Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive electronic biopsy for 3D virtual colonscopy

We propose an interactive electronic biopsy technique for more accurate colon cancer diagnoses by using advanced volume rendering technologies. The volume rendering technique defines a transfer function to map different ranges of sample values of the original volume data to different colors and opacities, so that the interior structure of the polyps can be clearly recognized by human eyes. Specifically, we provide a user- friendly interface for physicians to modify various parameters in the transfer function, so that the physician can interactively change the transfer function to observe the interior structures inside the abnormalities. Furthermore, to speed up the volume rendering procedure, we propose an efficient space-leaping technique by observing that the virtual camera parameters are often fixed when the physician modifies the transfer function. In addition, we provide an important tool to display the original 2D CT image at the current 3D camera position, so that the physician is able to double check the interior structure of a polyp with the density variation in the corresponding CT image for confirmation. Compared with the traditional biopsy in the procedure of optical colonoscopy, our method is more flexible, noninvasive, and therefore without risk.
Modeling Security Vulnerabilities: A Constraints and Assumptions Perspective

Preventing exploits from compromising software applications requires a fundamental understanding of how they are being exploited, and then leveraging that understanding in the formulation of tests that reveal software application vulnerabilities. To advance that understanding this paper first presents a process/object model of computation that establishes a relationship between software vulnerabilities, an executing process, and computer system resources such as memory, input/output, and cryptographic resources. That relationship promotes the concept that a software application is vulnerable to exploits when it violates (a) constraints imposed by computer system resources or (b) assumptions made about the usage of those resources. Secondly, the process/object model also serves as a foundation for the definition of a taxonomy of vulnerabilities. That is, the computer system resources (or objects) identified in the process/object model form the categories and refined subcategories of the taxonomy. Vulnerabilities, which are expressed in the form of constraints and assumptions, are classified within the taxonomy according to these categories and subcategories. This taxonomy of vulnerabilities is novel and distinctively different from other taxonomies found in literature, and is also outlined in this paper
Microfabricated Formaldehyde Gas Sensors

Formaldehyde is a volatile organic compound that is widely used in textiles, paper, wood composites, and household materials. Formaldehyde will continuously outgas from manufactured wood products such as furniture, with adverse health effects resulting from prolonged low-level exposure. New, microfabricated sensors for formaldehyde have been developed to meet the need for portable, low-power gas detection. This paper reviews recent work including silicon microhotplates for metal oxide-based detection, enzyme-based electrochemical sensors, and nanowire-based sensors. This paper also investigates the promise of polymer-based sensors for low-temperature, low-power operation.
Automatically Constructing a Lexicon of Verb Phrase Idiomatic Combinations

We investigate the lexical and syntactic flexibility of a class of idiomatic expressions. We develop measures that draw on such linguistic properties, and demonstrate that these statistical, corpus-based measures can be successfully used for distinguishing idiomatic combinations from non-idiomatic ones. We also propose a means for automatically determining which syntactic forms a particular idiom can appear in, and hence should be included in its lexical representation.
Inter-Network Cooperation Exploiting Game Theory and Bayesian Networks

Relay sharing has been recently investigated to increase the performance of coexisting wireless multi-hop networks. In this paper, we analyze a scenario where two wireless ad hoc networks are willing to share some of their nodes, acting as relays, in order to gain benefits in terms of lower packet delivery delay and reduced loss probability. Bayesian network analysis is exploited to compute the probabilistic relationships between local parameters and overall performance, whereas the selection of the nodes to share is made by means of a game theoretic approach. Our results are then validated through the use of a system level simulator, which shows that an accurate selection of the shared nodes can significantly increase the performance gain with respect to a random selection scheme.
Practical Approach in Developing Desirable Peel–Seal and Clear Lidding Films Based on Poly(Lactic Acid) and Poly(Butylene Adipate‐Co‐Terephthalate) Blends

In this research, poly(lactic acid) (PLA) blend with poly(butylene adipate‐co‐terephthalate) (PBAT) were selected to fabricate peelable lidding films. In general, blending PLA with PBAT results in hazy films; however, desirable low haze films (<10%) could be achieved in this study by designing proper blend composition and cast film process under optimum conditions. Based on various blends containing PBAT ranging from 15 to 30% by weight, it could be seen that a PBAT/PLA blend of 20/80 showed desired optical and peel–seal property, which had a haze of <10% and low peel strength in an easy‐peel characteristic. It was also observed that not only the blend composition but also the film thickness could influence both optical and peel–seal behaviours because the bulk morphology and surface irregularities of the films could vary by changing films' thicknesses. Thus, cast extruded pristine and PBAT/PLA (20/80) blend films of three different thicknesses (20, 35 and 50 μm) were studied. Peel–seal behaviour and optical properties of these films were examined. An I‐peel test (180°) of films sealed on PLA sheet (thickness of ~350 μm) with different interfacial sealing temperature illustrated failure mechanism of four types, i.e. tearing, partial tearing, cohesive and adhesive failure. Based on this study, the PBAT/PLA of 20/80 wt% films with thickness of 20 μm can be used as easy‐peel lidding film sealed with PLA container. Such PBAT/PLA blend films possess a low haze of ~4% and a low peel strength of 8–10 N/15 mm at a broad range of interfacial sealing temperature of 76–105°C. Copyright © 2017 John Wiley & Sons, Ltd.
Social roles in hierarchical models for human activity recognition

We present a hierarchical model for human activity recognition in entire multi-person scenes. Our model describes human behaviour at multiple levels of detail, ranging from low-level actions through to high-level events. We also include a model of social roles, the expected behaviours of certain people, or groups of people, in a scene. The hierarchical model includes these varied representations, and various forms of interactions between people present in a scene. The model is trained in a discriminative max-margin framework. Experimental results demonstrate that this model can improve performance at all considered levels of detail, on two challenging datasets.
Gain dependence of measured spectra in coherent Brillouin optical time-domain analysis sensors

We report on the effects of large pump pulse powers on Brillouin optical time-domain analysis (BOTDA) sensors based on phase-modulated probe wave and coherent detection. It is found that the large Brillouin gain that comes from the use of high power pulses induces a narrowing of the RF phase-shift spectrum that is measured in these sensors. This narrowing leads to a Brillouin frequency shift measurement error when the sensor is configured for dynamic measurements. However, the effect has been found to be less significant than that observed in dynamic slope-assisted BOTDA sensors based on amplitude.
From visual words to a visual grammar: using language modelling for image classification

The Bag--of--Visual--Words (BoVW) is a visual description technique that aims at shortening the semantic gap by partitioning a low--level feature space into regions of the feature space that potentially correspond to visual concepts and by giving more value to this space. In this paper we present a conceptual analysis of three major properties of language grammar and how they can be adapted to the computer vision and image understanding domain based on the bag of visual words paradigm. Evaluation of the visual grammar shows that a positive impact on classification accuracy and/or descriptor size is obtained when the technique are applied when the proposed techniques are applied.
Faces in the mist: illusory face and letter detection

We report three behavioral experiments on the spatial characteristics evoking illusory face and letter detection. False detections made to pure noise images were analyzed using a modified reverse correlation method in which hundreds of observers rated a modest number of noise images (480) during a single session. This method was originally developed for brain imaging research, and has been used in a number of fMRI publications, but this is the first report of the behavioral classification images. In Experiment 1 illusory face detection occurred in response to scattered dark patches throughout the images, with a bias to the left visual field. This occurred despite the use of a fixation cross and expectations that faces would be centered. In contrast, illusory letter detection (Experiment 2) occurred in response to centrally positioned dark patches. Experiment 3 included an oval in all displays to spatially constrain illusory face detection. With the addition of this oval the classification image revealed an eyes/nose/mouth pattern. These results suggest that face detection is triggered by a minimal face-like pattern even when these features are not centered in visual focus.
ComputerScience 1-1-2008 OptRR : Optimizing Randomized Response Schemes for Privacy-Preserving Data Mining

The randomized response (RR) technique is a promising technique to disguise private categorical data in Privacy-Preserving Data Mining (PPDM). Although a number of RR-based methods have been proposed for various data mining computations, no study has systematically compared them to find optimal RR schemes. The difficulty of comparison lies in the fact that to compare two PPDM schemes, one needs to consider two conflicting metrics: privacy and utility. An optimal scheme based on one metric is usually the worst based on the other metric. In this paper, we first describe a method to quantify privacy and utility. We formulate the quantification as estimate problems, and use estimate theories to derive quantification. We then use an evolutionary multi-objective optimization method to find optimal disguise matrices for the randomized response technique. The experimental results have shown that our scheme has a much better performance than the existing RR schemes.
Peer Reviewed Title: Identifying patients with diabetes and the earliest date of diagnosis in real time: an electronic health record case-finding algorithm

Abstract Background Effective population management of patients with diabetes requires timely recognition. Current case-finding algorithms can accurately detect patients with diabetes, but lack real-time identification. We sought to develop and validate an automated, real-time diabetes case-finding algorithm to identify patients with diabetes at the earliest possible date. Methods The source population included 160,872 unique patients from a large public hospital system between January 2009 and April 2011. A diabetes case-finding algorithm was iteratively derived using chart review and subsequently validated (n = 343) in a stratified random sample of patients, using data extracted from the electronic health records (EHR). A point-based algorithm using encounter diagnoses, clinical history, pharmacy data, and laboratory results was used to identify diabetes cases. The date when accumulated points reached a specified threshold equated to the diagnosis date. Physician chart review served as the gold standard. Results The electronic model had a sensitivity of 97%, specificity of 90%, positive predictive value of 90%, and negative predictive value of 96% for the identification of patients with diabetes. The kappa score
Effect of Manure vs. Fertilizer Inputs on Productivity of Forage Crop Models

Manure produced by livestock activity is a dangerous product capable of causing serious environmental pollution. Agronomic management practices on the use of manure may transform the target from a waste to a resource product. Experiments performed on comparison of manure with standard chemical fertilizers (CF) were studied under a double cropping per year regime (alfalfa, model I; Italian ryegrass-corn, model II; barley-seed sorghum, model III; and horse-bean-silage sorghum, model IV). The total amount of manure applied in the annual forage crops of the model II, III and IV was 158, 140 and 80 m3 ha−1, respectively. The manure applied to soil by broadcast and injection procedure provides an amount of nitrogen equal to that supplied by CF. The effect of manure applications on animal feeding production and biochemical soil characteristics was related to the models. The weather condition and manures and CF showed small interaction among treatments. The number of MFU ha−1 of biomass crop gross product produced in autumn and spring sowing models under manure applications was 11,769, 20,525, 11,342, 21,397 in models I through IV, respectively. The reduction of MFU ha−1 under CF ranges from 10.7% to 13.2% those of the manure models. The effect of manure on organic carbon and total nitrogen of topsoil, compared to model I, stressed the parameters as CF whose amount was higher in models II and III than model IV. In term of percentage the organic carbon and total nitrogen of model I and treatment with manure was reduced by about 18.5 and 21.9% in model II and model III and 8.8 and 6.3% in model IV, respectively. Manure management may substitute CF without reducing gross production and sustainability of cropping systems, thus allowing the opportunity to recycle the waste product for animal forage feeding.
Eulerian solids for soft tissue and more

This course focuses on the use of Eulerian solids to simulate muscles, tendons and other highly constrained mechanical and biomechanical systems. We aim to give the reader both a theoretical and practical introduction to the Eulerian solids methodology by focusing on relevant applications in physically based animation. Eulerian methods have many advantages over standard techniques: First, they can simulate highly deformable objects without resorting to complicated remeshing operations. Furthermore they can handle sliding and conforming contact efficiently as well as trivially simulate volumetric data. This makes them useful for simulating a wide class of elastic solids undergoing bilateral or unilateral constraints and particularly well-suited for muscles, tendons and other tissues. As such, the addition of Eulerian solids to the graphics practitioner’s arsenal greatly extends the types of physically based animation that can be created. This course is targeted at researchers and developers of physical simulation software. We assume some familiarity with standard finite element methods as well as rigid body dynamics. Our goals are to review the Eulerian solids formulation and to demonstrate how it can be used to simulate 1-, 2and 3-D elastoplastic solids. We will also detail how the method can be combined with existing simulation techniques to improve robustness and to add detail to animations. This course will feature many practical examples of Eulerian solids in action with a focus on biomechanical applications. At the conclusion of the course, attendees will have a full working knowledge of the Eulerian solids methodology.
Co-morbidity of depression and anxiety in common age-related eye diseases: a population-based study of 662 adults

This study examined the prevalence of co-morbid age-related eye disease and symptoms of depression and anxiety in late life, and the relative roles of visual function and disease in explaining symptoms of depression and anxiety. A community-based sample of 662 individuals aged over 70 years was recruited through the electoral roll. Vision was measured using a battery of tests including high and low contrast visual acuity, contrast sensitivity, motion sensitivity, stereoacuity, Useful Field of View, and visual fields. Depression and anxiety symptoms were measured using the Goldberg scales. The prevalence of self-reported eye disease [cataract, glaucoma, or age-related macular degeneration (AMD)] in the sample was 43.4%, with 7.7% reporting more than one form of ocular pathology. Of those with no eye disease, 3.7% had clinically significant depressive symptoms. This rate was 6.7% among cataract patients, 4.3% among those with glaucoma, and 10.5% for AMD. Generalized linear models adjusting for demographics, general health, treatment, and disability examined self-reported eye disease and visual function as correlates of depression and anxiety. Depressive symptoms were associated with cataract only, AMD, comorbid eye diseases and reduced low contrast visual acuity. Anxiety was significantly associated with self-reported cataract, and reduced low contrast visual acuity, motion sensitivity and contrast sensitivity. We found no evidence for elevated rates of depressive or anxiety symptoms associated with self-reported glaucoma. The results support previous findings of high rates of depression and anxiety in cataract and AMD, and in addition show that mood and anxiety are associated with objective measures of visual function independently of self-reported eye disease. The findings have implications for the assessment and treatment of mental health in the context of late-life visual impairment.
Fixed points of quantum gravity in higher dimensions

We study quantum gravity in more than four dimensions by means of an exact functional flow. A non‐trivial ultraviolet fixed point is found in the Einstein‐Hilbert theory. It is shown that our results for the fixed point and universal scaling exponents are stable. If the fixed point persists in extended truncations, quantum gravity in the metric field is asymptotically safe. We indicate physical consequences of this scenario in phenomenological models with low‐scale quantum gravity and large extra dimensions.
Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.
Wavelet Transforms Generated by splines

In this paper, we design a new family of biorthogonal wavelet transforms that are based on polynomial and discrete splines. The wavelet transforms are constructed via lifting steps, where the prediction and update filters are derived from various types of interpolatory and quasi-interpolatory splines. The transforms use finite and infinite impulse response (IIR) filters and are implemented in a fast lifting mode. We analyze properties of the generated scaling functions and wavelets. In the case when the prediction filter is derived from a polynomial interpolatory spline of even order, the synthesis scaling function and wavelet are splines of the same order. We formulate conditions for the IIR filter to generate an exponentially decaying scaling function.
Concentration Measurements in a Water Model Tundish using the Combined DPIV/PLIF Technique

The mixing process in a 1:3 scaled water model of a single‐strand tundish for the production of stainless steel is investigated using the combined DPIV/PLIF (Digital Particle Image Velocimetry/Planar Laser Induced Fluorescence) technique. The velocities in the water model are measured in different light sheet planes up to a size of 300 mm · 1100 mm by the conventional DPIV method. The variation of the time‐dependent concentration field is measured in the same plane by the PLIF method. The tracers are polyamide particles for DPIV and a rhodamine 6G solution as fluorescent dye for PLIF. Due to the special calibration procedure of the DPIV/PLIF system, the optical, geometrical and physical parameters do not have to be determined analytically, thus leading to reliable results. The experiments are carried out with a turbulent Reynolds number of Re = 5000 and show that the mixing process correlates with the quasi steady‐state flow pattern. The residence time of some water region in the tundish model is significantly longer than the mean residence time (θ < 5). Such information is important for the steel production because the number of mixed slabs produced during sequence casting with a grade change is closely related to the mixing of the tundish melt. The presented laser‐optical investigations have been used to establish the combination of DPIV and PLIF technique. The results of combined DPIV/PLIF measurements will be used to validate numerical simulations of the mixing processes in water models of metallurgical reactors.
Reconstruction of the Gene Regulatory Network Involved in the Sonic Hedgehog Pathway with a Potential Role in Early Development of the Mouse Brain

The Sonic hedgehog (Shh) signaling pathway is crucial for pattern formation in early central nervous system development. By systematically analyzing high-throughput in situ hybridization data of E11.5 mouse brain, we found that Shh and its receptor Ptch1 define two adjacent mutually exclusive gene expression domains: Shh+Ptch1− and Shh−Ptch1+. These two domains are associated respectively with Foxa2 and Gata3, two transcription factors that play key roles in specifying them. Gata3 ChIP-seq experiments and RNA-seq assays on Gata3-knockdown cells revealed that Gata3 up-regulates the genes that are enriched in the Shh−Ptch1+ domain. Important Gata3 targets include Slit2 and Slit3, which are involved in the process of axon guidance, as well as Slc18a1, Th and Qdpr, which are associated with neurotransmitter synthesis and release. By contrast, Foxa2 both up-regulates the genes expressed in the Shh+Ptch1− domain and down-regulates the genes characteristic of the Shh−Ptch1+ domain. From these and other data, we were able to reconstruct a gene regulatory network governing both domains. Our work provides the first genome-wide characterization of the gene regulatory network involved in the Shh pathway that underlies pattern formation in the early mouse brain.