Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized infection and lack of delayed hypersensitivity in BALB/c mice infected with Leishmania tropica major

The susceptibility of a few strains of mice to a subcutaneous injection of Leishmania tropica major, the causative agent of cutaneous leishmaniasis in humans, was studied. The infection in six strains (CBA, AKR/J, AKR/cu, C57BL/6, A/J, and C3H) remained cutaneous, and the animals recovered within 3 to 4 months. In contast, the infection in BALB/c became generalized and killed 1005 of infected animals. Intraperitoneal injection of infected liver of BALB/c to A/J and syngeneic mice produced a lethal disease in BALB/c but no infection in A/J mice. Lower doses of the parasite produced a lethal infection in BALB/c but no apparent disease in A/J. Hence, the host rather than the parasite is responsible for the outcome of the disease. The peak antibody titer of BALB/c mice was not significantly higher than that of A/J mice. However, BALB/c failed to show any delayed hypersensitivity to leishmania tested by footpad reaction, whereas A/J mice showed a strong response.
Linear and non-linear indices of heart rate variability in chronic heart failure: mutual interrelationships and prognostic value

We computed 3 linear and 20 nonlinear HRV indexes on 24-h Holter recordings from 200 stable CHF patients (age 52plusmn9 yrs, NYHA II-III, LVEF 24plusmn6%) with the aim to assess i) the mutual interrelationships between these indexes and ii) their prognostic value towards cardiac death. We found high correlations between variables, with potential bias in fitting survival models. To overcome this problem a clustering procedure was used, obtaining 11 clusters. Cox analysis showed that seven clusters were significantly associated with the study outcome (p<0.05) but, after adjustment for major clinical prognostic parameters, significance persisted only in 2 of them (both composed by nonlinear variables). Our results indicate that composite scores derived from nonlinear indices contain significant prognostic information independent of classical clinical predictors, highlighting the importance of non linear HRV parameters in prognostic stratification of CHF patients
Valuing a Change in a Fishing Site Without Collecting Characteristics Data on All Fishing Sites: A Complete But Minimal Model

Resource economists are often asked to value a proposed change at one, and only one, recreational site; the model we develop and estimate is applicable for those cases. The application is valuing the elimination of fish consumption advisories on a large bay on Lake Michigan. The model is minimal but complete: complete in that the choice set is not restricted, minimal in that only two conditional indirect utility functions are estimated. It is utility-theoretic and one does not have to collect characteristic data on all of the other fishing sites in the region. Data include the number of trips each individual currently takes to Green Bay, answers to “would you prefer to fish Green Bay under conditions A or B? ” and how often each angler says they would fish Green Bay under different sets of conditions. Copyright 2006, Oxford University Press.
Massive calcium–activated endocytosis without involvement of classical endocytic proteins

We describe rapid massive endocytosis (MEND) of >50% of the plasmalemma in baby hamster kidney (BHK) and HEK293 cells in response to large Ca transients. Constitutively expressed Na/Ca exchangers (NCX1) are used to generate Ca transients, whereas capacitance recording and a membrane tracer dye, FM 4–64, are used to monitor endocytosis. With high cytoplasmic adenosine triphosphate (ATP; >5 mM), Ca influx causes exocytosis followed by MEND. Without ATP, Ca transients cause only exocytosis. MEND can then be initiated by pipette perfusion of ATP, and multiple results indicate that ATP acts via phosphatidylinositol-bis 4,5-phosphate (PIP2) synthesis: PIP2 substitutes for ATP to induce MEND. ATP-activated MEND is blocked by an inositol 5-phosphatase and by guanosine 5′-[γ-thio]triphosphate (GTPγS). Block by GTPγS is overcome by the phospholipase C inhibitor, U73122, and PIP2 induces MEND in the presence of GTPγS. MEND can occur in the absence of ATP and PIP2 when cytoplasmic free Ca is clamped to 10 µM or more by Ca-buffered solutions. ATP-independent MEND occurs within seconds during Ca transients when cytoplasmic solutions contain polyamines (e.g., spermidine) or the membrane is enriched in cholesterol. Although PIP2 and cholesterol can induce MEND minutes after Ca transients have subsided, polyamines must be present during Ca transients. MEND can reverse over minutes in an ATP-dependent fashion. It is blocked by brief β-methylcyclodextrin treatments, and tests for involvement of clathrin, dynamins, calcineurin, and actin cytoskeleton were negative. Therefore, we turned to the roles of lipids. Bacterial sphingomyelinases (SMases) cause similar MEND responses within seconds, suggesting that ceramide may be important. However, Ca-activated MEND is not blocked by reagents that inhibit SMases. MEND is abolished by the alkylating phospholipase A2 inhibitor, bromoenol lactone, whereas exocytosis remains robust, and Ca influx causes MEND in cardiac myocytes without preceding exocytosis. Thus, exocytosis is not prerequisite for MEND. From these results and two companion studies, we suggest that Ca promotes the formation of membrane domains that spontaneously vesiculate to the cytoplasmic side.
Optimal design of generalized lapped orthogonal transforms: multiobjective optimization techniques and experimental results

We explore multiobjective optimization techniques for the design of generalized lapped orthogonal transforms (GenLOTs). The design objectives handled are the coding gain, the stopband attenuation and the DC leakage. As the optimization algorithm, the pattern search method is used and also as the multiobjective optimization method, the weighted linear combination (WLC) and minmax methods are handled. Some techniques and findings to obtain good optima by these methods are presented. The experimental results show the following. The pattern search method with the strategy for selecting the starting point and the method for assigning the frequency slot has a capability to yield good optima. The WLC and minmax methods have a capability to yield various good optima by varying the relative magnitude of each weight. There is a good possibility that the solution by the pattern search method is one of the global optima in some cases.
Monocular navigation for long-term autonomy

We present a reliable and robust monocular navigation system for an autonomous vehicle. The proposed method is computationally efficient, needs off-the-shelf equipment only and does not require any additional infrastructure like radio beacons or GPS. Contrary to traditional localization algorithms, which use advanced mathematical methods to determine vehicle position, our method uses a more practical approach. In our case, an image-feature-based monocular vision technique determines only the heading of the vehicle while the vehicle's odometry is used to estimate the distance traveled. We present a mathematical proof and experimental evidence indicating that the localization error of a robot guided by this principle is bound. The experiments demonstrate that the method can cope with variable illumination, lighting deficiency and both short- and long-term environment changes. This makes the method especially suitable for deployment in scenarios which require long-term autonomous operation.
Employing a fiber-based finite-length plastic hinge model for representing the cyclic and seismic behaviour of hollow steel columns

Numerical simulations are prevalently used to evaluate the seismic behaviour of structures. The accuracy of the simulation results depends directly on the accuracy of the modelling techniques employed to simulate the behaviour of individual structural members. An empirical modelling technique is employed in this paper to simulate the behaviour of column members under cyclic and seismic loading. Despite the common modelling techniques, this technique is capable of simulating two important aspects of the cyclic and seismic behaviour of columns simultaneously. The proposed fiber-based modelling technique captures explicitly the interaction between the bending moment and the axial force in columns, and the cyclic deterioration of the hysteretic behaviour of these members is implicitly taken into account. The fiber-based model is calibrated based on the cyclic behaviour of square hollow steel sections. The behaviour of several column archetypes is investigated under a dual cyclic loading protocol to develop a benchmark database before the calibration procedure. The dual loading protocol used in this study consists of both axial and lateral loading cycles with varying amplitudes. After the calibration procedure, a regression analysis is conducted to derive an equation for predicting a varying calibrated modelling parameter. Finally, several nonlinear time-history analyses are conducted on a 6-story steel special moment frame in order to investigate how the results of numerical simulations can be affected by employing the intended modelling technique for columns instead of other common modelling techniques.
Fast prediction and evaluation of gravitational waveforms using surrogate models

We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced order model in both parameter and physical dimensions that can be used as a surrogate for the true or fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant that is built for the fiducial waveform family. Third, a fit in the parameter dimension is performed for the waveform’s value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order O(mL+mc_(fit)) online operations, where c_(fit) denotes the fitting function operation count and, typically, m≪L. The result is a compact, computationally efficient, and accurate surrogate model that retains the original physics of the fiducial waveform family while also being fast to evaluate. We generate accurate surrogate models for effective-one-body waveforms of nonspinning binary black hole coalescences with durations as long as 10^5M, mass ratios from 1 to 10, and for multiple spherical harmonic modes. We find that these surrogates are more than 3 orders of magnitude faster to evaluate as compared to the cost of generating effective-one-body waveforms in standard ways. Surrogate model building for other waveform families and models follows the same steps and has the same low computational online scaling cost. For expensive numerical simulations of binary black hole coalescences, we thus anticipate extremely large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy. Surrogates built in this paper, as well as others, are available from GWSurrogate, a publicly available python package.
Micro Ethanol Sensors with a Heater Fabricated Using the Commercial 0.18 μm CMOS Process

The study investigates the fabrication and characterization of an ethanol microsensor equipped with a heater. The ethanol sensor is manufactured using the commercial 0.18 μm complementary metal oxide semiconductor (CMOS) process. The sensor consists of a sensitive film, a heater and interdigitated electrodes. The sensitive film is zinc oxide prepared by the sol-gel method, and it is coated on the interdigitated electrodes. The heater is located under the interdigitated electrodes, and it is used to supply a working temperature to the sensitive film. The sensor needs a post-processing step to remove the sacrificial oxide layer, and to coat zinc oxide on the interdigitated electrodes. When the sensitive film senses ethanol gas, the resistance of the sensor generates a change. An inverting amplifier circuit is utilized to convert the resistance variation of the sensor into the output voltage. Experiments show that the sensitivity of the ethanol sensor is 0.35 mV/ppm.
Hospital Variation in Survival After Pediatric In-Hospital Cardiac Arrest

Background—Although survival after in-hospital cardiac arrest is likely to vary among hospitals caring for children, validated methods to risk-standardize pediatric survival rates across sites do not currently exist. Methods and Results—From 2006 to 2010, within the American Heart Association’s Get With the Guidelines-Resuscitation registry for in-hospital cardiac arrest, we identified 1551 cardiac arrests in children (<18 years). Using multivariable hierarchical logistic regression, we developed and validated a model to predict survival to hospital discharge and calculated risk-standardized rates of cardiac arrest survival for hospitals with a minimum of 10 pediatric cardiac arrest cases. A total of 13 patient-level predictors were identified: age, sex, cardiac arrest rhythm, location of arrest, mechanical ventilation, acute nonstroke neurological event, major trauma, hypotension, metabolic or electrolyte abnormalities, renal insufficiency, sepsis, illness category, and need for intravenous vasoactive agents prior to the arrest. The model had good discrimination (C-statistic of 0.71), confirmed by bootstrap validation (validation C-statistic of 0.69). Among 30 hospitals with ≥10 cardiac arrests, unadjusted hospital survival rates varied considerably (median, 37%; interquartile range, 24–42%; range, 0–61%). After risk-standardization, the range of hospital survival rates narrowed (median, 37%; interquartile range, 33–38%; range, 29–48%), but variation in survival persisted. Conclusions—Using a national registry, we developed and validated a model to predict survival after in-hospital cardiac arrest in children. After risk-standardization, significant variation in survival rates across hospitals remained. Leveraging these models, future studies can identify best practices at high-performing hospitals to improve survival outcomes for pediatric cardiac arrest.
Feasibility study of a wearable carbon monoxide warning system for construction workers

This paper presents a feasibility study of a wearable computing system to protect construction workers from carbon monoxide poisoning. A pulse oximetry sensor has been integrated into a typical construction helmet to allow continuous and non-invasive monitoring of workers' blood saturation levels. To show the feasibility of monitoring for carbon monoxide poisoning without subjecting users to dangerous conditions, a prototype for monitoring blood O2 was constructed and tested during a user study involving typical construction tasks to determine its reliability while undergoing motion. Because monitoring for blood O2 and CO involve the same principles and technologies, if monitoring O2 is feasible, then monitoring for CO will be feasible as well. The results of this initial study show that integrating an oximeter into a construction helmet will warn the user of impeding carbon monoxide poisoning with a probability greater than 99%.
Simultaneous Quantification of Cells and Nanomaterials by Inductive-Coupled Plasma Techniques

We demonstrate that endogenous cellular magnesium levels can be used as an accurate determinant of total cell number by inductively coupled plasma techniques, increasing the throughput and reproducibility of nanoparticle-uptake studies. Uptake of either gold nanoparticles or quantum dots did not affect intracellular concentration of Mg. To demonstrate this technique, we show the decreased uptake of nano-urchins in A549 cells compared with gold nanospheres.
FaceTime — Deep learning based face recognition attendance system

In the interest of recent accomplishments in the development of deep convolutional neural networks (CNNs) for face detection and recognition tasks, a new deep learning based face recognition attendance system is proposed in this paper. The entire process of developing a face recognition model is described in detail. This model is composed of several essential steps developed using today's most advanced techniques: CNN cascade for face detection and CNN for generating face embeddings. The primary goal of this research was the practical employment of these state-of-the-art deep learning approaches for face recognition tasks. Due to the fact that CNNs achieve the best results for larger datasets, which is not the case in production environment, the main challenge was applying these methods on smaller datasets. A new approach for image augmentation for face recognition tasks is proposed. The overall accuracy was 95.02% on a small dataset of the original face images of employees in the real-time environment. The proposed face recognition model could be integrated in another system with or without some minor alternations as a supporting or a main component for monitoring purposes.
Learning Paraphrases from WNS Corpora

Paraphrase detection can be seen as the task of aligning sentences that convey the same information but yet are written in different forms. Such resources are important to automatically learn text-to-text rewriting rules. In this paper, we present a new metric for unsupervised detection of paraphrases and apply it in the context of clustering of paraphrases. An exhaustive evaluation is conducted over a set of standard paraphrase corpora and real-world web news stories (WNS) corpora. The results are promising as they outperform state-of-the-art measures developed for similar tasks.
A Study of Third-Party Tracking by Mobile Apps in the Wild

We report the first field study of real-world tracking via mobile apps in which we measured how 20 participants were tracked over three weeks as they exercised their Android smartphone apps. We instrumented the phones with dynamic taint tracking to record communications that exposed identifying information, and inspected web cookie databases. We find that 36% of the sites (655 out of 1824) that our study apps are programmed to contact are tracking users. Of these sites, 37% track users with persistent identifiers (mostly AndroidId and IMEI) derived from an identifying string unique to the user’s device. This is privacy risk as these IDs are long-lived and enable cross-application and cross-site profiling of the user; they are often sent without encryption and with geo-location too. Advertising and analytics services are widely used, being embedded in 57% of apps and tracking every single participant in our study. Most of these sites are heavy trackers: 25% of their tracking is done with persistent identifiers and geo-location is gathered by half of the top 10 advertisers. To one participant’s surprise, over 600 geocoordinates were exposed to a third-party advertising site during the study. Our participants expected to be tracked but wanted greater transparency and the ability to opt out in cases when there was no perceived value. To let them opt out, we prototype a privacy control that selectively shadows access to identifiers and other sensitive personal data by third-party components.
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation

In this paper, we present an analysis of feature extraction methods via dimensionality reduction for the task of biomedical Word Sense Disambiguation (WSD). We modify the vector representations in the 2-MRD WSD algorithm, and evaluate four dimensionality reduction methods: Word Embeddings using Continuous Bag of Words and Skip Gram, Singular Value Decomposition (SVD), and Principal Component Analysis (PCA). We also evaluate the effects of vector size on the performance of each of these methods. Results are evaluated on five standard evaluation datasets (Abbrev.100, Abbrev.200, Abbrev.300, NLM-WSD, and MSH-WSD). We find that vector sizes of 100 are sufficient for all techniques except SVD, for which a vector size of 1500 is referred. We also show that SVD performs on par with Word Embeddings for all but one dataset.
Graph regularized non-negative local coordinate factorization with pairwise constraints for image representation

Chen et al. proposed a non-negative local coordinate factorization algorithm for feature extraction (NLCF) [1], which incorporated the local coordinate constraint into non-negative matrix factorization (NMF). However, NLCF is actually a unsupervised method without making use of prior information of problems in hand. In this paper, we propose a novel graph regularized non-negative local coordinate factorization with pairwise constraints algorithm (PCGNLCF) for image representation. PCGNLCF incorporates pairwise constraints and graph Laplacian into NLCF. More specifically, we expect that data points having pairwise must-link constraints will have the similar coordinates as much as possible, while data points with pairwise cannot-link constraints will have distinct coordinates as much as possible. Experimental results show the effectiveness of our proposed method in comparison to the state-of-the-art algorithms on several real-world applications.
The Flat-Spectrum Radio Luminosity Function, Gravitational Lensing, Galaxy Ellipticities, and Cosmology

The number of lenses found in the JVAS survey of flat-spectrum radio sources for gravitational lenses is consistent with statistical models of optical surveys for lensed quasars. The 90% confidence limit on Ω0 in flat cosmological models (Ω0 + λ0 = 1) is approximately 0.15 ≲ Ω0 ≲ 2. Depending on the RLF model, we predict 2.40-3.6 lenses in the JVAS survey and in the first paper part of the fainter CLASS survey and 0.3-:0.6 lenses in the brighter PHFS survey for an Ω0 = 1 model. The uncertainties are because of the small numbers of lenses (there are only 4 compact JVAS lenses) and the uncertainties in the radio luminosity function (RLF) caused by the lack of information on the redshift distribution of 10-300 mJy radio sources. If we force the models to produce the observed number of JVAS lenses, the mean redshift of a 50 mJy source varies from zs = 0.4 for Ω0 = 0, to 1.9 for Ω0 = 1, to almost 4.0 for Ω0 = 2 when Ω0+ λ0 = 1. The source fluxes and redshifts of the lenses in the JVAS and CLASS surveys are consistent with the statistical models. The numbers of four-image lenses found in the JVAS survey and in surveys for lensed quasars are mutually consistent but slightly larger than expected for models using the observed axis ratios of E and S0 galaxies. The best fits to the lens data require a projected axis ratio of b/a = 0.50 with a 90% confidence range of 0.25 < b/a < 0.65.