Miracle-dz/UniFAR-FTUs huggingface dataset:
Thromboendarterectomy for Total Occlusion of the Internal Carotid Artery: A Reappraisal of Risks, Success Rate and Potential Benefits

Forty consecutive patients undergoing thromboendarterectomy for total internal carotid artery occlusion were studied in an attempt to determine a) whether careful case selection could be expected to reduce future postoperative mortality and morbidity, b) whether the achieved patency rate justified early operation and c) whether patients in whom patency was restored and maintained had a better long-term prognosis. The results show that a group of patients can be selected that will have low postoperative mortality and morbidity. The success rate for restoration of blood flow is high, particularly if the operation is performed soon after occlusion. The long-term prognosis in patients in whom patency of the internal carotid artery is restored and maintained appears to be better than in those with persistent occlusion of the carotid artery.
Bridging low-level features and high-level semantics via fMRI brain imaging for video classification

The multimedia content analysis community has made significant effort to bridge the gap between low-level features and high-level semantics perceived by human cognitive systems such as real-world objects and concepts. In the two fields of multimedia analysis and brain imaging, both topics of low-level features and high level semantics are extensively studied. For instance, in the multimedia analysis field, many algorithms are available for multimedia feature extraction, and benchmark datasets are available such as the TRECVID. In the brain imaging field, brain regions that are responsible for vision, auditory perception, language, and working memory are well studied via functional magnetic resonance imaging (fMRI). This paper presents our initial effort in marrying these two fields in order to bridge the gaps between low-level features and high-level semantics via fMRI brain imaging. Our experimental paradigm is that we performed fMRI brain imaging when university student subjects watched the video clips selected from the TRECVID datasets. At current stage, we focus on the three concepts of sports, weather, and commercial-/advertisement specified in the TRECVID 2005. Meanwhile, the brain regions in vision, auditory, language, and working memory networks are quantitatively localized and mapped via task-based paradigm fMRI, and the fMRI responses in these regions are used to extract features as the representation of the brain's comprehension of semantics. Our computational framework aims to learn the most relevant low-level feature sets that best correlate the fMRI-derived semantics based on the training videos with fMRI scans, and then the learned models are applied to larger scale test datasets without fMRI scans for category classifications. Our result shows that: 1) there are meaningful couplings between brain's fMRI responses and video stimuli, suggesting the validity of linking semantics and low-level features via fMRI; 2) The computationally learned low-level feature sets from fMRI-derived semantic features can significantly improve the classification of video categories in comparison with that based on original low-level features.
User learning and performance with bezel menus

Touchscreen phones tend to require constant visual attention, thus not allowing eyes-free interaction. For users with visual impairment, or when occupied with another task that requires a user's visual attention, these phones can be difficult to use. Recently, marks initiating from the bezel, the physical touch-insensitive frame surrounding a touchscreen display, have been proposed as a method for eyes-free interaction. Due to the physical form factor of the mobile device, it is possible to access different parts of the bezel eyes-free. In this paper, we first studied the performance of different bezel menu layouts. Based on the results, we designed a bezel-based text entry application to gain insights into how bezel menus perform in a real-world application. From a longitudinal study, we found that the participants achieved 9.2 words per minute in situations requiring minimal visual attention to the screen. After only one hour of practice, the participants transitioned from novice to expert users. This shows that bezel menus can be adopted for realistic applications.
Fabrication of Photonic/Microfluidic Integrated Devices Using an Epoxy Photoresist

Using a single layer of SU-8 photoresist to fabricate optical waveguide cores and microfluidic channels on Pyrex glass is an ideal way to achieve photonic/microfluidic integration on a single chip. To address the problem of poor bonding, a thin nanoscale intermediate polymer layer was applied to reduce the stress generated from the material processing while maintaining strong adhesion between the patterning polymer layer and Pyrex. It was found that a 186-600 nm thick intermediate layer of a specialty epoxy photoresist effectively served the purpose without deteriorating the optical performance of the involved waveguides. Quality photonic/microfluidic integrated devices with satisfied optical performance were fabricated.
Understanding Checkpointing Overheads on Massive-Scale Systems: Analysis of the IBM Blue Gene/P System

Providing fault tolerance in high-end petascale systems, consisting of millions of hardware components and complex software stacks, is becoming an increasingly challenging task. Checkpointing continues to be the most prevalent technique for providing fault tolerance in such high-end systems. Considerable research has focussed on optimizing checkpointing; however, in practice, checkpointing still involves a high-cost overhead for users. In this paper, we study the checkpointing overhead seen by various applications running on leadership-class machines like the IBM Blue Gene/P at Argonne National Laboratory. In addition to studying popular applications, we design a methodology to help users understand and intelligently choose an optimal checkpointing frequency to reduce the overall checkpointing overhead incurred. In particular, we study the Grid-Based Projector-Augmented Wave application, the Carr-Parrinello Molecular Dynamics application, the Nek5000 computational fluid dynamics application and the Parallel Ocean Program application—and analyze their memory usage and possible checkpointing trends on 65,536 processors of the Blue Gene/P system.
Taming the Flying Cable Monster: A Topology Design and Optimization Framework for Data-Center Networks

Data-center network designers now have many choices for high-bandwidth, multi-path network topologies. Some of these topologies also allow the designer considerable freedom to set parameters (for example, the number of ports on a switch, link bandwidths, or switch-to-switch wiring patterns) at design time. This freedom of choice, however, requires the designer to balance among bandwidth, latency, reliability, parts cost, and other real-world details. Designers need help in exploring this design space, and especially in finding optimal network designs. We describe the specific challenges that designers face, and we present Perseus, a framework for quickly guiding a network designer to a small set of candidate designs. We identify several optimization problems that can be accommodated within this framework, and present solution algorithms for many of these problems.
An enhanced segmentation of blood vessels in retinal images using contourlet

Retinal images acquired using a fundus camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.
Physician-patient communication about overactive bladder: Results of an observational sociolinguistic study

Introduction Overactive bladder (OAB) and urinary incontinence are common problems that have significant impact on quality of life (QOL). Less than half of sufferers seek help from their physicians; many who do are dissatisfied with treatment and their physicians’ understanding of their problems. Little is known about the sociolinguistic characteristics of physician-patient communication about OAB in community practice. Methods An IRB-approved observational sociolinguistic study of dialogues between patients with OAB and treating physicians was conducted. Study design included semi-structured post-visit interviews, post-visit questionnaires, and follow-up phone calls. Conversations were analyzed using techniques from interactional sociolinguistics. Results Communication was physician- rather than patient-centered. Physicians spoke the majority of words and 83% of questions were closed-ended. The impact of OAB on QOL and concerns about and adherence to treatment were infrequently addressed by physicians, who were poorly aligned with patients in their understanding. These topics were addressed more frequently when open-ended questions successfully eliciting elaborated responses were used in ask-tell-ask or ask-tell sequences. Discussion Clinical dialogue around OAB is physician-centered; topics critical to managing OAB are infrequently and inadequately addressed. The use of patient-centered communication is correlated with more discussion of critical topics, and thus, more effective management of OAB.
An AODE-based intrusion detection system for computer networks

Detecting anomalous traffic on the Internet has remained an issue of concern for the community of security researchers over the years. Advances in computing performance, in terms of processing power and storage, have allowed the use of resource-intensive intelligent algorithms, to detect intrusive activities, in a timely manner. Naïve Bayes is a statistical inference learning algorithm with promise for document classification, spam detection and intrusion detection. The attribute independence issue associated with Naïve Bayes has been resolved through the development of the Average One Dependence Estimator (AODE) algorithm. In this paper, we propose the application of AODE for intrusion detection. The performance of the proposed scheme is studied and analyzed on the KDD-99 intrusion benchmark data set. With a detection rate of 99.7%, AODE outperformed Naïve Bayes, which reported a detection rate of 97.3%, and a larger number of false positives.
Comment-based multi-view clustering of web 2.0 items

Clustering Web 2.0 items (i.e., web resources like videos, images) into semantic groups benefits many applications, such as organizing items, generating meaningful tags and improving web search. In this paper, we systematically investigate how user-generated comments can be used to improve the clustering of Web 2.0 items. In our preliminary study of Last.fm, we find that the two data sources extracted from user comments -- the textual comments and the commenting users -- provide complementary evidence to the items' intrinsic features. These sources have varying levels of quality, but we importantly we find that incorporating all three sources improves clustering. To accommodate such quality imbalance, we invoke multi-view clustering, in which each data source represents a view, aiming to best leverage the utility of different views. To combine multiple views under a principled framework, we propose CoNMF (Co-regularized Non-negative Matrix Factorization), which extends NMF for multi-view clustering by jointly factorizing the multiple matrices through co-regularization. Under our CoNMF framework, we devise two paradigms -- pair-wise CoNMF and cluster-wise CoNMF -- and propose iterative algorithms for their joint factorization. Experimental results on Last.fm and Yelp datasets demonstrate the effectiveness of our solution. In Last.fm, CoNMF betters k-means with a statistically significant F1 increase of 14%, while achieving comparable performance with the state-of-the-art multi-view clustering method CoSC (Co-regularized Spectral Clustering). On a Yelp dataset, CoNMF outperforms the best baseline CoSC with a statistically significant performance gain of 7%.
Energy Expenditure Ranges and Muscular Work Grades

This paper is based on the findings of a field study which was planned to ascertain by metabolic measurement the rates of energy expenditure of men and women on productive effort at work in modern factories. The investigation which is described was carried out during a period of peace-time full employment, mainly in factories associated with the Slough Industrial Health Service in which a nutritional survey of the calorie intake of male operatives had been made by the Ministry of Health and the Medical Research Council in 1952. The rates of energy expenditure of 70 men and 54 women in 27 occupational groups were measured by indirect calorimetric methods. On the basis of the criteria for the classification of work according grades to its heaviness, adopted by the Factory Department of the Ministry of Labour, muscular work grades have been ascribed to the occupations studied. From the distribution of 390 metabolic measurements, ranges of energy expenditure have been computed for occupations classed as sedentary, light, moderate, heavy, or very heavy, Observation of recurrent phase variations in types of productive effort in the work-cycle indicated that wider work grades, such as light-to-moderate or moderate-to-heavy, are needed to cover the energy expenditure rates of men and women in many occupations. The data obtained in this study have enabled a table termed the “Slough Scales” to be compiled giving ranges of energy expenditure and pulmonary ventilation rates for the various work grades ascribed to occupations. The mean rates of energy expenditure of 257 workers (in industries in different parts of England and Scotland) which have been calculated from data published by other investigators have been found to fall within the ranges specified in these scales for the work grades of their occupations. It is felt, therefore, that the Slough Scales represent a reasonably true appraisal of the relation between the Ministry of Labour occupational work grades and the rates of energy expenditure of men and women at work under environmental and management conditions which usually appertain in the United Kingdom.
A variational analysis of shape from specularities using sparse data

Looking around in our every day environment, many of the encountered objects are specular to some degree. Actively using this fact when reconstructing objects from image sequences is the scope of the shape from specularities problem. One reason why this problem is important is that standard structure from motion techniques fail when the object surfaces are specular. Here this problem is addressed by estimating surface shape using information from the specular reflections. A specular reflection gives constraints on the surface normal. The approach differs significantly from many earlier shapes from specularities methods since the normal data used is sparse. The main contribution is to give a solid foundation for shape from specularities problems. Estimation of surface shape using reflections is formulated as a variational problem and the surface is represented implicitly using a level set formulation. A functional incorporating all surface constraints is proposed and the corresponding level set motion PDE is explicitly derived. This motion is then proven to minimize the functional. As a part of this functional a variational approach to normal alignment is proposed and analyzed. Also novel methods for implicit surface interpolation to sparse point sets are presented together with a variational analysis. Experiments on both real and synthetic data support the proposed method.
Influences of Deviatoric Stress on the Soil-Water Characteristic Curve

The soil-water characteristic curve (SWCC) is one of the major research subjects in unsaturated soil mechanics. To study the influence of deviatoric stress on the SWCC of an unsaturated soil, a series of triaxial drained shear tests by controlling constant net mean stress and suction were conducted. It was found that the SWCC was dependent on deviatoric stress. A unified SWCC equation was proposed including not only water content and suction, but also net mean stress and deviatoric stress.
Filler-matrix interaction in solid-state foaming of composite foams

Solid-state foaming is a relatively new process for producing closed-cell thermoset foams starting from powders. In this study, the possibility of introducing nanoclay into epoxy foams by solid-state foaming was investigated. The nanoclay was found to affect the foaming efficiency and the foam density; even if large nanoclay aggregates are present in the foams, for a small range of filler content (2.5—3 wt%), the mechanical properties are positively influenced, as shown by specific compressive toughness which attains a maximum value. Electron microscope observations provided important information on the dependence of the cell size on the filler percentage, and the presence of a critical size (about 5 μm) of nanoclay aggregates, below which they are coherent with the matrix.
SIRT1, Is It a Tumor Promoter or Tumor Suppressor?

SIRT1 has been considered as a tumor promoter because of its increased expression in some types of cancers and its role in inactivating proteins that are involved in tumor suppression and DNA damage repair. However, recent studies demonstrated that SIRT1 levels are reduced in some other types of cancers, and that SIRT1 deficiency results in genetic instability and tumorigenesis, while overexpression of SIRT1 attenuates cancer formation in mice heterozygous for tumor suppressor p53 or APC. Here, I review these recent findings and discuss the possibility that activation of SIRT1 both extends lifespan and inhibits cancer formation.
Thermal Sensor Allocation and Placement for Reconfigurable Systems

Temperature monitoring using thermal sensors is an essential tool for evaluating the thermal behavior and sustaining the reliable operation in high-performance and high-power systems. With current technology scaling and integration trends timely and accurate detection of localized heating will be evermore important. In this work, we address the creation of a resource efficient sensor infrastructure for computing systems that are of regular nature, such as logic array-based computing platforms. We propose algorithms to embed thermal sensors into a regular structure to minimize the number of sensors and determine sensor locations required to maintain a given accuracy in temperature sensing for a given design. Our algorithms are tailored for minimal usage of thermal sensors to suit a variety of architectural conditions. For programmable logic arrays the highly application-specific usage of the hardware resources leads to unpredictable thermal profiles. As a result, post-manufacture instantiation of thermal sensors is desired, which in turn demands the use of native hardware resources, which can be scarce. We demonstrate that using our techniques the number of sensors required to monitor a set of hotspots is reduced by 75% on an average, across different sizes of logic arrays for different hotspot distributions compared to a uniform distribution of sensors throughout the fabrics
Nonlinear output feedback controller design for tracking control of ODIN in wave disturbance condition

This paper presents the design of a nonlinear controller for tracking control of a spherical autonomous underwater vehicle (AUV), named as Omni-Directional Intelligent Navigator (ODIN) operating in shallow water area. When the AUV operates in shallow water environment, significant disturbance due to the wave motion will be introduced into the position and heading of the marine vehicles. It is critical to obtain the knowledge of the wave information or the wave induced disturbance information to reduce the reaction of the controller to this wave motion. In this paper, an observer is designed to estimate the shallow water wave motion, the low frequency motion and bias disturbance by using only the position and heading measurement. A nonlinear output feedback controller is derived based on the developed observer using the observer backstepping technique. The globally exponentially stability (GES) of the whole observer and controller system is proved be Lyapunov stability theory. A set of simulations is carried out to test the performance of the proposed observer and controller for tracking control of ODIN
Feasibility of rapid infusion of the initial dose of bevacizumab in patients with cancer.

PURPOSE Bevacizumab is a monoclonal antibody against vascular endothelial growth factor (VEGF) widely used in clinical oncology. Bevacizumab is commonly co-adminis- tered with chemotherapy. It is recommended that the first infusion of the antibody last 90 min, the second 60 and all subsequent 30 min. Since there is no clear rationale for the proposed schedule of administration, our study assessed the feasibility of a 30 min initial infusion. METHODS Cancer patients eligible for de novo bevacizumab treatment were enrolled. All patients received standard bevacizumab dose of 5, 7.5 or 10 mg/kg according to the indication, diluted in 250 ml normal saline, as a 30-min intravenous infusion. RESULTS Thirty two patients were enrolled: male 18, female 14, median age 58 years, range 42-78. Oncologic diagnosis: lung cancer 16, colorectal 4, breast 3, ovarian 7, renal 2. All patients tolerated the infusion well. No hypersensitivity reactions were noted. Mean systolic and diastolic blood pressures were 122 and 73 mm/Hg respectively prior to the infusion and 125 and 75 mm/Hg 15 min after the infusion (p=0.3). During the observation period of 1 hour, blood pressure did not change. Transient grade 3 systolic hypertension was noted in 1 patient, with spontaneous regression in 45 min. CONCLUSION Rapid administration of bevacizumab in 30 min, rather than the recommended in the package insert 90 min is feasible and safe. Such a practice limits the time of confinement in the treatment area to patients' satisfaction and would result in cost savings by reducing health resource utilization.
Response characteristics of a viscoelastic gel under the co-action of sound waves and an electric field

We design a flexible sound tunable sandwiched panel structure, which is composed of a nanoelectrorheological gel layer and two conductive rubber sheets, and experimentally investigate the tunable behaviors of the sound transmitted through the panel. For the frequency range of 380–500 Hz the transmitted sound pressure level (SPL) decreases with the electric field strength Ee, while at about 550–650 Hz the SPL increases with Ee. Within 500–550 Hz a hump appears and the hump apex shifts in the high frequency direction with increase of Ee. Besides this, the phase angle of the transmitted sound wave changes with Ee within these frequency ranges. The weight fraction of particles in the electrorheological gels also influences these observed tunable characteristics. The theoretical calculation based on a vibration–radiation model agrees with the experimental results, qualitatively. It is revealed that the electric field induced viscoelasticity change in the electrorheological gel and hence the vibration–radiation variation on the sandwiched panel is the origin of the phenomenon. The flexible composite electrorheological panel could be used in sound sensitive artificial skins or sound tunable actuators and has potential for use in robots and intelligent structures and systems.