Miracle-dz/UniFAR-FTUs huggingface dataset:
Obstruction of Pores in Distal Protection Filters and Angiographically-Documented Flow Impairment during Carotid Artery Stenting

Purpose: To determine any relationship between angiographically documented flow impairment associated with the Angioguard XP cerebral protection filter during carotid artery stenting (CAS) and the condition of the pores in the retrieved filter. Methods: To obtain baseline characteristics of the Angioguard XP, an unused filter was fully expanded and examined photographically from the cephalad end of the device to determine the structure of the pores in the filter basket. Ten pores assembled in a hexagonal pattern made up a pore group, several of which were arranged in 4 concentric rings surround a central hub that did not have any pores. For each ring of pore groups, the ring diameter, number of pore groups, and the mean minimum pore diameter were measured on a plane perpendicular to the long axis of the device. From these, the area of the ring membrane, the area of the pores, and the ratio of pore area to membrane area were calculated for each ring. Filters retrieved from 56 CAS procedures were retrospectively analyzed along with the operative records and intraprocedural angiograms performed after filter placement, predilation, stent placement, postdilation, aspiration of blood, and filter retrieval. The operators classified blood flow immediately before filter retrieval as normal, slow, or stopped. After retrieval, the filter was cut, rinsed with saline, fixed in 10% neutral buffer formalin, and macroscopically and microscopically inspected. The number of the open pores without any obstruction was counted for each ring. Results: Retrieved filters from flow-impaired cases showed a significantly lower percentage of open pores in comparison to normal-flow cases (p<0.05). In some normal-flow cases, however, the obstruction rates were higher than mean obstruction rates of the slow-flow cases. In normal-flow cases, >5% of pores from the center to the second ring of the filter were open; this constituted more than two thirds of the entire filter diameter. Conclusion: The flow state on DSA was related to, but did not completely depend on, filter patency. The low patency rate of the filter in normal-flow cases suggested that flow impairment was occurring but could not be detected by the qualitative evaluation of flow on angiography.
Learning Binary Codes and Binary Weights for Efficient Classification

This paper proposes a generic formulation that significantly expedites the training and deployment of image classification models, particularly under the scenarios of many image categories and high feature dimensions. As a defining property, our method represents both the images and learned classifiers using binary hash codes, which are simultaneously learned from the training data. Classifying an image thereby reduces to computing the Hamming distance between the binary codes of the image and classifiers and selecting the class with minimal Hamming distance. Conventionally, compact hash codes are primarily used for accelerating image search. Our work is first of its kind to represent classifiers using binary codes. Specifically, we formulate multi-class image classification as an optimization problem over binary variables. The optimization alternatively proceeds over the binary classifiers and image hash codes. Profiting from the special property of binary codes, we show that the sub-problems can be efficiently solved through either a binary quadratic program (BQP) or linear program. In particular, for attacking the BQP problem, we propose a novel bit-flipping procedure which enjoys high efficacy and local optimality guarantee. Our formulation supports a large family of empirical loss functions and is here instantiated by exponential / hinge losses. Comprehensive evaluations are conducted on several representative image benchmarks. The experiments consistently observe reduced complexities of model training and deployment, without sacrifice of accuracies.
Venturia inaequalis: the causal agent of apple scab.

UNLABELLED The fungus Venturia inaequalis infects members of the Maloideae, and causes the disease apple scab, the most important disease of apple worldwide. The early elucidation of the gene-for-gene relationship between V. inaequalis and its host Malus has intrigued plant pathologists ever since, with the identification of 17 resistance (R)-avirulence (Avr) gene pairings. The Avr gene products are presumably a subset of the total effector arsenal of V. inaequalis (predominantly proteins secreted in planta assumed to facilitate infection). The supposition that effectors from V. inaequalis act as suppressors of plant defence is supported by the ability of the pathogen to penetrate the cuticle and differentiate into large pseudoparenchymatous structures, termed stromata, in the subcuticular space, without the initiation of an effective plant defence response. If effectors can be identified that are essential for pathogenicity, the corresponding R genes will be durable and would add significant value to breeding programmes. An R gene cluster in Malus has been cloned, but no V. inaequalis effectors have been characterized at the molecular level. However, the identification of effectors is likely to be facilitated by the resolution of the whole genome sequence of V. inaequalis. TAXONOMY Teleomorph: Venturia inaequalis Cooke (Wint.); Kingdom Fungi; Phylum Ascomycota; Subphylum Euascomycota; Class Dothideomycetes; Family Venturiaceae; genus Venturia; species inaequalis. Anamorph: Fusicladium pomi (Fr.) Lind or Spilocaea pomi (Fr.). LIFE CYCLE: V. inaequalis is a hemibiotroph and overwinters as pseudothecia (sexual fruiting bodies) following a phase of saprobic growth in fallen leaf tissues. The primary inoculum consists of ascospores, which germinate and penetrate the cuticle. Stromata are formed above the epidermal cells but do not penetrate them. Cell wall-degrading enzymes are only produced late in the infection cycle, raising the as yet unanswered question as to how V. inaequalis gains nutrients from the host. Conidia (secondary inoculum) arise from the upper surface of the stromata, and are produced throughout the growing season, initiating multiple rounds of infection. VENTURIA INAEQUALIS AS A MODEL PATHOGEN OF A WOODY HOST: V. inaequalis can be cultured and is amenable to crossing in vitro, enabling map-based cloning strategies. It can be transformed readily, and functional analyses can be conducted by gene silencing. Expressed sequence tag collections are available to aid in gene identification. These will be complemented by the whole genome sequence, which, in turn, will contribute to the comparative analysis of different races of V. inaequalis and plant pathogens within the Dothideomycetes.
Religiosity, spirituality, and depressive symptoms in older adults in an active living community

The population of older adults in the United States is steadily rising. The Centers for Disease Control and Prevention (CDC) recently released a call to reduce mental distress in older adults. Research shows that mental distress is associated with depressive symptoms, which are significantly related to many chronic medical conditions, functional impairment, suicide, and allcause mortality. Depression is a major public health concern. There is an interest in gerontology research on the buffering role of engagement against depressive symptoms such as volunteering, social activities, and religion. Certain religious beliefs and behaviors contribute to maintaining or improving mental health and research suggests that religiosity may act as a buffer against depressive symptoms. As the population of older adults exponentially increases, there is a need for theory guided research that examines the relationship between religiosity and depressive symptoms and mediators as possible mechanisms. This study addresses two important gaps in the literature on depressive symptoms within the religious gerontology field: the relationships of a wider range of religious variables with depressive symptoms, and examining health behaviors and social support as mediators. Data were collected from the University of South Florida (USF) Health in The Villages study, a population-based study of older adults residing in an active living community in southwest central Florida. Binary logistic regression analyses were conducted that examined multiple measures of religiosity (organizational religiosity, subjective religiosity, and subjective spirituality) and covariates as predictors of depressive symptoms as defined by the Patient Health Questionaire-2 (PHQ-2). The PHQ-2 is a validated 2-item screener tool for measuring depressive
Wilson disease in two consecutive generations: an exceptional family

organ, it is not feasible in most cases. Drugs are a relatively uncommon cause of pancreatitis, reported only infrequently in the English language literature (5). The association of riluzole with pancreatitis in this case appears probable. The patient had clinical, laboratory, and radiological evidence of acute pancreatitis. There was a temporal relationship between the use of riluzole and the onset of symptoms, and the picture resolved after the drug was stopped. Other likely causes of pancreatitis were not present. Although the patient was diagnosed with peptic ulcer he had been symptom free for years when the pancreatitis occurred. Rechallenge was not attempted, and therefore evidence for a definite association is failing. The absence of systemic hypersensitivity manifestations and the appearance of injury months after exposure suggest that the damage may be produced through the accumulation of a toxic metabolite. The mechanism of drug-induced damage in the pancreas is still not completely understood (6). Although acute pancreatitis is a serious medical condition with considerable morbidity and mortality, drug-induced acute pancreatitis usually runs a benign course (5). A wide variety of different drugs ( .85) have consistently been associated with acute pancreatitis (7), but few data exist about the incidence of drug-induced pancreatitis in the general population. Acute pancreatitis has previously been reported with the use of riluzole (8). Overall, 11 cases of pancreatitis possibly associated with riluzole have been reported up to December, 1997, resulting in an estimated incidence of about 4.5/10,000 treated patients, according to data reported to Rhone-Poulenc-Rourer (9). Therefore, riluzole should be added to the list of medications that potentially cause acute pancreatitis. Although this is not consistent with the product information, physicians should be made aware of this risk. In view of the modest improvements in survival rate that have been demonstrated in this fatal progressive degenerative disorder with riluzole and the concerns about its side effect profile, only patients for whom evidence of efficacy is provided by well-designed clinical trials should be treated (10), so that the benefit of the agent outweighs potential risk and therefore it could be used with an acceptable benefit to risk ratio.
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise

Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for constructing a kernel Fisher discriminant (KFD) from training examples with noisy labels. The approach allows to associate with each example a probability of the label being flipped. We utilise an expectation maximization (EM) algorithm for updating the probabilities. The E-step uses class conditional probabilities estimated as a by-product of the KFD algorithm. The M-step updates the flip probabilities and determines the parameters of the discriminant. We demonstrate the feasibility of the approach on two real-world data-sets.
Training a network to attend like human drivers saves it from common but misleading loss functions

We proposed a novel FCN-ConvLSTM model to predict multi-focal human driver's attention merely from monocular dash camera videos. Our model has surpassed the state-of-the-art performance and demonstrated sophisticated behaviors such as watching out for a driver exiting from a parked car. In addition, we have demonstrated a surprising paradox: fine-tuning AlexNet on a largescale driving dataset degraded its ability to register pedestrians. This is due to the fact that the commonly practiced training paradigm has failed to reflect the different importance levels of the frames of the driving video datasets. As a solution, we propose to unequally sample the learning frames at appropriate probabilities and introduced a way of using human gaze to determine the sampling weights. We demonstrated the effectiveness of this proposal in human driver attention prediction, which we believe can also be generalized to other driving-related machine learning tasks.
Foot-mounted INS for everybody - an open-source embedded implementation

We present an open-source, realtime, embedded implementation of a foot-mounted, zero-velocity-update-aided inertial navigation system. The implementation includes both hardware design and software, uses off-the-shelf components and assembly methods, and features a standard USB interface. The software is written in C and can easily be modified to run user implemented algorithms. The hardware design and the software are released under permissive open-source licenses and production files, source code, documentation, and further resources are available at www.openshoe. org. The reproduction cost for a single unit is below $800, with the inertial measurement unit making up the bulk ($700). The form factor of the implementation is small enough for it to be integrated in the sole of a shoe. A performance evaluation of the system shows a position errors for short trajectories (<;100 [m]) of ± 0.2-1% of the traveled distance, depending on the shape of trajectory.
Gene Expression Profiling in Cervical Cancer: State of the Art and Future Directions

In this issue of The Cancer Journal, Wong et al report the identification of 10 genes associated with radiation response in cervical cancer. The aim of this work and of similar studies is to identify genes that have different levels of expression in patients with better or worse outcomes, which can be used to improve the accuracy with which prognosis can be predicted. However, traditional prognostic factors, such as stage and grade, continue to be used exclusively in most malignancies to make decisions about optimal cancer therapy. In a few diseases, molecular markers have been adequately informative to be incorporated into clinical decision making, while for the majority of malignancies, the hard work of finding ways to meaningfully and reproducibly categorize tumors on the basis of genetic changes continues. Genome-wide expression profiling has the potential to more accurately predict outcome since it allows selection of the genes that associate most strongly with outcome by screening a large number of these genes simultaneously. The hope is that additional genetic prognostic information can improve tailoring of treatment—e.g., permit a patient with a low chance of recurrence to avoid toxic therapy or identify patients at high risk who need the most aggressive therapy possible. Gene expression profiling also has the potential to facilitate development of biologically targeted therapies by identifying disrupted pathways that contribute to the malignant phenotype. P O T E N T I A L A P P L I C A T I O N S O F E X P R E S S I O N P R O F I L I N G I N C E R V I C A L C A N C E R
SeTM: Efficient Execution of Speculative Threads with Hardware Transactional Memory

Thread-Level Speculation (TLS) was researched to automatically parallelize portions of serial programs for execution, and transactional memory (TM) was studied as a promising alternative of lock for parallel programming due to its simplicity. Both TLS and TM require similar underlying support. In the paper, we present SeTM (Sequential Transactional Memory), a hardware enhanced TM system which supports TLS at minor extra cost. Signature is an effective way to buffer speculative states in TM and TLS. But it cripples TM and TLS performance due to its false-positive in terms of conflict detection, especially for conflict-intensive TLS. SeTM adopts R/W bits and signature concurrently to ameliorate this bad influence. Additionally, SeTM introduces fast rollback mechanism, which provides fast abort recovery for eager log-based HTM and TLS. The most important contribution of SeTM is conflict-tolerant mechanism, which tolerates some ambiguous data conflicts in TLS. Six representative benchmarks have been adopted to evaluate our model. Our experimental results show that our scheme improves the execution performance of most tested codes at a modest hardware cost. For a set of important scientific loops, we report the highest speedup of 6.5 with 15 cores. Besides, experimental results also show good scalability of SeTM system.
Frequent loop detection using efficient non-intrusive on-chip hardware

Dynamic software optimization methods are becoming increasingly popular for improving software performance and power. The first step in dynamic optimization consists of detecting frequently executed code, or "critical regions. " Previous critical region detectors have been targeted to desktop processors. We introduce a critical region detector targeted to embedded processors, with the unique features of being very size and power efficient, and being completely non-intrusive to the software's execution - features needed in timing-sensitive embedded systems. Our detector not only finds the critical regions, but also determines their relative frequencies, a potentially important feature for selecting among alternative dynamic optimization methods. Our detector uses a tiny cache coupled with a small amount of logic. We provide results of extensive explorations across seventeen embedded system benchmarks. We show that highly accurate results can be achieved with only a 0.02% power overhead and acceptable size overhead. Our detector is currently being used as part of a dynamic hardware/software partitioning approach, but is applicable to a wide-variety of situations.
Mobile Music Business Models in Asia's Emerging Markets

In the telecom business, there has been a heavy competition from Internet, media and handset vendors companies. These over-the-top (OTT) players offer compiling telecom services, cause a transformation in the telecom business ecosystem, and the most challenging services posed here are media services. China, India and Indonesia, as world’s emerging markets in Asia, are predicted to take the largest share in the global mobile traffic explosion by 2015. It is critical for mobile network operators (MNOs) in this region to explore strategy for mobile media services, as mobile broadband is likely preferred compared to fixed broadband. In this paper, we analyze and compare mobile music business models used in these markets and structure the relation models between the key actors, using Actors, Relations and Business Activities (ARA) model. We present the economic models that are emerging, and an insight of why and how these multitudes actors are betting on currently. We found that the MNOs generally have a much stronger position compared to their counterparts in the developed markets, and the personalization services, like ring-back tone, are still a huge success. The actors tend to deliver the services by their own, rather than to collaborate in a horizontal business setting.
Modeling Wearable Bend Sensor Behavior for Human Motion Capture

The possibilities offered by variable resistance bend sensors, applied as wearable devices on body garments, to recover human joint bend angles for body segment movement tracking, have been investigated, underlying their advantages and drawbacks in real-time applications. Due to their pliability, sensitivity, and cheapness, they could be a valid alternative to movement analysis systems, based on optoelectronic devices or inertial electronic sensors. This paper suggests a new method for sensor characterization under fast bend and extension movements, to extract few parameters of a synthetic model, which provide to the users the chance to foresee their electrical performance in different applications. The sensor and their extracted models were applied to register the human knee rotation during a gait cycle, either at slow speed (83 deg/s) for a walking pattern at 5 km/h, and at high speed (650 deg/s) for a running pattern of a sprinter at 10 m/s, and finally the finger joint rotations at their maximum angular velocity (900 deg/s). This was done for a twofold purpose: from one hand, to assess the model capability to predict the sensor performance, tracking human body segment rotations at different speed, without the need of measurement; from the other hand, to recover in real time the actual sensor rotation from its resistance measurement, especially in high speed applications, where its response is distorted. With this technique, the mean error decreases from 22.5° to 3.7° in the worst case.
Collage technique may provide new perspectives for Alzheimer patients by exploring messages from their inner world

Although the collage art technique has been introduced as a psychotherapeutic method, it has not been fully applied in dementia. Objectives To analyze characteristics of the collage articles produced by patients with Alzheimer’s disease (AD). Methods Twenty AD patients were asked to select and place several clippings as they wished. The MMSE was used for cognitive assessments. Results Simplification and poor organization in their articles were found. The themes of one patient were found to change according to behavior. We discussed the images of the articles, especially spiritual images in the early stage and family images in the later stage. Conclusions We concluded that the collage technique could provide new perspectives for dementia patients by exploring messages from their inner world.
Polynomial algorithms for multiple processor agreement

Reaching agreement in a distributed system while handling malfunctioning behavior is a central issue for reliable computer systems. All previous algorithms for reaching the agreement required an exponential number of messages to be sent, with or without authentication. We give polynomial algorithms for reaching (Byzantine) agreement, both with and without the use of authentication protocols. We also prove that no matter what kind of information is exchanged, there is no way to reach agreement with fewer than t+1 rounds of exchange, where t is the upper bound on the number of faults.
Mesh Saliency Analysis via Local Curvature Entropy

We present a novel approach for estimating mesh saliency. Our method is fast, flexible, and easy to implement. By applying the well-known concept of Shannon entropy to 3D mesh data, we obtain an efficient method to determine mesh saliency. Comparing our method to the most recent, state-of-the-art approach, we show that results of at least similar quality can be achieved within a fraction of the original computation time. We present saliency-guided mesh simplification as a possible application.