Miracle-dz/UniFAR-FTUs huggingface dataset:
High Performance Relay Mechanism for MPI Communication Libraries Run on Multiple Private IP Address Clusters

We have been developing a Grid-enabled MPI communication library called GridMPI, which is designed to run on multiple clusters connected to a wide-area network. Some of these clusters may use private IP addresses. Therefore, some mechanism to enable communication between private IP address clusters is required. Such a mechanism should be widely adoptable, and should provide high communication performance. In this paper, we propose a message relay mechanism to support private IP address clusters in the manner of the Interoperable MPI (IMPI) standard. Therefore, any MPI implementations which follow the IMPI standard can communicate with the relay. Furthermore, we also propose a trunking method in which multiple pairs of relay nodes simultaneously communicate between clusters to improve the available communication bandwidth. While the relay mechanism introduces an one-way latency of about 25 musec, the extra overhead is negligible, since the communication latency through a wide area network is a few hundred times as large as this. By using trunking, the inter-cluster communication bandwidth can improve as the number of trunks increases. We confirmed the effectiveness of the proposed method by experiments using a 10 Gbps emulated WAN environment. When relay nodes with 1 Gbps NICs are used, the performance of most of the NAS Parallel Benchmarks improved proportional to the number of trunks. Especially, using 8 trunks, FT and IS are 4.4 and 3.4 times faster, respectively, compared with the single trunk case. The results showed that the proposed method is effective for running MPI programs over high bandwidth-delay product networks.
GCTrees: Garbage collecting snapshots

File-system snapshots have been a key component of enterprise storage management since their inception. Creating and managing them efficiently, while maintaining flexibility and low overhead, has been a constant struggle. Although the current state-of-the-art mechanism, hierarchical reference counting, performs reasonably well for traditional small-file workloads, these workloads are increasingly vanishing from the enterprise data center, replaced instead with virtual machine and database workloads. These workloads center around a few very large files, violating the assumptions that allow hierarchical reference counting to operate efficiently. To better cope with these workloads, we introduce GCTrees, a novel method of space management that uses concepts of block lineage across snapshots, rather than explicit reference counting. As a proof of concept, we create a prototype file system, gcext4, a modified version of ext4 that uses GCTrees as a basis for snapshots and copy-on-write. In evaluating this prototype analytically, we find that, though they have a somewhat higher overhead for traditional workloads, GCTrees have dramatically lower overhead than hierarchical reference counting for large-file workloads, improving by a factor of 34 or more in some cases. Furthermore, gcext4 performs comparably to ext4 across all workloads, showing that GCTrees impose minor cost for their benefits.
Transient Inability to Distinguish Between Faces: Electrophysiologic Studies

It is not known with certainty at which level of face processing by the cortex the distinction between a familiar and an unfamiliar face is made. Subdural electrodes were implanted under the fusiform gyrus of the right temporal lobe in a patient who developed an unusual inability to distinguish differences between faces as part of the epileptic aura (“all faces looked the same”). A cortical region located posterior to the epileptic focus was identified that exhibited a maximum evoked response to the presentation of facial images (N165), but not to objects, scenes, or character strings. Evoked potentials elicited by a variety of visual images indicated that any perturbation away from novel whole-face stimuli produced submaximal responses from this region of the right temporal lobe. Electrical stimulation of this region resulted in an impairment of face discrimination. It was found that presentation of familiar faces (grandmother, treating physician) produced a different response from that observed for novel faces. These observations demonstrate that within 165 msec of face presentation, and before the conscious precept of face familiarity has formed, this cortical region has already begun to distinguish between a familiar and an unfamiliar face.
Ray-tracing simulation and analysis of propagation for 3GPP high speed scenarios

In this paper, the propagation for 3GPP high speed train (HST) scenarios is studied both at 30 GHz and 3.5 GHz. Urban, cutting and viaduct scenarios are modeled and simulated by using 3GPP deployment configurations. The optimum direction of beam is suggested in order to achieve the best coverage. Propagation at 30 GHz and 3.5 GHz are compared in terms of received power and Doppler shift. The wideband path loss parameters are modeled, and suggestions are provided to guide high-data-rate HST communication system design.
Bayesian Community Detection : an application to a dynamic wild bird network PRS Transfer Report

Understanding how parts of a system interact, is as important as understanding the parts themselves [1]. In this work, we explore the idea of describing a system as a network, by mapping the web of interactions of its individual components to a mathematical graph. We thus seek to get insight on the overall system's form and function by examining the statistical and topological properties that arise from such a relational representation. In Chapter 1 of the present work, we provide an overview of how this paradigm has been used in modelling a wide range of complex systems in nature and technology, from protein interactions and animal populations to the World Wide Web and Social Media. After introducing the main concepts of network analysis in Chapter 1, we proceed by discussing how real-world networks differ from random graphs, as they possess a collection of unique properties such as community structure. Community structure is a prominent organisational scheme of complex networks, where sets of individual nodes are grouped together in tightly connected modules. We introduce this concept and discuss why identifying such latent node classes is a challenging inference task and a major research theme in contemporary network analysis literature. Chapter 1 concludes with a discussion of various fitness criteria for evaluating the quality of community partitions and a critical overview of many popular methodologies for community detection. In Chapter 2 we present our contribution to the community detection literature, by introducing a novel approach to extracting modules that overcomes the limitations of many popular existing methods. Our method addresses the issues of describing overlapping communities, defining node membership scores and possesses low computational overhead. We present our model formulation, which is based on finding the most probable community configuration that can account for our interaction data (network), given a set of prior assumptions. We then examine the module identification capabilities of our method on a range of artificial and real-world benchmark problems. The development of the aforementioned method is motivated by our future research work, which i is the modelling of a wild bird population in a social network context, by utilising a sparse stream of temporal observation data. In Chapter 3 we introduce our problem context, namely a data set of birds of the Great Tit (Parus Major) population at Wytham Woods, Oxford, which forms over the course of each year highly dynamic overlapping groups with frequent changes in composition …
The art of vaginal breech birth at term on all fours

Despite a shift in clinical practice favouring cesarean section for breech presentation, adequate skills are still needed for a safe vaginal breech birth. This case report illustrates the physiological mechanism of vaginal breech birth. The accompanying pictures are a testimony to the “hands‐off” approach and could be used for educational purposes.
Stroke survivor gait adaptation and performance after training on a Powered Ankle Foot Orthosis

With over 600 thousand people each year surviving a stroke, it has become the leading cause of serious long-term disability in the United States [1], [2]. The adverse financial and social conditions attributed to stroke have prompted researchers and entrepreneurs to explore the viability of rehabilitation robots. The Powered Ankle Foot Orthosis (PAFO) utilizes robotic tendon technology and supports motion with a single degree of freedom, ankle rotation in the Sagittal plane. Motion capture data, robot sensor data, and functional 6 minute walk data were collected on three stroke subjects. All subjects had some positive changes in their key gait variables while using the PAFO. These changes were more dramatic while harnessed and using a treadmill as opposed to walking over ground. Robot sensor data showed significant improvements on key variables for the three subjects. Motion capture data showed improvements in knee range of motion for subject 1, and the 6 minute walk data showed an increase in distance walked for subjects 1 and 3. Comfort, stability, and robustness proved to be critical design parameters for developing a gait therapy robot capable of collecting repeatable data with low variability.
Joint Conference on Neural Networks , Orlando , Florida , USA , August 12-17 , 2007 Agnostic Learning vs . Prior Knowledge Challenge

"When everything fails, ask for additional domain knowledge" is the current motto of machine learning. Therefore, assessing the real added value of prior/domain knowledge is a both deep and practical question. Most commercial data mining programs accept data pre-formatted as a table, each example being encoded as a fixed set of features. Is it worth spending time engineering elaborate features incorporating domain knowledge and/or designing ad hoc algorithms? Or else, can off-the-shelf programs working on simple features encoding the raw data without much domain knowledge do as well or better than skilled data analysts? To answer these questions, we organized a challenge for IJCNN 2007. The participants were allowed to compete in two tracks: The "prior knowledge" (PK) track, for which they had access to the original raw data representation and as much knowledge as possible about the data, and the "agnostic learning" (AL) track for which they were forced to use data pre-formatted as a table with dummy features. The AL vs. PK challenge web site remains open: http://www.agnostic. inf.ethz. ch/.
How to tell an airport from a home: techniques and applications

Today's Internet services increasingly use IP-based geolocation to specialize the content and service provisioning for each user. However, these systems focus almost exclusively on the current position of users and do not attempt to infer or exploit any qualitative context about the location's relationship with the user (e.g., is the user at home? on a business trip? ). This paper develops such a context by profiling the usage patterns of IP address ranges, relying on known user and machine identifiers to track accesses over time. Our preliminary results suggest that rough location categories such as residences, workplaces, and travel venues can be accurately inferred, enabling a range of potential applications from demographic analyses to ad specialization and security improvements.
Strength in Numbers: Using Big Data to Simplify Sentiment Classification

Sentiment classification, the task of assigning a positive or negative label to a text segment, is a key component of mainstream applications such as reputation monitoring, sentiment summarization, and item recommendation. Even though the performance of sentiment classification methods has steadily improved over time, their ever-increasing complexity renders them comprehensible by only a shrinking minority of expert practitioners. For all others, such highly complex methods are black-box predictors that are hard to tune and even harder to justify to decision makers. Motivated by these shortcomings, we introduce BigCounter: a new algorithm for sentiment classification that substitutes algorithmic complexity with Big Data. Our algorithm combines standard data structures with statistical testing to deliver accurate and interpretable predictions. It is also parameter free and suitable for use virtually "out of the box," which makes it appealing for organizations wanting to leverage their troves of unstructured data without incurring the significant expense of creating in-house teams of data scientists. Finally, BigCounter's efficient and parallelizable design makes it applicable to very large data sets. We apply our method on such data sets toward a study on the limits of Big Data for sentiment classification. Our study finds that, after a certain point, predictive performance tends to converge and additional data have little benefit. Our algorithmic design and findings provide the foundations for future research on the data-over-computation paradigm for classification problems.
Flugate Sensor With Pulse Feedback

Fluxgate sensors have typically only 100 μT range, which sometimes limits their applications. The main obstacle for increasing the measurement range is the power dissipated in their feedback coil. Until now, the feedback was always continuous. We suggest using pulse excitation only for the active part of the period, in which an output signal is present. In this paper, we show for the first time that if the sensor is excited by short pulses, the feedback need not be continuous, but it can be formed by the pulses slightly wider than the excitation pulses. We have shown that, in our case, the feedback current duty cycle can be only 17.25%. This means that for the same power, we can increase maximum feedback current and, thus, the range by the factor of three. We show that this can be done without compromising the sensor performance.
Quantification of green fluorescent protein by in vivo imaging, PCR, and flow cytometry: Comparison of transgenic strains and relevance for fetal cell microchimerism

Animal models are increasingly being used for the assessment of fetal cell microchimerism in maternal tissue. We wished to determine the optimal transgenic mouse strain and analytic technique to facilitate the detection of rare transgenic microchimeric fetal cells amongst a large number of maternal wild‐type cells. We evaluated two strains of mice transgenic for the enhanced green fluorescent protein (EGFP): a commercially available, commonly used strain (C57BL/6‐Tg(ACTB‐EGFP)10sb/J) (CAG) and a newly created strain (ROSA26‐EGFP) using three different techniques: in vivo and ex vivo fluorescent imaging (for whole body and dissected organs, respectively), PCR amplification of gfp, and flow cytometry (FCM). By fluorescent imaging, organs from CAG mice were 10‐fold brighter than organs from ROSA26‐EGFP mice (P < 0.0001). By PCR, more transgene from CAG mice was detected compared to ROSA26‐EGFP mice (P = 0.04). By FCM, ROSA26‐EGFP cell fluorescence was more uniform than CAG cells. A greater proportion of cells from ROSA26‐EGFP organs were positive for EGFP than cells from CAG organs, but CAG mice had a greater proportion of cells with the brightest fluorescent intensity. Each transgenic strain possesses characteristics that make it useful under specific experimental circumstances. The CAG mouse model is preferable when experiments require brighter cells, whereas ROSA26‐EGFP is more appropriate when uniform or ubiquitous expression is more important than brightness. Investigators must carefully select the transgenic strain most suited to the experimental design to obtain the most consistent and reproducible data. In vivo imaging allows for phenotypic evaluation of whole animals and intact organs; however, we did not evaluate its utility for the detection of rare, fetal microchimeric cells in the maternal organs. Finally, while PCR amplification of a paternally inherited transgene does allow for the quantitative determination of rare microchimeric cells, FCM allows for both quantitative and qualitative evaluations of fetal cells at very high sensitivity in a plethora of maternal organs. © 2008 International Society for Analytical Cytology
Hydrogen sulphide‐induced relaxation of porcine peripheral bronchioles

Hydrogen sulphide (H2S) is an endogenous gasotransmitter. Although it has been shown to elicit responses in vascular and other smooth muscle preparations, a role for endogenously produced H2S in mediating airway tone has yet to be demonstrated. Therefore, the aim of this study was to determine whether H2S is produced within the airways and to determine the functional effect on airway tone.
J un 2 00 6 IFT-UAM / CSIC-06-26 A class of non-supersymmetric orientifolds

We study type IIB orientifolds on T/ZN with supersymmetry broken by the compactification. We determine tadpole cancellation conditions including antibranes and considering different actions for the parity Ω. Using these conditions we then obtain the spectrum of tachyons and massless states. Various examples with N even correspond to type 0B orientifolds. On leave from Departamento de F́ısica, Facultad de Ciencias, Universidad Central de Venezuela, A.P. 20513, Caracas 1020-A, Venezuela.
Integrated Approaches to Preventing Antisocial Behavior Patterns among School-Age Children and Youth

This article provides a reconceptualization of the role of schools in preventing antisocial behavior problems among children and youth. The U.S. Public Health Service's conceptual model of prevention, involving primary, secondary, and tertiary prevention approaches, is used as an organizing framework to illustrate how schools can deliver interventions more effectively and improve outcomes. Traditional school approaches to coping with students who are at risk and antisocial are reviewed, and the following major topics are addressed: (a) A case is made that schools can play a central, coordinating role in collaboration with families and social service agencies in addressing the challenging problems presented by antisocial students; (b) a generic intervention approach is suggested that involves reducing risk factors for antisocial behavior and enhancing protective factors; (c) a three-level approach to organizing specific interventions for achieving prevention goals and outcomes is described; and (d) recommended interventions or approaches are suggested for each prevention level (i.e., primary, secondary, tertiary). The article concludes with a discussion of some factors associated with a revised mission for schools in this domain and how these factors may impair or enhance the necessary changes required to achieve this goal.
Xanthine dehydrogenase: An old enzyme with new knowledge and prospects

ABSTRACT Xanthine dehydrogenase (EC 1.17.1.4, XDH) is a typical and complex molybdenum-containing flavoprotein which has been extensively studied for over 110 years. This enzyme catalyzes the oxidation of purines, pterin and aldehydes with NAD+ or NADP+ as electron acceptor, and sometimes can be transformed to xanthine oxidase (EC 1.17.3.2, XOD) capable of utilizing oxygen as the electron acceptor. XDHs are widely distributed in all eukarya, bacteria and archaea domains, and are proposed to play significant roles in various cellular processes, including purine catabolism and production of reactive oxygen species (ROS) and nitric oxide (NO) in both physiological and pathological contexts. The recent applications of XDHs include clinical detections of xanthine and hypoxanthine content in body fluidics, and other diagnostic biomarkers like inorganic phosphorus, 5′-nucleotidase and adenosine deaminase. XDHs can also find applications in environmental degradation of pollutants like aldehydes and industrial application in nucleoside drugs like ribavirin. In this commentary, we would outline the latest knowledge on occurrence, structure, biosynthesis, and recent advances of production and applications of XDH, and highlighted the need to develop XDHs with improved performances by gene prospecting and protein engineering, and protocols for efficient production of active XDHs in response to the increasing demands.
Multiple Molecular and Cellular Mechanisms of Action of Lycopene in Cancer Inhibition

Epidemiological studies suggest that including fruits, vegetables, and whole grains in regular dietary intake might prevent and reverse cellular carcinogenesis, reducing the incidence of primary tumours. Bioactive components present in food can simultaneously modulate more than one carcinogenic process, including cancer metabolism, hormonal balance, transcriptional activity, cell-cycle control, apoptosis, inflammation, angiogenesis and metastasis. Some studies have shown an inverse correlation between a diet rich in fruits, vegetables, and carotenoids and a low incidence of different types of cancer. Lycopene, the predominant carotenoid found in tomatoes, exhibits a high antioxidant capacity and has been shown to prevent cancer, as evidenced by clinical trials and studies in cell culture and animal models. In vitro studies have shown that lycopene treatment can selectively arrest cell growth and induce apoptosis in cancer cells without affecting normal cells. In vivo studies have revealed that lycopene treatment inhibits tumour growth in the liver, lung, prostate, breast, and colon. Clinical studies have shown that lycopene protects against prostate cancer. One of the main challenges in cancer prevention is the integration of new molecular findings into clinical practice. Thus, the identification of molecular biomarkers associated with lycopene levels is essential for improving our understanding of the mechanisms underlying its antineoplastic activity.
Managing update conflicts in Bayou, a weakly connected replicated storage system

Bayou is a replicated, weakly consistent storage system designed for a mobile computing environment that includes portable machines with less than ideal network connectivity. To maximize availability, users can read and write any accessible replica. Bayou’s design has focused on supporting application-specific mechanisms to detect and resolve the update conflicts that naturally arise in such a system, ensuring that replicas move towards eventual consistency, and defining a protocol by which the resolution of update conflicts stabilizes. It includes novel methods for conflict detection, called dependency checks, and per -write conflict resolution based on client-provid ed mer ge procedures. To guarantee eventual consistency, Bayou servers must be able to rollback the effects of previously executed writes and redo them according to a global serialization order . Furthermore, Bayou permits clients to observe the results of all writes received by a server , including tentative writes whose conflicts have not been ultimately resolved. This paper presents the motivation for and design of these mechanisms and describes the experiences gained with an initial implementation of the system.