Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi Protocol Active Messages on a Cluster of SMP

Cluster of multiprocessors, or Clumps, promise to be the supercomputers of the future, but obtaining high performance on these architectures requires an understanding of interactions between the multiple levels of interconnection. In this paper, we present the first multi-protocol implementation of a lightweight message layer-a version of Active Messages-II running on a cluster of Sun Enterprise 5000 servers connected with Myrinet. This research brings together several pieces of high-performance interconnection technology: bus backplanes for symmetric multiprocessors, low-latency networks for connections between machines, and simple, user-level primitives for communication. The paper describes the shared memory message-passing protocol and analyzes the multi-protocol implementation with both microbenchmarks and Split-C applications. Three aspects of the communication layer are critical to performance: the overhead of cache-coherence mechanisms, the method of managing concurrent access, and the cost of accessing state with the slower protocol. Through the use of an adapative polling strategy, the multi-protocol implementation limits performance interactions between the protocols, delivering up to 160 MB/s of bandwidth with 3.6 microsecond end-to-end latency. Applications within an SMP benefit from this fast communication, running up to 75% faster than on a network of uniprocessor workstations. Applications running on the entire Clump are limited by the balance of NIC's to processors in our system, and are typically slower than on the NOW. These results illustrate several potential pitfalls for the Clumps architecture.
Superelliptical insert gradient coil with a field‐modifying layer for breast imaging

Many MRI applications such as dynamic contrast‐enhanced MRI of the breast require high spatial and temporal resolution and can benefit from improved gradient performance, e.g., increased gradient strength and reduced gradient rise time. The improved gradient performance required to achieve high spatial and temporal resolution for this application may be achieved by using local insert gradients specifically designed for a target anatomy. Current flat gradient systems cannot create an imaging volume large enough to accommodate both breasts; further, their gradient fields are not homogeneous, dropping off rapidly with distance from the gradient coil surface. To attain an imaging volume adequate for bilateral breast MRI, a planar local gradient system design has been modified into a superellipse shape, creating homogeneous gradient volumes that are 182% (Gx), 57% (Gy), and 75% (Gz) wider (left/right direction) than those of the corresponding standard planar gradient. Adding an additional field‐modifying gradient winding results in an additional improvement of the homogeneous gradient field near the gradient coil surface over the already enlarged homogeneous gradient volumes of the superelliptical gradients (67%, 89%, and 214% for Gx, Gy, and Gz respectively). A prototype y‐gradient insert has been built to demonstrate imaging and implementation characteristics of the superellipse gradient in a 3 T MRI system. Magn Reson Med, 2011. © 2010 Wiley‐Liss, Inc.
PSGO: Particle Swarm Gravitation Optimization Algorithm

Particle swarm optimization (PSO) is the most well known of the swarm-based intelligence algorithms. However, the PSO converges prematurely, which rapidly decreases the population diversity, especially when approaching local optima. To improve the diversity of the PSO, we here propose a memetic algorithm called particle swarm gravitation optimization (PSGO). After a specific number of iterations, some individuals selected from the PSO and GSA systems are exchanged by the roulette wheel approach. Finally, to increase the diversities of the PSO and GSA, we introduce a diversity enhancement operator, which is inspired by the crossover operator used in differential evolution algorithms. In evaluations of five benchmark functions, the PSGO significantly outperformed the PSO and Cuckoo search and yielded a superior performance to the GSA of most of instances and computation times. 8
FURTHER DEVELOPMENTS IN IONOSPHERIC MITIGATION OF REPEAT-PASS INSAR DATA

The National Research Council (NRC) conducted a Decadal Survey of Earth Sciences [1] for NASA, and formulated a chronological plan for critical Earth Science missions to be flown over the next decade. The Survey recommended that NASA proceed with a number of missions immediately, one of which was called DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), comprising both polarimetric a L-band radar operating as a repeat-pass interferometer and a multiple-beam lidar. These sensors will measure surface deformation for understanding natural hazards and climate and vegetation structure for understanding ecosystem health. NASA has directed the Jet Propulsion Laboratory and Goddard Space Flight Center to conduct formulation trade studies to construct a feasible design that meets these science objectives within the programmatic constraints. These studies are well under way, and key performance and technical issues are being identified and addressed.
Adaptive Decision Feedback Space–Time Equalization With Generalized Sidelobe Cancellation

In wireless communications, cochannel interference (CCI) and intersymbol interference (ISI) are two main factors that limit system performance. Conventionally, a beamformer is used to reduce CCI, whereas an equalizer is used to compensate for ISI. These two devices can be combined into one as space-time equalizer (STE). A training sequence is usually required to train the STE prior to its use. In some applications, however, spatial information corresponding to a desired user is available, but the training sequence is not. In this paper, we propose an adaptive decision feedback STE to cope with this problem. Our scheme consists of an adaptive decision feedback generalized sidelobe canceller (DFGSC), a blind decision feedback equalizer (DFE), and a channel estimator. Due to the feedback operation, the proposed DFGSC is not only superior to the conventional generalized sidelobe canceller but also robust to multipath channel propagation and spatial signature error. Theoretical results are derived for optimum solutions, convergence behavior, and robustness properties. With the special channel-aided architecture, the proposed blind DFE can reduce the error propagation effect and be more stable than the conventional blind DFE. Simulation results show that the proposed STE is effective in mitigating both CCI and ISI, even in severe channel environments.
Automatic Detection of Epileptiform Discharges in the EEG

The diagnosis of epilepsy generally includes a visual inspection of EEG recorded data by the Neurologist, with the purpose of checking the occurrence of transient waveforms called interictal epileptiform discharges. These waveforms have short duration (less than 100 ms), so the inspection process is usually time-consuming, particularly for ambulatory long term EEG records. Therefore, an automatic detection system of epileptiform discharges can be a valuable tool for a Neurology service. The proposed approach is the development of a multi stage detection algorithm, which processes the complete EEG signals and applies decision criteria to selected waveforms. It employs EEG analysis techniques such as Wavelet Transform and Mimetic Analysis, complemented with a classification based on Fuzzy Logic. In order to evaluate the algorithm's performance, data were collected from several epileptic patients, with epileptiform activity marked by a Neurologist. The average values obtained for both Sensitivity and Specificity were respectively higher than 80 and 70 percent.
Fast Local Mapping For Mobile Robots

The focus of academic research to map building for mobile robots lies most often on the algorithms that use accurate sensor data, obtained by e.g. a laser scanner, to reduce uncertainty about movement, thereby facilitating the construction of large consistent maps. This thesis describes the research that is done to the possibilities concerning fast, local map building using inaccurate sensors. The characteristics of several sensors are analysed, both individually and together in a reconstructed setup and algorithms are evaluated to study their potential for dealing with noisy sensors in real time. A simulator is written in C++ to integrate these matters and a robot platform is constructed to test the sensors in combination with the algorithm in a real life application.
Human Gesture Analysis Using Multimodal Features

Human gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and PLS is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.
Context-aware Search for Personal Information Management Systems

With the fast growth of disk capacity in personal computers, keyword search over personal data (a.k.a. desktop search) is becoming increasingly important. Nonetheless, desktop search has been shown to be more challenging than traditional Web search. Modern commercial Web search engines heavily rely on structural information (i.e., hyperlinks betweenWeb pages) to rank their search results. However, such information is not available in the circumstance of desktop search. Therefore, state-of-the-art desktop search systems such as Google Desktop Search usually leverage pure textbased ranking approaches (e.g., TF-IDF), which often fail to give promising rankings due to the misinterpretation of user intention. We observed that in desktop search, the semantics of keyword queries are often context-aware, i.e., they are related to the current activity state (e.g., writing a paper, navigating a website, etc.) of the user. In this paper, we present a novel context-aware search framework by taking this activity information into consideration. Specifically, we use Hidden Markov Model (HMM) to capture the relationships between user’s access actions (e.g., opening/closing files, sending/receiving emails, etc.) and activity states. The model is learned from user’s past access history and is used to predict user’s current activity upon the submission of some keyword query. We further propose a ranking scheme with this predicted context information incorporated. Experimental evaluation demonstrates both the effectiveness of the proposed context-aware search method and the enhancement to user’s search experience.
Osmolality-Dependent Relocation of Penicillin-Binding Protein PBP2 to the Division Site in Caulobacter crescentus

ABSTRACT The synthesis of the peptidoglycan cell wall is carefully regulated in time and space. In nature, this essential process occurs in cells that live in fluctuating environments. Here we show that the spatial distributions of specific cell wall proteins in Caulobacter crescentus are sensitive to small external osmotic upshifts. The penicillin-binding protein PBP2, which is commonly branded as an essential cell elongation-specific transpeptidase, switches its localization from a dispersed, patchy pattern to an accumulation at the FtsZ ring location in response to osmotic upshifts as low as 40 mosmol/kg. This osmolality-dependent relocation to the division apparatus is initiated within less than a minute, while restoration to the patchy localization pattern is dependent on cell growth and takes 1 to 2 generations. Cell wall morphogenetic protein RodA and penicillin-binding protein PBP1a also change their spatial distribution by accumulating at the division site in response to external osmotic upshifts. Consistent with its ecological distribution, C. crescentus displays a narrow range of osmotolerance, with an upper limit of 225 mosmol/kg in minimal medium. Collectively, our findings reveal an unsuspected level of environmental regulation of cell wall protein behavior that is likely linked to an ecological adaptation.
Stories We Tell: Fragmentation and Convergence in Communication Disciplinary History

The disciplinary status of communication is hindered by the lack of a unified history. While there is a mostly agreed-on history of the development of various types of communication theory, that history is confounded by the histories of the two areas of study—speech and journalism—and eventually became prominent in communication research. This article recounts the speech story, the journalism story, and the communication story and offers some direction for a history that accounts for communication's disciplinary status while still recognizing the heritage of speech and journalism.
Technical Advances and Pitfalls in Head and Neck Radiotherapy

Intensity Modulated Radiotherapy (IMRT) is the standard of care in the treatment of head and neck squamous cell carcinomas (HNSCC) based on level 1 evidence. Technical advances in radiotherapy have revolutionized the treatment of HNSCC, with the most tangible gain being a reduction in long term morbidity. However, these benefits come with a serious and sobering price. Today, there is a greater chance of missing the target/tumor due to uncertainties in target volume definition by the clinician that is demanded by the highly conformal planning process involved with IMRT. Unless this is urgently addressed, our patients would be better served with the historically practiced non conformal radiotherapy, than IMRT which promises lesser morbidity. Image guided radiotherapy (IGRT) ensures the level of set up accuracy warranted to deliver a highly conformal treatment plan and should be utilized with IMRT, where feasible. Proton therapy has a theoretical physical advantage over photon therapy due to a lack of “exit dose”. However, clinical data supporting the routine use of this technology for HNSCC are currently sparse. The purpose of this article is to review the literature, discuss the salient issues and make recommendations that address the gaps in knowledge.
Early detection of postoperative acute kidney injury by Doppler renal resistive index in cardiac surgery with cardiopulmonary bypass.

BACKGROUND Acute kidney injury (AKI) is common after cardiac surgery, affecting outcome. Early detection of an AKI marker is likely to speed diagnosis and implementation of measures to preserve renal function. In septic shock and unselected ventilated subjects, an increased Doppler renal resistive index (RRI) is a predictor of AKI. This study aims to determine whether RRI would act similarly in the postoperative setting of cardiac surgery. METHODS This study included 65 subjects aged more than 60 yr undergoing elective heart surgery with cardiopulmonary bypass (CPB) and at risk of AKI. All presented at least one AKI risk factor [arteritis, diabetes, or serum creatinine (sCr) clearance of 30-60 ml min(-1)] and were haemodynamically stable without arrhythmia. Doppler RRI was measured in the immediate postoperative period (POP) while subjects were ventilated and sedated. AKI was assessed when sCr increased 30% above the preoperative baseline. RESULTS Eighteen subjects developed AKI between days 1 and 4, with six requiring dialysis. RRI in the POP was increased in AKI [RRI: 0.79 (0.08) with AKI vs 0.68 (0.06) without AKI, P<0.001], correlating to AKI severity [0.68 (0.06) without AKI, 0.77 (0.08) with AKI but no dialysis, and 0.84 (0.03) with AKI and dialysis, P<0.001]. RRI was similar in subjects receiving catecholamines. RRI >0.74 in the POP predicted delayed AKI with high sensitivity and specificity (0.85 and 0.94, respectively). Multivariate analysis showed that AKI was associated with increased RRI and transfusion. CONCLUSIONS RRI used in the immediate POP after cardiac surgery with CPB enabled prediction of delayed AKI and anticipation of its severity.
System Dynamic Modeling of Plant Maintenance Strategy in Thailand

Although management often views maintenance work as only an expense, a proper maintenance strategy can reduce overall plant operation cost, boosting productivity and increasing plant uptime. This research studied the plant maintenance strategy and condition monitoring technology used in Thailand compared with typical and benchmarking plants in United States. Structured interviews with respondents working in power generation, petrochemical, refinery and gas separation plants in Thailand were compared with the practice of typical and benchmarking plants in the United States, in addition to related information on condition monitoring technology. The study employed a system dynamics approach to model a generic plant maintenance system with collected data from interviews guiding appropriate inputs to the model. Plant uptime and maintenance cost were used as the relevant outputs. The results suggest that industrial plants in Thailand should reduce preventive maintenance levels and increase predictive maintenance level to better meet the benchmark and increase plant uptime and reduce maintenance cost. The simulation model can be a starting point for particular plants to study optimal plant maintenance behavior and can be combined with actual plant data to further refine the model.
Inferior alveolar canal course: a radiographic study.

OBJECTIVES To describe the morphology and course of the inferior alveolar canal (IAC) as it appears in digital panoramic radiographs. MATERIALS AND METHODS Three hundred and eighty-six digital rotational panoramic radiographs (OPG) were studied using the Clinview Software (6.1.3.7 version, Instrumentarium). Among the 386 radiographs, 86 radiographs with 5-mm steel balls were used to calculate the magnification. RESULTS The average magnification of radiographs in this study was 7.24+/-7.55%. The course of IAC as seen in the panoramic radiograph may be classified into four types: (1) linear curve, 12.75%, (2) spoon-shaped curve, 29.25%, (3) elliptic-arc curve, 48.5%, and (4) turning curve, 9.5%. On panoramic radiographs, the IAC appeared closest to the inferior border of the mandible in the region of the first molar. In relation to the teeth, on panoramic radiographs, the IAC appeared closest to the distal root tip of the third molar and furthest from the mesial root tip of the first molar. CONCLUSION In the OPG, there are four types of IAC: linear, spoon shape, elliptic-arc, and turning curve. The data found in the study may be useful for dental implant, mandibule surgery, and dental anesthesia. The limitations of the panoramic radiograph in depicting the true three-dimensional (3D) morphology of the IAC are recognized, computed tomography (CT) and cone beam (CB)3D imaging being more precise.
Transparency for computer synthesized images

Simple transparency algorithms which assume a linear transparency over an entire surface are the type most often employed to produce computer synthesized images of transparent objects with curved surfaces. Although most of the images created with these algorithms do give the impression of transparency, they usually do not look realistic. One of the most serious problems is that the intensity of the light that is transmitted through the objects is generally not proportional to the amount of material through which it must pass. Another problem is that the image seen behind the objects is not distorted as would naturally occur when the light is refracted as it passes through a material of different density. Use of a non-linear transparency algorithm can provide a great improvement in the realism of an image at a small additional cost. Making the transparency proportional to the normal to the surface causes it to decrease towards the edges of the surface where the path of the light through the object is longer. The exact simulation of refraction, however, requires that each sight ray be individually traced from the observer, through the picture plane and through each transparent object until an opaque surface is intersected. Since the direction of the ray would change as each material of differing optical density was entered, the hidden surface calculations required would be very time consuming. However, if a few assumptions are made about the geometry of each object and about the conditions under which they are viewed, a much simplier algorithm can be used to approximate the refractive effect. This method proceeds in a back to front order, mapping the current background image onto the next surface, until all surfaces have been considered.
The Relationship between Denominational Affiliation and Spiritual Health among Weekly-Churchgoing 13- to 15-Year-Old Adolescents in England and Wales

THIS PAPER DRAWS on John Fisher's formative definition of spiritual health as comprising good relationships within four domains (the personal, the communal, the environmental and the transcendental) and uses the operationalization of these constructs proposed by Francis and Robbins (2005). Comparisons are made between the responses of five groups of 13- to 15-year-olds who report weekly church attendance: 1,549 Anglicans, 1,458 Roman Catholics, 830 members of one of the Free Churches, 212 members of one of the Pentecostal churches, and 212 Jehovah's Witnesses. The data demonstrate significant variations in the levels of spiritual health reported by weekly churchgoers according to denominational affiliation. The conclusion is drawn that denominational affiliation needs to be taken into account alongside frequency of church attendance in constructing a view of the relationship between Christian practice and spiritual health during the adolescent years.
Effective sentiment classification based on words and word senses

Sentiment analysis is an area which has gained a lot of attention in recent years, mainly due to the many practical applications it supports and a growing demand for such applications. Previous work has shown that word senses carry potentially useful information for sentiment analysis. However due to limitations in the existing methods to assign senses to words in open-domain texts, this word sense based approach has not demonstrated significant advantages over the traditional term-based approaches. Also most sentiment lexicons consider limited polarity values (usually 2 or 3), therefore may convey very little information for distinguishing between a sentence that is positive and one that is negative. This paper proposes to address these limitations by making use of term-based sentiment lexicons, by increasing the number of possible polarity values considered in lexicons, and by processing the sentences for local negation. Finally we propose a novel sentiment representation generated by merging the word features with the developed sentiment features in a single sequence. Our evaluations show that and our proposed improvements effectively increased the quality of the sentiment representations. However, these sentiment representations are still behind the best factored representations which exclude the sentiment features.