Miracle-dz/UniFAR-FTUs huggingface dataset:
Sirolimus-Eluting Stents to Abolish Intimal Hyperplasia and Improve Flow in Porcine Arteriovenous Grafts: A 4-Week Follow-Up Study

Background—The patency of arteriovenous (AV) expanded polytetrafluoroethylene (ePTFE) hemodialysis grafts is severely compromised by intimal hyperplasia (IH) at the venous anastomosis and in the venous outflow tract. We addressed the potential of primary placement of a sirolimus-eluting stent (SES) in a validated porcine model. Methods and Results—In 25 pigs, ePTFE AV grafts were created bilaterally between the carotid artery and the jugular vein, whereupon a self-expandable nitinol stent (14 SESs and 11 bare-metal stents) was implanted over the venous anastomosis in 1 of the 2 grafts. After exclusion of technical failures and 1 unilateral occlusion, 16 pigs (9 SESs and 7 bare-metal stents) were included for further analysis. After 28 days, we measured graft flow and performed quantitative angiography. The pigs were then euthanized, and grafts with adjacent vessels were excised for histological analysis. Minimal luminal diameter was substantially larger in the SES group compared with unstented controls (5.9±0.2 versus 3.8±0.4 mm, respectively, P=0.01), which was accompanied by more prominent graft flow (SES, 1360±89 mL/min versus unstented, 861±83 mL/min, P=0.05). IH at the venous anastomosis was 77% less in the SES group compared with unstented controls (0.44±0.05 versus 1.92±0.5 mm2, respectively, P=0.01), whereas IH increased markedly when bare-metal stents were used (5.7±1.4 mm2, P=0.05). Conclusions—SESs in the venous outflow of AV grafts significantly reduce IH and increase vessel diameter and graft flow compared with unstented grafts. These findings suggest that SESs have the potential to improve primary patency of AV grafts in hemodialysis patients.
Medical and Para-Medical Personnel' Perspectives on Home Health Care Technology

User-based research is strongly recommended in design for older adults. The aim of this paper is to focus the attention on the poorly explored role of medical and para-medical personnel’s perspective on home health care technologies using data that have been gained during the “Active Ageing At Home” (AA@H) project. A focus group was organized at the National Institute of Health & Science on Ageing (INRCA) in Italy. Results demonstrate that several challenges deserve a stronger effort by the whole research sector on ageing and technology: (1) a leading role of the participatory design process; (2) the assessment of the added value of health technologies through robust methods; (3) the definition of an unique identity and well established practices among disciplines; (4) the creation of favorable prerequisites and conditions to the technology uptake.
Web Image and Video Mining Towards Universal and Robust Age Estimator

In this paper, we present an automatic web image and video mining framework with the ultimate goal of building a universal human age estimator based on facial information, which is applicable to all ethnic groups and various image qualities. On one hand, a large (391 k) yet noisy human aging image database is collected from Flickr and Google Image using a set of human age-related text queries. Multiple human face detectors based on distinctive techniques are adopted for noise-prune face detection. For each image, the detected faces with high detection confidences constitute a bag of face instances. We further remove the outliers via principal component analysis (PCA), which results in a condensed image database with about 175 k face instances. A robust multi-instance regressor learning algorithm is then developed to learn the kernel regression-based human age estimator in the presence of bag label noises. On the other hand, about 10 k video clips are downloaded from YouTube. We extract tracked face sequences from these video clips. Although their age labels are unknown, the tracked faces within a sequence are naturally with identical ages. This age-consistence constraint for face pairs is used as an extra regularizer to enhance the robustness of the age estimator. The derived human age estimator is extensively evaluated on three benchmark human aging databases, and without taking any images from these benchmark databases as training samples, comparable age estimation accuracies with the state-of-the-art results are achieved.
Computer Assisted Vocabulary Learning: Examining English Language Learners' Vocabulary Notebooks

The present study aims to investigate whether and how keeping vocabulary notebooks in digital forms influence students' vocabulary learning practices, performance, and perceptions. Of particular interest to this study is the use of learner-constructed vocabulary notebooks to engage students in the process of intentional vocabulary learning, and ultimately, to enhance their vocabulary acquisition. A Computer Assisted Vocabulary Learning (CAVL) system was developed in this study to assist learners of English as a foreign language. The usage of the CAVL system involved three major steps (i.e., Select, Organize, and Integrate), which engaged learners in watching online videos to intentionally study target words, through the construction of personal vocabulary notebooks. The effectiveness of this system, in combination with the intentional vocabulary learning strategy, was evaluated through a quasi-experimental study with two groups of students from a university in Taiwan. The students' use of vocabulary notebooks, scores of vocabulary tests, individual interviews, and responses to a perception survey were closely analyzed, and the results showed the overall positive impact of the investigated strategy on vocabulary learning. The practical implications of this study are thus discussed to promote the use of digital vocabulary notebooks as an intentional learning strategy in vocabulary instruction.
Adaptive robust control for servo system with friction and input dead-zone nonlinearity

An adaptive robust control (ARC) algorithm is developed for servo system driving by gears with friction and dead-zone nonlinearity, parametric uncertainties and uncertain nonlinearities disturbances. The existing robust adaptive control methods mainly focus on using on-line parameter adaptation for friction and the approximate inversion of the unknown dead-zone. But even without other uncertain nonlinearities and disturbance, asymptotic output tracking can never be achieved by continuous controller for the non-smooth characteristics of friction and dead-zone. In this paper, the dead-zone inverse is not constructed. Furthermore viscous friction and elasticity force are considered in the system model. The proposed adaptive robust control law consists three parts: model compensation term, the robust control term and robust feedback term. The ARC ensures that all closed-loop signals are bounded and achieves the tracking within the desired precision. Simulations results illustrate the performance of the ARC.
Detection of Treponema pallidum subsp. pallidum from Skin Lesions, Serum, and Cerebrospinal Fluid in an Infant with Congenital Syphilis after Clindamycin Treatment of the Mother during Pregnancy

ABSTRACT We report here a case of congenital syphilis in a newborn after clindamycin treatment in pregnancy. Using PCR detection of tmpC (TP0319) and DNA sequencing of the genes TP0136 and TP0548, DNA sequences identical to Treponema pallidum subsp. pallidum strain SS14 were detected in the infant's skin lesions, serum, and cerebrospinal fluid.
Infection and blood transfusion: a guide to donor screening

Abstract In recent years, blood-component therapy has become more accessible in veterinary practice. As with human medicine, care must be taken to minimize the risk of disease transmission from donor to recipient. Determining the appropriate diseases to screen for is complicated by regional variations in disease incidence, the existence of chronic carrier states for some diseases, the difficulty in screening-test selection, and testing cost. The feline diseases considered include retroviral infections, feline coronaviruses, ehrlichiosis (Ehrlichia canis-like), anaplasmosis (Anaplasma phagocytophilum), neorickettsiosis (Neorickettsia risticii), hemoplasmosis (Mycoplasma hemofelis and M. hemominutum, previously feline hemobartonellosis), and cytauxzoonosis (Cytauxzoon felis). The canine diseases considered in this paper include babesiosis (Babesia canis and B. gibsonii,) ehrlichiosis (E. canis and E. ewingii), anaplasmosis (A. phagocytophilum), neorickettsiosis (N. risticii var. atypicalis), leishmaniasis (Leishmania donovani complex), brucellosis (Brucella canis), hemoplasmosis (M. hemocanis, previously canine hemobartonellosis), and bartonellosis (Bartonella vinsonii).
Menstrual Cycle Phase and Duration of Oral Contraception Intake Affect Olfactory Perception

Although a significant impact of cycle phase on olfactory thresholds has been shown in females, limited data exist regarding discrimination and identification. Therefore, we investigated a broader range of olfactory performance and analyzed the impact of cycle phase and oral contraception. We measured 80 healthy Caucasians, including 20 females taking oral contraceptives and 40 females without oral contraception who were further divided into follicular and luteal phase. Olfactory performance of all participants was assessed twice using the “Sniffin’ Sticks” battery and intensity and pleasantness ratings of n-butanol were collected. Data analysis revealed that females outperformed males in odor discrimination and odor identification. In the luteal phase, higher thresholds and higher intensity ratings for n-butanol emerged. Duration of oral contraception correlated positively with olfactory performance pointing to better performance with longer intake. Hence, our data show that odor performance is affected by menstrual cycle phase and duration of oral contraception intake and thus can be modulated by hormonal changes.
Adjustable Autonomy: From Theory to Implementation

Recent exciting, ambitious applications in agent technology involve agents acting individually or in teams in support of critical activities of individual humans or entire human organizations. Applications range from intelligent homes [13], to "routine" organizational coordination[16], to electronic commerce[4] to long-term space missions[12, 6]. These new applications have brought forth an increasing interest in agents’ adjustable autonomy (AA), i.e., in agents’ dynamically adjusting their own level of autonomy based on the situation[8]. In fact, many of these applications will not be deployed, unless reliable AA reasoning is a central component. At the heart of AA is the question of whether and when agents should make autonomous decisions and when they should transfer decision-making control to other entities (e.g., human users). Unfortunately, previous work in adjustable autonomy has focused on individual agent-human interactions and tile techniques developed fail to scale-up to complex heterogeneous organizations. Indeed, as a first step, we focused on a smallscale, but real-world agent-human organization called Electric Elves, where an individual agent and human worked together within a larger multiagent context. Although’the application limits the interactions among entities, key weaknesses of previous approaches to adjustable autonomy are readily apparent. In particular, previous approaches to transferof-control are seen to be too rigid, employing one-shot transfersof-control that can result in unacceptable coordination failures. Furthermore, the previous approaches ignore potential costs (e.g., from delays) to an agent’s team due to such transfers of control. To remedy such problems, we propose a novel approach to AA, based on the notion of a transfer-of-control strategy. A transfer-of-control strategy consists of a conditional sequence of two types of actions: (i) actions to transfer decision-making control (e.g., from the agent to the user or vice versa) and (ii) actions to change an agent’s pre-specified coordination constraints with team members, aimed at minimizing miscoordination costs. The goal is for high quality individual decisions to be made with minimal disruption to the coordination of the team. We operationalize such strategies via Markov decision processes (MDPs) which select the optimal strategy given an uncertain environment and costs to individuals and teams. We have developed a general reward function and state representation for such an MDP, to facilitate application of the approach to different domains. We present results from a careful evaluation of this approach, including via its use in our real-world, deployed Electric Elves system.
Toward Harmonizing Self-reported and Logged Social Data for Understanding Human Behavior

While self-reporting remains the most common method to understand human behavior, recent advances in social networks, mobile technologies, and other computer-mediated communication technologies are allowing researchers to obtain detailed logs of human behavior with ease. While the logged data is very useful (and accurate) at capturing the structure of the user's social network, the self-reported data provides an insight into the user's cognitive map of her social network. Based on a field study involving 47 users for a period of ten weeks we report that combining the two sets of data (self-reported and logged) gives higher predictive power than using either one of them individually. Further, the difference between the two types of values captures the level of dissonance between a user's actual and perceived social behavior and is found to be an important predictor of the person's social outcomes including social capital, social support and trust.
Tools for incremental development of educational software interfaces

In this paper we describe the evolution of an educational software tool designed to let non-programmers build content-rich learning environments. Version 1 was a wholly model-driven authoring environment, but was unpopular with authors as they were forced them to build up-front domain representations before prototyping their interfaces. Version 2 uses a GUI method of interface development while the model is developed incrementally and as needed. In this version, authors built less of a model overall, but were more satisfied with the results. This paper discusses the natures of the two approaches to model-building and how they are authored.
Rolling Shutter Camera Calibration

Rolling Shutter (RS) cameras are used across a wide range of consumer electronic devices-from smart-phones to high-end cameras. It is well known, that if a RS camera is used with a moving camera or scene, significant image distortions are introduced. The quality or even success of structure from motion on rolling shutter images requires the usual intrinsic parameters such as focal length and distortion coefficients as well as accurate modelling of the shutter timing. The current state-of-the-art technique for calibrating the shutter timings requires specialised hardware. We present a new method that only requires video of a known calibration pattern. Experimental results on over 60 real datasets show that our method is more accurate than the current state of the art.
Area optimization of cryptographic co-processors implemented in dual-rail with precharge positive logic

Field programmable gate arrays (FPGAs) become very popular for embedded cryptographic operations. In order to resist side-channel attacks, FPGAs must implement reasoned countermeasures. The most efficient way to mitigate attacks is to adopt a gate-level protection. Two secure gates families exist: those that ldquohiderdquo and those that ldquomaskrdquo side-channel leakage. In this article, we detail methods to reduce the size of wave dynamic differential logic (WDDL) implementations. These circuits are designed to hide any physical leak by ensuring a data-independent activity. This study is meant to be generic, and thus applies to any 4 rarr 1 LUT-based FPGAs. Further optimizations can be reached by taking advantage of some FPGAs proprietary features. Our solutions include RTL code modification, synthesizer usage (potentially in a re-entrant way), and ad hoc mapping. We show that linear parts of algorithms can be delegated to a synthesizer, but that non-linear parts are better off to be handled with heuristics. We present a 23 % area gain over the state-of-the-art as for the positive WDDL triple-DES symmetric encryption algorithm.
Detection and isolation of routing attacks through sensor watermarking

In networked control systems, leveraging the peculiarities of the cyber-physical domains and their interactions may lead to novel detection and defense mechanisms against malicious cyber-attacks. In this paper, we propose a multiplicative sensor watermarking scheme, where each sensor's output is separately watermarked by a Single Input Single Output (SISO) filter. Hence, such scheme does not require communication between multiple sensors, but can still lead to detection and isolation of malicious cyber-attacks. In particular, we analyze the benefits of the proposed watermarking scheme for two attack scenarios: the physical sensor re-routing attack and the cyber measurement re-routing one. For each attack scenario, detectability and isolability properties are analyzed with and without the proposed watermarking scheme and we show how the watermarking scheme can be leveraged to detect cyber sensor routing attacks. In order to detect compromised sensors, we design an observer-based detector with a robust adaptive threshold. Additionally, we identify the sensors involved in the re-routing attacks by means of a tailored Recursive Least Squares parameter estimation algorithm. The results are illustrated through a numerical example.
Connections Between Score Matching, Contrastive Divergence, and Pseudolikelihood for Continuous-Valued Variables

Score matching (SM) and contrastive divergence (CD) are two recently proposed methods for estimation of nonnormalized statistical methods without computation of the normalization constant (partition function). Although they are based on very different approaches, we show in this letter that they are equivalent in a special case: in the limit of infinitesimal noise in a specific Monte Carlo method. Further, we show how these methods can be interpreted as approximations of pseudolikelihood.
Color permutation: an iterative algorithm for memory packing

It is predicted that 70% of silicon real-estate will be occupied by memories in future system-on-chips. The minimization of on-chip memory hence becomes increasingly important for cost, performance and energy consumption. In this paper, we present a reasonably fast algorithm based on iterative improvement, which packs a large number of memory blocks into a minimum-size address space. The efficiency of the algorithm is achieved by two new techniques. First, in order to evaluate each solution in linear time, we propose a new algorithm based on the acyclic orientation of the memory conflict graph. Second, we propose a novel representation of the solution which effectively compresses the potentially infinite solution space to a finite value of n! , where n is the number of vertices in the memory conflict graph. Furthermore, if a near-optimal solution is satisfactory, this value can be dramatically reduced to /spl chi/! , where /spl chi/! is the chromatic number of the memory conflict graph. Experiments show that consistent improvement over scalar method by 30% can be achieved.
Quantitative PCR and Digital PCR for Detection of Ascaris lumbricoides Eggs in Reclaimed Water

The reuse of reclaimed water from wastewater depuration is a widespread and necessary practice in many areas around the world and must be accompanied by adequate and continuous quality control. Ascaris lumbricoides is one of the soil-transmitted helminths (STH) with risk for humans due to its high infectivity and an important determinant of transmission is the inadequacy of water supplies and sanitation. The World Health Organization (WHO) recommends a limit equal to or lower than one parasitic helminth egg per liter, to reuse reclaimed water for unrestricted irrigation. We present two new protocols of DNA extraction from large volumes of reclaimed water. Quantitative PCR (qPCR) and digital PCR (dPCR) were able to detect low amounts of A. lumbricoides eggs. By using the first extraction protocol, which processes 500 mL of reclaimed water, qPCR can detect DNA concentrations as low as one A. lumbricoides egg equivalent, while dPCR can detect DNA concentrations as low as five A. lumbricoides egg equivalents. By using the second protocol, which processes 10 L of reclaimed water, qPCR was able to detect DNA concentrations equivalent to 20 A. lumbricoides eggs. This fact indicated the importance of developing new methodologies to detect helminth eggs with higher sensitivity and precision avoiding possible human infection risks.
A Systematic Review and Pooled Analysis of Peroneal Artery Perforators for Fibula Osteocutaneous and Perforator Flaps

Background: Despite the availability of cadaveric, anatomic, and clinical models to identify peroneal artery perforators in the lower leg, there is no consensus on the optimal fibula interval to reliably capture perforators for flap and skin paddle design. Methods: A systematic review of the MEDLINE and Cochrane databases was performed to identify all anatomical, clinical, and radiographic reports of peroneal artery perforators in the lower leg. Locations were indexed along tenths of the total fibula length to incorporate a uniform format. Results: Three clinical and six cadaveric reports identified 445 legs and 1710 perforators. The 0.6 interval had the greatest total perforator frequency at 19.1 ± 1 percent, with 310 perforators and a positive probability of 79.1 ± 2.1 percent. Chi-square analysis found a statistical difference in perforator frequency at the flanking intervals of 0.5 and 0.8 (p = 0.0058 and p = 0.0019) and beyond. Subgroup analysis of septocutaneous perforators was based on 345 legs and 608 perforators. The 0.6 interval was the densest, with 110 perforators and a frequency of 18.1 ± 1.6 percent. The musculocutaneous subgroup analysis found 292 legs and 831 perforators, and a densest interval at 0.4, based on 157 perforators and a frequency of 18.9 ± 1.4 percent. Conclusions: This systematic review and pooled analysis of all available and complete peroneal artery perforator data demonstrates clustering over the 0.6 interval of the lateral leg. This interval should be considered during flap design and elevation to reliably capture irrigating perforators for free and local flap applications.
Real-Time LDCRF-Based Method for Inferring TV Viewer Interest

Context-awareness provides users with more versatile user interface environments when using digital devices. In a TV viewing environment, context-awareness techniques can be used for recommending useful information related to the viewed program. To incorporate a user's preference in doing so, it is vital to infer whether the viewer is actually interested in the TV program. Therefore, we propose a method for inferring viewer interest in a TV program. In the proposed method, we regard the problem of inferring viewer interest as a sequential labeling problem and solve it by applying latent dynamic conditional random fields to data sequences generated by integrating the operational log information of user interaction and visual information of viewer behaviors.