Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Adjustment of Region-Based Active Contour Parameters Using Local Image Geometry

A principled method for active contour (AC) parameterization remains a challenging issue in segmentation research, with a potential impact on the quality, objectivity, and robustness of the segmentation results. This paper introduces a novel framework for automated adjustment of region-based AC regularization and data fidelity parameters. Motivated by an isomorphism between the weighting factors of AC energy terms and the eigenvalues of structure tensors, we encode local geometry information by mining the orientation coherence in edge regions. In this light, the AC is repelled from regions of randomly oriented edges and guided toward structured edge regions. Experiments are performed on four state-of-the-art AC models, which are automatically adjusted and applied on benchmark datasets of natural, textured and biomedical images and two image restoration models. The experimental results demonstrate that the obtained segmentation quality is comparable to the one obtained by empirical parameter adjustment, without the cumbersome and time-consuming process of trial and error.
Elucidating the Role of Host Long Non-Coding RNA during Viral Infection: Challenges and Paths Forward

Research over the past decade has clearly shown that long non-coding RNAs (lncRNAs) are functional. Many lncRNAs can be related to immunity and the host response to viral infection, but their specific functions remain largely elusive. The vast majority of lncRNAs are annotated with extremely limited knowledge and tend to be expressed at low levels, making ad hoc experimentation difficult. Changes to lncRNA expression during infection can be systematically profiled using deep sequencing; however, this often produces an intractable number of candidate lncRNAs, leaving no clear path forward. For these reasons, it is especially important to prioritize lncRNAs into high-confidence “hits” by utilizing multiple methodologies. Large scale perturbation studies may be used to screen lncRNAs involved in phenotypes of interest, such as resistance to viral infection. Single cell transcriptome sequencing quantifies cell-type specific lncRNAs that are less abundant in a mixture. When coupled with iterative experimental validations, new computational strategies for efficiently integrating orthogonal high-throughput data will likely be the driver for elucidating the functional role of lncRNAs during viral infection. This review highlights new high-throughput technologies and discusses the potential for integrative computational analysis to streamline the identification of infection-related lncRNAs and unveil novel targets for antiviral therapeutics.
Improvement in object detection using Super Pixels

Most of the object detectors performance is degraded due to change in illumination, variant background and camera position. A method to enhance the detection performance of an offline generic detector is proposed in the paper. In this approach, all the detections are represented in Bag of Word fashion considering super pixels as its feature of classification, combining super pixels extraction and bag of word improves the object detection of a generic offline detector, object shape extraction from its background is segmented using graph cut algorithm. In standard, proposed approach takes the detection bounding box generated by a generic detector as input and improves the detection with better average precision. Bounding boxes are reduced with the objects shapes giving better performance using graph cut algorithm. Keywords—BoW, superpixels, segmentation
Towards a propagation model for wireless biomedical applications

Propagation model plays a very important role in designing wireless communication systems. Current advances in semiconductor technology has made it possible to implant a network of bio-sensors inside the human body for health monitoring purposes [C. Furse, H.K. Lai, C. Estes, A. Mahadik, A. Duncan, 1999], [C. Furse, R. Mohan, A. Jakayar, S. Karidehal, B. McCleod, S. Going, 2001], [L. Schwiebert, S.K. S. Gupta, P.S. G. Auner, G. Abrams, R. Lezzi, P. McAlister, 2002]. For wireless communication inside the human body, the tissue medium acts as a channel through which the information is sent as electromagnetic (EM) radio frequency (RF) waves. A propagation model is necessary to determine the losses involved in the form of absorption of EM wave power by the tissue. Absorption of EM waves by the tissue body, which consists of mostly saline water, accounts for a major portion of the propagation loss. In this paper we present a propagation loss model (PMBA) for homogeneous tissue bodies. We have verified the model for the frequency range of our interest (900 MHz to 3 GHz) using a 3D EM simulation software, HFSS/spl trade/, and experimental measurements using saturated salt water.
Modelling intermediate age and old stellar populations in the Infrared

In this paper we have investigated the spectro- photometric properties of the Asymptotic Giant Branch (AGB) starsandtheircontributiontotheintegratedinfraredemissionin simple stellar populations (SSP). Adopting analytical relations describing the evolution of these stars in the HR diagram and empirical relations for the mass-loss rate and the wind terminal velocity, we were able to model the effects of the dusty enve- lope around these stars, with a minimal number of parameters. After deriving simple scaling relations which allow us to ac- count for the metallicity of the star, we computed isochrones at different age and initial metal content. We compare our models withexistinginfraredcolorsofMgiantsandMirastarsandwith IRAS PSC data. The former data are fairly well reproduced by our models, though a possible inadequacy of the adopted at- mospheric models is indicated. Though being characterized by different metallicity, the isochrones follow a single path in the IRAS two color diagram, xed by the composition and optical properties of the dust mixture. The bulk of the data in the latter diagram is delimited by the curves corresponding to a mixture of silicate grains and one of carbonaceous grains. We also dis- cuss the effects of detached shells of matter but we do not take into account this phenomenon in the present computations. Contrary to previous models, in the new isochrones the mass-lossrate,whichestablishesthedurationoftheAGBphase, also determines the spectral properties of the stars. The contri- bution of these stars to the integrated light of the population is thus obtained in a consistent way. We nd that the emission in the mid infrared is about one order of magnitude larger when dust is taken into account in an intermediate age population, irrespective of the particular mixture adopted. The dependence of the integrated colors on the metallicity and age is discussed, with particular emphasis on the problem of age-metallicity de- generacy. We show that, contrary to the case of optical or near infrared colors, the adoption of a suitable pass-band in the mid infrared allows a fair separation of the two effects. We suggest intermediate redshift elliptical galaxies as possible targets of this method of solving the age-metallicity dilemma.
Exploiting Contextual Independence In Probabilistic Inference

Bayesian belief networks have grown to prominence because they provide compact representations for many problems for which probabilistic inference is appropriate, and there are algorithms to exploit this compactness. The next step is to allow compact representations of the conditional probabilities of a variable given its parents. In this paper we present such a representation that exploits contextual independence in terms of parent contexts; which variables act as parents may depend on the value of other variables. The internal representation is in terms of contextual factors (confactors) that is simply a pair of a context and a table. The algorithm, contextual variable elimination, is based on the standard variable elimination algorithm that eliminates the nonquery variables in turn, but when eliminating a variable, the tables that need to be multiplied can depend on the context. This algorithm reduces to standard variable elimination when there is no contextual independence structure to exploit. We show how this can be much more efficient than variable elimination when there is structure to exploit. We explain why this new method can exploit more structure than previous methods for structured belief network inference and an analogous algorithm that uses trees.
Experiences with a metropolitan multiradio wireless mesh network: design, performance, and application

Wireless mesh networks comprise nodes with multiple radio interfaces, and can provide low-cost high-speed Internet access or connectivity for data transfer. In this article we report our experiences and investigations with an experimental metropolitan multiradio mesh network that covers an area of approximately 60 km2 in the city of Heraklion, Crete. We present the design and deployment of the network, experiments to quantify the network's performance, and an application that runs on top of it and exploits it's low-cost wide-area connectivity. The metropolitan network consists of 16 nodes, among which six are core nodes, each with up to four 802.11a wireless interfaces and an additional wireless interface for management and monitoring. The distance between core mesh nodes varies from 1.6 to 5 km, and the mesh network contains two gateways that connect it to a wired network. Our performance experiments involve rate, power, and channel control for long-distance metropolitan links, and include investigations of the timescales for the operation for these mechanisms. Finally, we present a system for continuous online electromagnetic field monitoring and spectrum sensing, which utilizes the metropolitan mesh network for collecting wide-area measurements from low-cost EMF measurement devices.
A Comparison of Quality of Life in Haemodialysis and Peritoneal Dialysis Patients

Decreased quality of life of end-stage renal disease is further compromised by renal function replacement treatments such as haemodialysis (HD) and peritoneal dialysis (PD). Poor quality of life negatively affects treatment outcome. This study compared quality of life between HD and PD patients. Quality of life in 15 HD and 15 PD patients at a South African renal unit was compared using the SF-36 short form. There was no significant difference between HD and PD patients for total SF-36 score, but HD subjects reported more pain. Quality of life is similar in HD and PD patients, with the exception of higher pain levels in HD patients.
Linking Low-Level Stable Isotope Fractionation to Expression of the Cytochrome P450 Monooxygenase-Encoding ethB Gene for Elucidation of Methyl tert-Butyl Ether Biodegradation in Aerated Treatment Pond Systems

ABSTRACT Multidimensional compound-specific stable isotope analysis (CSIA) was applied in combination with RNA-based molecular tools to characterize methyl tertiary (tert-) butyl ether (MTBE) degradation mechanisms occurring in biofilms in an aerated treatment pond used for remediation of MTBE-contaminated groundwater. The main pathway for MTBE oxidation was elucidated by linking the low-level stable isotope fractionation (mean carbon isotopic enrichment factor [εC] of −0.37‰ ± 0.05‰ and no significant hydrogen isotopic enrichment factor [εH]) observed in microcosm experiments to expression of the ethB gene encoding a cytochrome P450 monooxygenase able to catalyze the oxidation of MTBE in biofilm samples both from the microcosms and directly from the ponds. 16S rRNA-specific primers revealed the presence of a sequence 100% identical to that of Methylibium petroleiphilum PM1, a well-characterized MTBE degrader. However, neither expression of the mdpA genes encoding the alkane hydroxylase-like enzyme responsible for MTBE oxidation in this strain nor the related MTBE isotope fractionation pattern produced by PM1 could be detected, suggesting that this enzyme was not active in this system. Additionally, observed low inverse fractionation of carbon (εC of +0.11‰ ± 0.03‰) and low fractionation of hydrogen (εH of −5‰ ± 1‰) in laboratory experiments simulating MTBE stripping from an open surface water body suggest that the application of CSIA in field investigations to detect biodegradation may lead to false-negative results when volatilization effects coincide with the activity of low-fractionating enzymes. As shown in this study, complementary examination of expression of specific catabolic genes can be used as additional direct evidence for microbial degradation activity and may overcome this problem.
From Patches to Honey-Patches: Lightweight Attacker Misdirection, Deception, and Disinformation

Traditional software security patches often have the unfortunate side-effect of quickly alerting attackers that their attempts to exploit patched vulnerabilities have failed. Attackers greatly benefit from this information; it expedites their search for unpatched vulnerabilities, it allows them to reserve their ultimate attack payloads for successful attacks, and it increases attacker confidence in stolen secrets or expected sabotage resulting from attacks. To overcome this disadvantage, a methodology is proposed for reformulating a broad class of security patches into honey-patches - patches that offer equivalent security but that frustrate attackers' ability to determine whether their attacks have succeeded or failed. When an exploit attempt is detected, the honey-patch transparently and efficiently redirects the attacker to an unpatched decoy, where the attack is allowed to succeed. The decoy may host aggressive software monitors that collect important attack information, and deceptive files that disinform attackers. An implementation for three production-level web servers, including Apache HTTP, demonstrates that honey-patching can be realized for large-scale, performance-critical software applications with minimal overheads.
Microfluidic serial dilution ladder.

Serial dilution is a fundamental procedure that is common to a large number of laboratory protocols. Automation of serial dilution is thus a valuable component for lab-on-a-chip systems. While a handful of different microfluidic strategies for serial dilution have been reported, approaches based on continuous flow mixing inherently consume larger amounts of sample volume and chip real estate. We employ valve-driven circulatory mixing to address these issues and also introduce a novel device structure to store each stage of the dilution process. The dilution strategy is based on sequentially mixing the rungs of a ladder structure. We demonstrate a 7-stage series of 1 : 1 dilutions with R(2) equal to 0.995 in an active device area of 1 cm(2).
ST-HMP: Unsupervised Spatio-Temporal feature learning for tactile data

Tactile sensing plays an important role in robot grasping and object recognition. In this work, we propose a new descriptor named Spatio-Temporal Hierarchical Matching Pursuit (ST-HMP) that captures properties of a time series of tactile sensor measurements. It is based on the concept of unsupervised hierarchical feature learning realized using sparse coding. The ST-HMP extracts rich spatio-temporal structures from raw tactile data without the need to predefine discriminative data characteristics. We apply it to two different applications: (1) grasp stability assessment and (2) object instance recognition, presenting its universal properties. An extensive evaluation on several synthetic and real datasets collected using the Schunk Dexterous, Schunk Parallel and iCub hands shows that our approach outperforms previously published results by a large margin.
Reactivation of cutaneous leishmaniasis after surgery

Cutaneous leishmaniasis (CL) is caused by a parasite from the genus Leishmania. Infection is transmitted to humans from the bite of sandflies. We describe an 85‐year‐old man who developed CL on his face after recent cutaneous surgery in that site. The case is also unusual because the most likely source of exposure to the infection occurred over 50 years previously. Polymerase chain reaction, slit‐skin smear, serology and the leishmanin test were not helpful in diagnosis, which was confirmed by histopathological demonstration of the parasite.
Toward Personalized Cell Therapies by Using Stem Cells: Seven Relevant Topics for Safety and Success in Stem Cell Therapy

Stem cells, both embryonic and adult, due to the potential for application in tissue regeneration have been the target of interest to the world scientific community. In fact, stem cells can be considered revolutionary in the field of medicine, especially in the treatment of a wide range of human diseases. However, caution is needed in the clinical application of such cells and this is an issue that demands more studies. This paper will discuss some controversial issues of importance for achieving cell therapy safety and success. Particularly, the following aspects of stem cell biology will be presented: methods for stem cells culture, teratogenic or tumorigenic potential, cellular dose, proliferation, senescence, karyotyping, and immunosuppressive activity.
A common short-term memory retrieval rate may describe many cognitive procedures

We examine the relationship between response speed and the number of items in short-term memory (STM) in four different paradigms and find evidence for a similar high-speed processing rate of about 25–30 items per second (∼35–40 ms/item). We propose that the similarity of the processing rates across paradigms reflects the operation of a very basic covert memory process, high-speed retrieval, that is involved in both the search for information in STM and the reactivation or refreshing of information that keeps it in STM. We link this process to a specific pattern of rhythmic, repetitive neural activity in the brain (gamma oscillations). This proposal generates ideas for research and calls for an integrative approach that combines neuroscientific measures with behavioral cognitive techniques.
Natural Language Grounding and Grammar Induction for Robotic Manipulation Commands

We present a cognitively plausible system capable of acquiring knowledge in language and vision from pairs of short video clips and linguistic descriptions. The aim of this work is to teach a robot manipulator how to execute natural language commands by demonstration. This is achieved by first learning a set of visual ‘concepts’ that abstract the visual feature spaces into concepts that have human-level meaning. Second, learning the mapping/grounding between words and the extracted visual concepts. Third, inducing grammar rules via a semantic representation known as Robot Control Language (RCL). We evaluate our approach against state-of-the-art supervised and unsupervised grounding and grammar induction systems, and show that a robot can learn to execute never seen-before commands from pairs of unlabelled linguistic and visual inputs.
A Gradient in Endogenous Rhythmicity and Oscillatory Drive Matches Recruitment Order in an Axial Motor Pool

The rhythmic firing behavior of spinal motoneurons is a function of their electrical properties and synaptic inputs. However, the relative contribution of endogenous versus network-based rhythmogenic mechanisms to locomotion is unclear. To address this issue, we have recorded from identified motoneurons and compared their current-evoked firing patterns to network-driven ones in the larval zebrafish (Danio rerio). Zebrafish axial motoneurons are recruited topographically from the bottom of the spinal cord up. Here, we have explored differences in the morphology of axial motoneurons, their electrical properties, and their synaptic drive, to reveal how they match the topographic pattern of recruitment. More ventrally located “secondary” motoneurons generate bursts of action potentials in response to constant current steps, demonstrating a strong inherent rhythmogenesis. The membrane potential oscillations underlying bursting behavior occur in the normal frequency range of swimming. In contrast, more dorsal secondaries chatter in response to current, while the most dorsally distributed “primary” motoneurons all fire tonically. We find that systematic variations in excitability and endogenous rhythmicity are inversely related to the level of oscillatory synaptic drive within the entire axial motor pool. Specifically, bursting cells exhibit the least amount of drive, while tonic cells exhibit the most. Our data suggest that increases in swimming frequency are accomplished by the recruitment of axial motoneurons that progressively rely on instructive synaptic drive to shape their oscillatory activity appropriately. Thus, within the zebrafish spinal cord, there are differences in the relative contribution of endogenous versus network-based rhythms to locomotion and these vary predictably according to order of recruitment.
Emergence of Mirror Neurons in a Model of Gaze Following

Gaze following is the ability to redirect one's gaze to the location where another agent is looking. We present a computational model of how human infants or other agents may acquire gaze following by learning to predict the locations of interesting sights from the looking behavior of other agents through reinforcement learning. The model accounts for many findings about the development of gaze following in human infants. During learning, the model develops pre-motor representations that exhibit many properties characteristic of mirror neurons, but they are specific to looking behaviors. The existence of such a new class of mirror neurons is the main prediction of our model. The model also offers a parsimonious account of how these and possibly other mirror neurons may acquire their special response properties. In this account, visual representations of other agents' actions become associated with pre-motor neurons that represent the intention to perform corresponding actions. The model also demonstrates how this development may be obstructed in autism spectrum disorder, giving rise to specific physiological and anatomical differences in the mirror system.