identify the different types of research practiced in the psychology of religion and critically discuss philosophical presuppositions involved in two major methodological traditions, the empiricist-analytical and the hermeneutical, often identified as quantitative and qualitative traditions, respectively.
Differentiation of early hepatocellular carcinoma from benign hepatocellular nodules on gadoxetic acid-enhanced MRI.

OBJECTIVE To test new diagnostic criteria for the discrimination of early hepatocellular carcinoma (HCC) from benign hepatocellular nodules on gadoxetic acid-enhanced MRI (Gd-EOB-MRI). METHODS We retrospectively analysed 34 patients with 29 surgically diagnosed early HCCs and 31 surgically diagnosed benign hepatocellular nodules. Two radiologists reviewed Gd-EOB-MRI, including diffusion-weighted imaging (DWI), and the signal intensity at each sequence, presence of arterial enhancement and washout were recorded. We composed new diagnostic criteria based on the lesion size and MRI findings, and then the diagnostic performance was compared with that of conventional imaging criteria with logistic regression and a generalised estimating equation method. RESULTS A size cut-off value (≥1.5 cm diameter) and MRI findings of T(1) hypointensity, T(2) hyperintensity, DWI hyperintensity on both low and high b-value images (b=50 and 800 s mm(-2), respectively), arterial enhancement, late washout and hepatobiliary hypointensity were selected as the diagnostic criteria. When lesions were considered malignant if they satisfied three or more of the above criteria, the sensitivity was significantly higher than when making a diagnosis based on arterial enhancement and washout alone (58.6% vs 13.8%, respectively; p=0.0002), while the specificity was 100.0% for both criteria. CONCLUSION Our new diagnostic criteria on Gd-EOB-MRI may help to improve the discrimination of early HCC from benign hepatocellular nodules.
Intraperitoneal Injection of Mice

Steward, Ornellas, Beernink, and Northway (2) reported a 14% error in the placement of intraperitoneal injections of mice. They considered this error inherent in the technique and not simply correctable. We similarly found an error in the intraperitoneal injection of mice and attempted to identify the cause of error by varying such technical procedures as size of needle, site of penetration (through lower left versus lower right quadrant), investigator, angle of needle to the abdominal wall, and speed of injection. None of these technical modifications consistently eliminated or reduced the error of placement.
Onset of chaos and its signature in the spectral autocorrelation function.

The signature of chaos in the spectral autocorrelation function and in its Fourier transform, the survival probability, is shown to be in good agreement with the predictions of random matrix theory. An expression is proposed for the survival probability of an experimentally prepared nonstationary state when the dynamics are intermediate between chaotic and regular. Its validity is tested through the study of a model Hamiltonian . Two parameters can be extracted from the above observable, one which characterizes the level statistics and one which characterizes the distribution of transition intensities.
Partial Signatures and their Applications

We introduce Partial Signatures, where a signer, given a message, can compute a “stub” which preserves her anonymity, yet later she, but nobody else, can complete the stub to a full and verifiable signature under her public key. We provide a formal definition requiring three properties, namely anonymity, unambiguity and unforgeability. We provide schemes meeting our definition both with and without random oracles. Our schemes are surprisingly cheap in both bandwidth and computation. We describe applications including anonymous bidding and betting.
MR Image Reconstruction Using a Combination of Compressed Sensing and Partial Fourier Acquisition: ESPReSSo

A Cartesian subsampling scheme is proposed incorporating the idea of PF acquisition and variable-density Poisson Disc (vdPD) subsampling by redistributing the sampling space onto a smaller region aiming to increase k-space sampling density for a given acceleration factor. Especially the normally sparse sampled high-frequency components benefit from this sampling redistribution, leading to improved edge delineation. The prospective subsampled and compacted k-space can be reconstructed by a seamless combination of a CS-algorithm with a Hermitian symmetry constraint accounting for the missing part of the k-space. This subsampling and reconstruction scheme is called Compressed Sensing Partial Subsampling (ESPReSSo) and was tested on in-vivo abdominal MRI datasets. Different reconstruction methods and regularizations are investigated and analyzed via global (intensity-based) and local (region-of-interest and line evaluation) image metrics, to conclude a clinical feasible setup. Results substantiate that ESPReSSo can provide improved edge delineation and regional homogeneity for multidimensional and multi-coil MRI datasets and is therefore useful in applications depending on well-defined tissue boundaries, such as image registration and segmentation or detection of small lesions in clinical diagnostics.
On handling negative transfer and imbalanced distributions in multiple source transfer learning

Transfer learning has benefited many real‐world applications where labeled data are abundant in source domains but scarce in the target domain. As there are usually multiple relevant domains where knowledge can be transferred, multiple source transfer learning (MSTL) has recently attracted much attention. However, we are facing two major challenges when applying MSTL. First, without knowledge about the difference between source and target domains, negative transfer occurs when knowledge is transferred from highly irrelevant sources. Second, existence of imbalanced distributions in classes, where examples in one class dominate, can lead to improper judgement on the source domains' relevance to the target task. Since existing MSTL methods are usually designed to transfer from relevant sources with balanced distributions, they will fail in applications where these two challenges persist. In this article, we propose a novel two‐phase framework to effectively transfer knowledge from multiple sources even when there exists irrelevant sources and imbalanced class distributions. First, an effective supervised local weight scheme is proposed to assign a proper weight to each source domain's classifier based on its ability of predicting accurately on each local region of the target domain. The second phase then learns a classifier for the target domain by solving an optimization problem which concerns both training error minimization and consistency with weighted predictions gained from source domains. A theoretical analysis shows that as the number of source domains increases, the probability that the proposed approach has an error greater than a bound is becoming exponentially small. We further extend the proposed approach to an online processing scenario to conduct transfer learning on continuously arriving data. Extensive experiments on disease prediction, spam filtering and intrusion detection datasets demonstrate that: (i) the proposed two‐phase approach outperforms existing MSTL approaches due to its ability of tackling negative transfer and imbalanced distribution challenges, and (ii) the proposed online approach achieves comparable performance to the offline scheme.
Understanding Similarities in Performance on Different Orientation Tasks: Strategy Adaptation

Spatial orientation is involved in a variety of common tasks, which are often difficult for individuals to perform. In this paper, a model is used to demonstrate that a general strategy may be adapted for use in different spatial orientation tasks. The predictions of the model, which was adapted from a model for another orientation task, closely match human performance on the target task. More importantly, the model provides insights into how individuals solve these sorts of tasks, and supports the conclusion that similar strategies can be adapted and used in different tasks.
On the Vertigo Due to Static Magnetic Fields

Vertigo is sometimes experienced in and around MRI scanners. Mechanisms involving stimulation of the vestibular system by movement in magnetic fields or magnetic field spatial gradients have been proposed. However, it was recently shown that vestibular-dependent ocular nystagmus is evoked when stationary in homogenous static magnetic fields. The proposed mechanism involves Lorentz forces acting on endolymph to deflect semicircular canal (SCC) cupulae. To investigate whether vertigo arises from a similar mechanism we recorded qualitative and quantitative aspects of vertigo and 2D eye movements from supine healthy adults (n = 25) deprived of vision while pushed into the 7T static field of an MRI scanner. Exposures were variable and included up to 135s stationary at 7T. Nystagmus was mainly horizontal, persisted during long-exposures with partial decline, and reversed upon withdrawal. The dominant vertiginous perception with the head facing up was rotation in the horizontal plane (85% incidence) with a consistent direction across participants. With the head turned 90 degrees in yaw the perception did not transform into equivalent vertical plane rotation, indicating a context-dependency of the perception. During long exposures, illusory rotation lasted on average 50 s, including 42 s whilst stationary at 7T. Upon withdrawal, perception re-emerged and reversed, lasting on average 30 s. Onset fields for nystagmus and perception were significantly correlated (p<.05). Although perception did not persist as long as nystagmus, this is a known feature of continuous SSC stimulation. These observations, and others in the paper, are compatible with magnetic-field evoked-vertigo and nystagmus sharing a common mechanism. With this interpretation, response decay and reversal upon withdrawal from the field, are due to adaptation to continuous vestibular input. Although the study does not entirely exclude the possibility of mechanisms involving transient vestibular stimulation during movement in and out of the bore, we argue these are less likely.
QDrill: Query-Based Distributed Consumable Analytics for Big Data

Consumable analytics attempt to address the shortage of skilled data analysts in many organizations by offering analytic functionality in a form more familiar to in-house expertise. Providing consumable analytics for Big Data faces three main challenges. The first challenge is making the analytics algorithms run in a distributed fashion in order to analyze Big Data in a timely manner. The second challenge is providing an easy interface to allow in-house expertise to run these algorithms in a distributed fashion while minimizing the learning cycle and existing code rewrites. The third challenge is running the analytics on data of different formats stored on heterogeneous data stores. In this paper, we address these challenges in the proposed QDrill. We introduce the Analytics Adaptor extension for Apache Drill, a schema-free SQL query engine for non-relational storage. The Analytics Adaptor introduces the Distributed Analytics Query Language for invoking data mining algorithms from within the Drill standard SQL query statements. The adaptor allows using any sequential single-node data mining library (e.g. WEKA) and makes its algorithms run in a distributed fashion without having to rewrite them. We evaluate QDrill against Apache Mahout. The evaluation shows that QDrill outperforms Mahout in Updatable model training and scoring phase while almost keeping the same performance for Non-Updatable model training. QDrill is more scalable and offers an easier interface, no storage overhead and the whole algorithms repository of WEKA, with the ability to extend to use algorithms from other data mining libraries.