Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualization of the Boron Neutron Capture Therapy treatment planning process

The focus of this thesis is the development of a visualization module (SeraSd) for the Simulated Environment for Radiotherapy Applications (SERA) software package, under development at Montana State University and the Idaho National Engineering and Environmental Laboratories. In 1997, a highly efficient particle tracking method was developed to speed the Monte Carlo transport calculations, which simulate the neutron/boron interactions in the anatomical geometry. The new particle tracking method required a uniform volume element (univel) description of the geometry. The uniformity allowed for fast tracking through highly efficient indexing schemes and integer-based arithmetic operations. The adoption of the univel descriptions resulted in the restructuring of the software package. With the restructuring of the older software package into SERA, and the advances in computer graphics hardware, the addition of a visualization module was undertaken to provide a visual understanding of all aspects of the proposed treatment plan. The three dimensional rendering in SeraSd is built on the OpenGL graphics library, while all of the user interfaces and components were developed using the Motif toolkit in an Xl I window environment. The univel geometry description provides great storage flexibility; virtually any anatomical structure can be represented. SeraSd is constructed with this flexibility mind,, allowing the three dimensional reconstruction of any region stored with this univel description. SeraSd also provides various tools for further examination of the region reconstruction. Multiple rendering windows, each through a different camera, as well as full model rotation capabilities provide views from any angle. Two clipping planes are provided along each of the three major orthogonal axes, offering a direct look into the interior of the geometry. Likewise, varying the values of region transparency allow views into the inner regions. Through the use of texture mapping, an image slice can be inlaid in any arbitrary direction within the reconstruction. This inclusion of the original data allows further confirmation of the surface geometry. Additionally, a camera view along the beam line is provided, as well as image slices perpendicular to the beam line. One of the unique elements of this system is that the same surface rendering methods used to display the reconstructed anatomical objects are used to display the isodose contours. This provides for a striking presentation of the radiation dose data and also provides a useful tool for the clinician in developing an efficacious treatment plan. A second method for displaying the dose data is colorwashing the medical image volume with the isodoses. This thesis includes the visual results of the applied techniques, as well as visions for the further integration of SeraSd into the SERA software package.
Near-field coupling in UHF-RFID systems

In this paper near-field coupling in UHF-RFID systems is investigated. The wireless power transfer among reader and tag antennas is addressed through a numerical model involving different reader antennas and a short-range tag. System performance is investigated in terms of both mutual impedance and power transfer efficiency. Finally, a new nearfield reader antenna based on coplanar waveguide technology will be described.
POPULATION BASED STUDY OF EPISIOTOMY

Objectives: To estimate episiotomy rate in a rural population and to find out if higher episiotomy rate is associated with place of delivery and category of health care provider. Design: Population based cross sectional study Setting: Rural population near Chennai. Sample: Included 442 mothers who had vaginal delivery between August 2004 and July 2005. Methods: Cluster sampling was used to select the study sample. Information about episiotomy during last child birth and other details were obtained by personal interview and from available medical records. Results: Overall episiotomy rate was 67% (95% CI 62.6 – 71.4). For women whose delivery was conducted by doctors the episiotomy rate was 77.4% and conducted by nurses it was 53.1%. Episiotomy rate was very high (91.8%) when delivery was conducted in private medical college hospitals and the rates were lower when conducted in secondary and primary level institutions. Adjusted odds ratio for episiotomy was 38 when doctors conducted delivery compared to trained birth attendants and 8.9 when delivery was conducted at private medical college hospitals compared to primary health centres. Conclusion Episiotomy rate in the study population is high. Probably similar high rates are found in other parts of India. The probability of episiotomy is very high when doctors conducted the delivery and when place of delivery is private medical college hospital. Evidence based restrictive practice of episiotomy to less than 30% should be adopted by all, particularly in tertiary care teaching hospitals which should serve as role models.
Multilingual Syntactic-Semantic Dependency Parsing with Three-Stage Approximate Max-Margin Linear Models

This paper describes a system for syntactic-semantic dependency parsing for multiple languages. The system consists of three parts: a state-of-the-art higher-order projective dependency parser for syntactic dependency parsing, a predicate classifier, and an argument classifier for semantic dependency parsing. For semantic dependency parsing, we explore use of global features. All components are trained with an approximate max-margin learning algorithm. In the closed challenge of the CoNLL-2009 Shared Task (Hajic et al., 2009), our system achieved the 3rd best performances for English and Czech, and the 4th best performance for Japanese.
Improved algorithms for path, matching, and packing problems

Improved randomized and deterministic algorithms are presented for PATH, MATCHING, and PACKING problems. Our randomized algorithms are based on the divide-and-conquer technique, and improve previous best algorithms for these problems. For example, for the <i>k</i>-PATH problem, our randomized algorithm runs in time <i>O</i>(4<sup><i>k</i></sup>k<sup>3.42</sup><i>m</i>) and space <i>O</i>(<i>nk</i>log<i>k</i> + <i>m</i>), improving the previous best randomized algorithm for the problem that runs in time <i>O</i>(5.44<sup><i>k</i></sup>km) and space <i>O</i>(2<sup><i>k</i></sup>kn + <i>m</i>). To achieve improved deterministic algorithms, we study a number of previously proposed de-randomization schemes, and also develop a new derandomization scheme. These studies result in a number of deterministic algorithms: one of time <i>O</i>(4<sup><i>k</i>+<i>o(k)</i></sup>m) for the <i>k</i>-PATH problem, one of time <i>O</i>(2.80<sup>3<i>k</i></sup>k nlog<sup>2</sup> <i>n</i>) for the 3-D MATCHING problem, and one of time <i>O</i>(4<sup>3<i>k</i>+<i>o(k)</i></sup>n) for the 3-SET PACKING problem. All these significantly improve previous best algorithms for the problems.
Detection of single action potential in multi-unit postganglionic sympathetic nerve recordings in humans: A matched wavelet approach

Sympathetic nerve activity associated with blood pressure regulation can be recorded directly using microneurography. Action potentials (APs) in the sympathetic nerve signal are dominated by colored gaussian noise. This paper proposes a novel method for detecting APs from muscle sympathetic nerve activity (MSNA) in multi-unit postganglionic recordings. The new method is based on designing a new mother wavelet matched to an actual AP template extracted from a real raw MSNA signal. To detect action potentials, the new matched wavelet was applied to the MSNA signal using a continuous wavelet transform following a thresholding procedure and detecting local maxima to estimate AP arrival times. The performance of the proposed method was evaluated using real MSNA recorded from six healthy participants and compared with two previous wavelet-based methods using a simulated MSNA signal.
Efficient Rate-Control System With Three Stages for JPEG2000 Image Coding

Although the conventional post-compression rate distortion (PCRD) optimum algorithm in JPEG2000 can provide excellent rate-distortion performance, it remains troublesome for VLSI design. It requires high-complexity computation and a large quantity of working memory. In this paper, a novel rate-control system for JPEG2000 image coding, which consists of three stages, is proposed to efficiently reduce the computational complexity and memory usage, as well as maintaining the high image comparable with PCRD. In the precoding stage, the rate allocation for the image tiles (RAIT) can allocate the bit rates for different image tiles based on their internal information; moreover, in order to make VLSI design easier, the image edge-detect algorithms and the prediction algorithms are used to evaluate the information of the image tiles. In the tier1 coding stage, according to the given bit rate, the rate allocation based on the rest rate distortion (RARRD) can adaptively truncate code stream based on the rest rate distortion of the current image tile and the rate-distortion (RD) slope of the current coding pass during the current code-block coding, and all of the truncated data need not be encoded and stored. In the post-coding stage, a new fast rate control with approximately optimum truncation (RCAOT) can get the approximately optimum truncation points through searching among the 256 quality layers once, which are divided based on the 8-b RD-slopes expressed by means of a logarithm. This system can not only maintain high image quality through RCAOT and RAIT but also save working memory and encoding time by means of RARRD and RCAOT. Experimental results show that, for the image which has distinct objects and background, the PSNR of the reconstructed images compressed by our rate-control system are much higher than those using PCRD; for other images, our system has the comparative effect as PCRD
Diffusion Weighted Image Denoising Using Overcomplete Local PCA

Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to the presence of noise from the measurement process that complicates and biases the estimation of quantitative diffusion parameters. In this paper, a new denoising methodology is proposed that takes into consideration the multicomponent nature of multi-directional DWI datasets such as those employed in diffusion imaging. This new filter reduces random noise in multicomponent DWI by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with state-of-the-art methods using synthetic and real clinical MR images, showing improved performance in terms of denoising quality and estimation of diffusion parameters.
Dairy Products Consumption Is Associated with Decreased Levels of Inflammatory Markers Related to Cardiovascular Disease in Apparently Healthy Adults: The ATTICA Study

Objective: The aim of this work was to investigate the association between consumption of dairy products and levels of various inflammatory markers among adults with no evidence of cardiovascular or other chronic disease. Methods: The ATTICA study is a cross-sectional survey that enrolled 1514 men (18–87 years old) and 1528 women (18–89 years old) from the Attica region in Greece. Fasting blood samples were collected and dietary habits (including consumption of dairy products [i.e., milk, cheese, and yogurt]) were evaluated using a validated food frequency questionnaire. Results: We observed that C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) levels of individuals consuming between 11 and 14 servings of dairy products per week were almost 16%, 5%, and 12% lower, respectively, than in those consuming fewer than 8 servings (p < 0.05), while those consuming more than 14 servings per week had 29%, 9%, and 20% lower levels of CRP, IL-6, and TNF-α, respectively (p < 0.01), even after adjustments were made for age, gender, smoking, physical activity, body mass, dietary habits, and other potential confounders. Conclusion: We identified an inverse association between dairy products consumption and levels of various inflammatory markers among healthy adults. Additional clinical trials are needed to refute or confirm our findings.
Exploring scalar fields using multiple sensor platforms: Tracking level curves

Autonomous mobile sensor networks are employed to measure large scale environmental scalar fields. Yet an optimal strategy for mission design addressing both the cooperative motion control and the collaborative sensing is still under investigation. We develop one strategy which uses four moving sensor platforms to explore a noisy scalar field defined in the plane; each platform can only take one measurement at a time. We derive a Kalman filter in conjunction with a nonlinear filter to produce estimates for the field value, the gradient and the Hessian along the averaged trajectories of the moving platforms. The shape of the platform formation is designed to minimize error in the estimates, and a cooperative control law is designed to asymptotically achieve the optimal formation. We develop a motion control law to allow the center of the platform formation to move along level curves of the averaged field. Convergence of the control laws are proved, and performance of both the filters and the control laws are demonstrated in simulated ocean fields.
Performance Implications of Processing-in-Memory Designs on Data-Intensive Applications

The popularity of data-intensive applications and recent hardware developments drive the re-emergence of processing-in-memory (PIM) after earlier explorations several decades ago. To introduce PIM into a system, we must answer a fundamental question: what computation logic should be included into PIM? In terms of computation complexity, PIM can be either relatively simple, fixedfunctional, or fully programmable. The choice of fixedfunctional PIM and programmable PIM has direct impact on performance. In this paper, we explore the performance implications of fixed-functional PIM and programmable PIM on three data-intensive benchmarks-including a real data-intensive application. Our results show that - with PIMs - we obtain 2.09x-91.4x speedup over no PIM cases. However, the fixed-functional PIM and programmable PIM perform differently across applications (with performance difference up to 90%). Our results show that neither fixed-functional PIM nor programmable PIM can perform optimally in all cases. We must decide the usage of PIM based on the characteristics of the workload and PIM (e.g., instruction-level parallelism), and the PIM overhead (e.g., PIM initialization and synchronization overhead).
Soft timers: efficient microsecond software timer support for network processing

This paper proposes and evaluates soft timers, a new operating system facility that allows the efficient scheduling of software events at a granularity down to tens of microseconds. Soft timers can be used to avoid interrupts and reduce context switches associated with network processing without sacrificing low communication delays.More specifically, soft timers enable transport protocols like TCP to efficiently perform rate-based clocking of packet transmissions. Experiments show that rate-based clocking can improve HTTP response time over connections with high bandwidth-delay products by up to 89% and that soft timers allow a server to employ rate-based clocking with little CPU overhead (2-6%) at high aggregate bandwidths.Soft timers can also be used to perform network polling, which eliminates network interrupts and increases the memory access locality of the network subsystem without sacrificing delay. Experiments show that this technique can improve the throughput of a Web server by up to 25%.
Macrophage Bridging Conduit Trafficking of HIV-1 Through the Endoplasmic Reticulum and Golgi Network

Bridging conduits (BC) are tubular protrusions that facilitate cytoplasm and membrane exchanges between tethered cells. We now report that the human immunodeficiency virus type I (HIV-1) exploits these conduits to accelerate its spread and to shield it from immune surveillance. Endosome transport through BC drives HIV-1 intercellular transfers. How this occurs was studied in human monocyte-derived macrophages using proteomic, biochemical, and imaging techniques. Endosome, endoplasmic reticulum (ER), Golgi markers, and HIV-1 proteins were identified by proteomic assays in isolated conduits. Both the ER and Golgi showed elongated and tubular morphologies that extended into the conduits of polarized macrophages. Env and Gag antigen and fluorescent HIV-1 tracking demonstrated that these viral constituents were sequestered into endocytic and ER-Golgi organelles. Sequestered infectious viral components targeted the Golgi and ER by retrograde transport from early and Rab9 late endosomes. Disruption of the ER-Golgi network impaired HIV-1 trafficking in the conduit endosomes. This study provides, for the first time, mechanisms for how BC Golgi and ER direct cell–cell viral transfer.
Effects of Interfacial Conditions on Wall Slip and Sharkskin Melt Fracture of HDPE

Abstract Experiments were performed in capillary and slit rheometers to determine the effects of the presence of fluoropolymers at the polymer-wall interface on wall slip and extrudate distortion of a molten high density polyethylene. Two fluoropolymers were used to modify the interface. It was found that one of these decreased slip compared to the clean interface while the other increased slip. However, both were found to improve extrudate appearance, thus indicating that both adhesion promoters and slip promoters may improve extrudate appearance. The mechanism underlying this rather surprising conclusion is also discussed.
Optimizing Monocapillary Optics for Synchrotron X‐ray Diffraction, Fluorescence Imaging, and Spectroscopy Applications

A number of synchrotron x‐ray applications such as powder diffraction in diamond anvil cells, microbeam protein crystallography, x‐ray fluorescence imaging, etc. can benefit from using hollow glass monocapillary optics to improve the flux per square micron on a sample. We currently draw glass tubing into the desired elliptical shape so that only one‐bounce under total reflection conditions is needed to bring the x‐ray beam to a focus at a 25 to 50 mm distance beyond the capillary tip. For modest focal spot sizes of 10 to 20 microns, we can increase the intensity per square micron by factors of 10 to 1000. We show some of the results obtained at CHESS and Hasylab with capillaries focusing 5 to 40 keV radiation, their properties, and how even better the experimental results could be if more ideal capillaries were fabricated in the future.
A 32 nm, 3.1 Billion Transistor, 12 Wide Issue Itanium® Processor for Mission-Critical Servers

An Itanium® processor implemented in 32 nm CMOS with nine layers of Cu contains 3.1 billion transistors. The die measures 18.2 mm by 29.9 mm. The processor has eight multi-threaded cores, a ring based system interface and combined cache on the die is 50 MB. High-speed links allow for peak processor-to-processor bandwidth of up to 128 GB/s and memory bandwidth of up to 45 GB/s.
Chemical Durability of Glass Thermal Insulation Fibers in Borate and Phosphate Water Solutions

Glass fiber is commonly used as thermal insulation for the equipment in nuclear power plants. In case of LOCA (Loss Of Coolant Accident), the insulation can be damaged by the jet impact and carried to the screens of the emergency systems needed to cool the reactor. In this case, the fibers can be strongly corroded by particular cooler solutions and their behavior under this environment can modify the head loss of the screens. The pH value of coolant solution can be stabilized respectively by borate or phosphate buffering systems depending of the plants. A new type of small scale laboratory equipment allowing simultaneous study of the chemical durability of glass fibers and hydrodynamic conditions on the glass fiber bed placed on the screen was developed and tested. The results obtained for leaching of glass fibers in sodium borate and sodium phosphate solutions show the significant difference between the saturation levels of Ca, Al, and Si in tested leaching solutions. The observed difference in leaching chemistry caused significant differences in the head loss value and its time development. This preliminary conclusion opens a new research field to improve the NPPs but it has to be substantiated by additional records and sensitivity studies including uncertainties analysis.
The learnability of quantum states

Traditional quantum state tomography requires a number of measurements that grows exponentially with the number of qubits n. But using ideas from computational learning theory, we show that one can do exponentially better in a statistical setting. In particular, to predict the outcomes of most measurements drawn from an arbitrary probability distribution, one needs only a number of sample measurements that grows linearly with n. This theorem has the conceptual implication that quantum states, despite being exponentially long vectors, are nevertheless ‘reasonable’ in a learning theory sense. The theorem also has two applications to quantum computing: first, a new simulation of quantum one-way communication protocols and second, the use of trusted classical advice to verify untrusted quantum advice.
Zero-Shot Learning via Class-Conditioned Deep Generative Models

We present a deep generative model for Zero-Shot Learning (ZSL). Unlike most existing methods for this problem, that represent each class as a point (via a semantic embedding), we represent each seen/unseen class using a class-specific latent-space distribution, conditioned on class attributes. We use these latent-space distributions as a prior for a supervised variational autoencoder (VAE), which also facilitates learning highly discriminative feature representations for the inputs. The entire framework is learned end-to-end using only the seen-class training data. At test time, the label for an unseen-class test input is the class that maximizes the VAE lower bound. We further extend the model to a (i) semi-supervised/transductive setting by leveraging unlabeled unseen-class data via an unsupervised learning module, and (ii) few-shot learning where we also have a small number of labeled inputs from the unseen classes. We compare our model with several state-of-the-art methods through a comprehensive set of experiments on a variety of benchmark data sets.
Structure, Magnetism and Dynamics of Nanostructured Materials : A Theoretical Investigation

The present work illustrates how modern atomistic modeling and simulation can supplement the experiments performed in the laboratory by helping to resolve and understand the experimental information, by predicting new phenomena and providing useful hints to guide the development of innovative materials with original, specifically tailored properties. This paper presents our recent theoretical work on nanostructured materials including i) magnetic alloyed CoRh nanoparticles that are good candidates to combine both a large magnetic moment and a high magnetic anisotropy, and ii) nanoscale Mn films adsorbed on W substrates as an example of artificial magnetic material.
An Empirical Study on Fault Prediction using Token-Based Approach

Since exhaustive testing is not possible, prediction of fault prone modules can be used for prioritizing the components of a software system. Various approaches have been proposed for the prediction of fault prone modules. Most of them uses module metrics as quality estimators. In this study, we proposed a tokenbased approach and combine the metric evaluated from our approach with the module metrics to further improve the prediction results. We conducted the experiment on an open source project for evaluating the approach. The proposed approach is further compared with the existing fault prone filtering technique. The results show that the proposed approach is an improvement over fault prone filtering technique.