BitTorrent Experiments on Testbeds: A Study of the Impact of Network Latencies

In this paper, we study the impact of network latency on the time required to download a file distributed using BitTorrent. This study is essential to understand if testbeds can be used for experimental evaluation of BitTorrent. We observe that the network latency has a marginal impact on the time required to download a file; hence, BitTorrent experiments can performed on testbeds

Studying Social Networks at Scale: Macroscopic Anatomy of the Twitter Social Graph

Twitter is one of the largest social networks using exclusively directed links among accounts. This makes the Twitter social graph much closer to the social graph supporting real life communications than, for instance, Facebook. Therefore, understanding the structure of the Twitter social graph is interesting not only for computer scientists, but also for researchers in other fields, such as sociologists. However, little is known about how the information propagation in Twitter is constrained by its inner structure. In this paper, we present an in-depth study of the macroscopic structure of the Twitter social graph unveiling the highways on which tweets propagate, the specific user activity associated with each component of this macroscopic structure, and the evolution of this macroscopic structure with time for the past 6 years. For this study, we crawled Twitter to retrieve all accounts and all social relationships (follow links) among accounts; the crawl completed in July 2012 with 505 million accounts interconnected by 23 billion links. Then, we present a methodology to unveil the macroscopic structure of the Twitter social graph. This macroscopic structure consists of 8 components defined by their connectivity characteristics. Each component group users with a specific usage of Twitter. For instance, we identified components gathering together spammers, or celebrities. Finally, we present a method to approximate the macroscopic structure of the Twitter social graph in the past, validate this method using old datasets, and discuss the evolution of the macroscopic structure of the Twitter social graph during the past 6 years.Comment: ACM Sigmetrics 2014 (2014

Creep and Anelastic Deformation in Austenitic Steels

This study examines the creep behaviour of austenitic steels under service temperatures, to determine the effect of creep on material performance. Nuclear power plant components are in regular use at temperatures greater than 450°C, where creep deformation plays a dominant role in limiting the lifetime of the material. The prime aim of this study was to characterise the effect of load-reductions on the creep behaviour of austenitic steels (AISI type 316H). In-service materials seldom operate at a constant load and/or temperature. The supply demand, maintenance operations, refuelling, etc. will result in large variation of load and temperature acting on the material. Experiments where load/temperature removals during a creep test were therefore conducted. These unloading procedures result in material recovery of the accumulated creep strain (anelasticity). This phenomenon will influence the material properties such as creep life and ductilities. Creep life was found to increase by 2-3 times whereas creep ductilities decreased by 50% when compared to steady-load creep data under identical conditions. The occurrence of anelasticity suggested the presence of a material backstress. The origin and evolution of this internal stress was investigated using neutron diffraction and TEM microscopy. Lattice strain measurements were conducted in-situ using neutron diffraction during a creep test which consisted of load/unload cycles. Experimental results suggest that creep strain is equivalent to plastic strain at a granular level. The data also shows intergranular micro-stresses are introduced into the material by primary creep. Anisotropic behaviour of the individual crystal planes results in formation of tensile and compressive intergranular stresses in individual grain families. Residual compressive stresses drive this anelastic deformation. TEM examinations of samples stopped during the unload show changes in dislocation and precipitate morphologies during the plastic strain recovery phase. Evidence of a changing dislocation substructure during the load-reduction period was found. Examinations have also shown carbide densities change during the unload. Pipe diffusion is a possible mechanism which can be used to explain this occurrence. The changing precipitate and dislocation state will influence the strengthening mechanisms, which in-turn will affect the deformation characteristics. These microstructural observations were introduced into a damage mechanics model. Predictions of material behaviour using this model have shown good agreement with experimental data. Outcomes of this project, have established that changes in creep deformation mechanisms will greatly influence material properties. Deformation history of the material will affect the intergranular stress state which in turn will affect the elastic and plastic response of the material. The effect of plastic strain history must be considered and incorporated accounted in any design and assessment procedure

Twin reversed arterial perfusion sequence: the heartless twin

To report a case of twin reversal arterial perfusion sequence and its management by means of laser coagulation of the vascular malformation in the placenta. Twin reversed arterial perfusion sequence is a rare form of twin to twin transfusion syndrome occurring primarily in Monochorionic monoamniotic twins. The prevalence is about 1 in 35,000 pregnancies. The significance of this condition is that there is a normal foetus and an acardiac foetus. The blood is shunted from the normal twin to the acardiac twin through vascular malformations in the placenta. The normal twin faces a high risk of both morbidity and mortality due to cardiac failure. A case of twin reversal arterial perfusion sequence diagnosed at 22 weeks following a target scan underwent laser photocoagulation and gave birth vaginally at 30 weeks without any complications. Early detection of this condition can lead to timely intervention and thereby improve the outcome. In Twin reversal arterial perfusion sequence, the normal or the pump twin has a high chance of mortality due to cardiac failure. As the size of the acardiac twin increases, there is a higher chance of mortality of the pump twin. There is a need for regular follow up with ultrasonography and foetal echocardiography along with early therapeutic interventions to ensure the survival of the normal twin. In our case, despite the large size of the acardiac twin, we had a successful pregnancy outcome for the normal twin due to timely intervention

Enabling Rapid Chemical Analysis of Plutonium Alloys via Machine Learning-enhanced Atomic Spectroscopy Techniques

Analytical atomic spectroscopy methods have the potential to provide solutions for rapid, high fidelity chemical analysis of plutonium alloys. Implementing these methods with advanced analytical techniques can help reduce the chemical analysis time needed for plutonium pit production, directly enabling the 80 pit-per-year by 2030 manufacturing goal outlined in the 2018 Nuclear Posture Review. Two commercial, handheld elemental analyzers were validated for potential in situ analysis of Pu. A handheld XRF device was able to detect gallium in a Pu surrogate matrix with a detection limit of 0.002 wt% and a mean error of 8%. A handheld LIBS device was able to yield univariate detection limits as low as 0.1 wt% Ga with mean error of 3%. Implementing machine learning methods for spectral analysis with the handheld LIBS device reduced error to 0.27%, but the limited device resolution impedes improvements in sensitivity. A compact Echelle spectrometer was implemented with a laboratory LIBS setup to reach a detection limit of 0.006 wt% Ga when coupled with an optimized extra trees regression. A Gaussian kernel regression trained on this high resolution data set yielded the most accurate predictive model with 0.33% error. Lastly, the phenomenon of self-absorption was quantified and corrected for in Ce-Ga LIBS spectra. By implementing a Stark broadening based correction, the univariate detection limit for Ga from LIBS spectra was reduced to 0.008%. Overall, this research indicates that implementing a compact, high resolving power spectrograph for recording Pu alloy spectra and developing optimized machine learning models for spectral analysis can yield high fidelity solutions for Pu alloy chemical analysis and quality control

Rapid Analysis of Plutonium Surrogate Material via Hand-Held Laser-Induced Breakdown Spectroscopy

This work investigated the capability of a portable LIBS device to detect and quantify dopants in plutonium surrogate alloys, specifically gallium, which is a common stabilizer used in plutonium alloys. The SciAps Z500-ER was utilized to collect spectral data from cerium-gallium alloys of varying gallium concentrations. Calibration models were built to process spectra from the Ce-Ga alloys and calculate gallium concentration from spectral emission intensities. Univariate and multivariate analysis techniques were used to determine limits of detection of different emission line ratios. Spatial mapping measurements were conducted to determine the device\u27s ability to detect variations in gallium concentration on the surface of sample. Chemometric techniques were implemented to build predictive calibration models from the entire spectral data set. Partial least-squares regression was determined to produce the superior calibration model for predicting Ga content in a Ce-Ga alloy. The results demonstrated the SciAps Z500-ER can be coupled with advanced multivariate analytical routines to efficiently and rapidly provide quantitative analysis of impurities in plutonium surrogate metal. By using a handheld LIBS device in lieu of traditional mass spectrometry methods, the chemical analysis time can be reduced to mere seconds. This has direct applications for several national security applications including directly enabling Pu pit production teams to meet the 80 pit-per-year production goal outlined in the 2018 Nuclear Posture Review

Model-based approach to envelope and positive instantaneous frequency estimation of signals with speech applications

An analytic signal s(t) is modeled over a T second duration by a pole-zero model by considering its periodic extensions. This type of representation is analogous to that used in discrete-time systems theory, where the periodic frequency response of a system is characterized by a finite number of poles and zeros in the z-plane. Except, in this case, the poles and zeros are located in the complex-time plane. Using this signal model, expressions are derived for the envelope, phase, and the instantaneous frequency of the signal s(t). In the special case of an analytic signal having poles and zeros in reciprocal complex conjugate locations about the unit circle in the complex-time plane, it is shown that their instantaneous frequency (IF) is always positive. This result paves the way for representing signals by positive envelopes and positive IF (PIF). An algorithm is proposed for decomposing an analytic signal into two analytic signals, one completely characterized by its envelope and the other having a positive IF. This algorithm is new and does not have a counterpart in the cepstral literature. It consists of two steps. In the first step, the envelope of the signal is approximated to desired accuracy using a minimum-phase approximation by using the dual of the autocorrelation method of linear prediction, well known in spectral analysis. The criterion that is optimized is a waveform flatness measure as opposed to the spectral flatness measure used in spectral analysis. This method is called linear prediction in spectral domain (LPSD). The resulting residual error signal is an all-phase or phase-only analytic signal. In the second step, the derivative of the error signal, which is the PIF, is computed. The two steps together provide a unique AM-FM or minimum-phase/all-phase decomposition of a signal. This method is then applied to synthetic signals and filtered speech signals

The Impact of Thread-Per-Core Architecture on Application Tail Latency

Peer reviewe

A rare presentation of a pyosalpinx in a post-menopausal woman

Primary fallopian tube carcinoma is a rare tumour of the female genital tract with an incidence of 0.1-1.8% of all genital malignancies, which is generally an intra-operative or a histological diagnosis.  It is a tumour that resembles epithelial ovarian cancer. A 61-year-old postmenopausal woman presented with complaints of continuous bleeding per vaginum with history of loss of appetite and weight for 6 months. She was also a known diabetic and hypertensive. On examination, per abdominal, per speculum and per vaginal findings were unremarkable.  A transvaginal ultrasonography done previously showed fluid in the endometrial cavity suggestive of hematometra/pyometra due to cervical stenosis. A fractional curettage done previously had shown strips of acanthotic squamous epithelium in the endocervical curetting.   She underwent abdominal hysterectomy with bilateral salpingo ovariectomy. Histopathological findings were suggestive of primary fallopian tube adenocarcinoma. Hence the patient was advised chemotherapy followed by a second look laparotomy. Preoperative diagnosis of fallopian tube carcinoma is difficult due to the silent course of this neoplasm and is usually first appreciated at the time of operation or by a pathologist. The treatment approach is similar to that of ovarian carcinoma, and it should consist of a total abdominal hysterectomy with bilateral salpingo-ovariectomy, omentectomy and lymph node dissection from the pelvic and the para-aortic regions

Programmable Session Layer MULTI-Connectivity

Our devices can use a wide range of communication technologies such as multiple cellular technologies (4G/5G), WiFi, and also Ethernet. At the same time, applications have a choice of a wide range of transport protocols such as QUIC and TCP that can be fine-tuned and optimized according to their needs. However, in spite of these advances, offering seamless multiconnectivity to applications continues to be a hard problem. The key factors that continue to be a roadblock towards achieving seamless multiconnectivity include a) applications cannot specify the communication technologies to be used by their flows, and b) the traditional definition of a connection endpoint was not designed to support mobile nodes. In this paper we discuss the key challenges that make this problem hard. We also present MULTI, a session layer approach that can be leveraged to address some of the key sub-problems of this problem. For instance, we observe that MULTI incurred a small overhead (less than 5% decrease in throughput) when using TCP compared to the native asyncio python library.Peer reviewe