gebhart/patrepeval huggingface dataset:
Cryoablation of Prostate- Improving Efficacy and Safety (2020)

Cryoablation has been shown to be an effective therapy for all stages of prostate cancer. Though judged efficacious, complications of treatment and persistent disease, although minimal, show the need for improvement. To this end, research has focused on new technology design for cryosurgical apparatus and imaging techniques. Adjunctive therapy, focusing on increasing cell death by apoptosis, also plays a role in this new direction with the intent of increasing cell death in the frozen tissue. Additionally, incorporating methods of protecting adjacent structures, including the urethra, bladder neck sphincter, urogenital diaphragm, neurovascular bundles, and rectum, are critical to achieving a successful outcome and continue to evolve. Several strategies to protect these structures are now commonplace as part of a cryosurgical procedure. These strategies include real-time temperature monitoring, visualization of ice growth during freezing, active heating and even the injection of protective media have emerged as methods to protect these structures. Another more recent procedural application is partial gland ablation or image-targeted focal therapy, developed to maintain cancer control yet minimize the risk of collateral damage to the various structures. Each of these methods has been shown in vitro, in vivo, and clinically to be beneficial. This article describes the directions that cryoablation has taken in an effort to improve procedural efficacy while reducing/eliminating associated co-morbidities.
Stress and bowing engineering in passive silicon interposer (2015)

Three modifications of the structure of a 4 BEOL layers with 10×100μm TSV Si interposer are proposed to mitigate the tensile stress and release the interposer warpage. By using a thicker compressive PMD layer, reducing Metal1 thickness and using a higher compressive oxide to build the BEOL, the bowing contributions of the TSV, Metal1 and Via2 to Metal4 were reduced by 75%, 37% and 120% respectively. In total, the bowing at wafer level was reduced by 75% after full interposer front side processing.
Electric field effects in graphene/LaAlO3/SrTiO3 heterostructures and nanostructures (2015)

We report the development and characterization of graphene/LaAlO3/SrTiO3 heterostructures. Complex-oxide heterostructures are created by pulsed laser deposition and are integrated with graphene using both mechanical exfoliation and transfer from chemical-vapor deposition on ultraflat copper substrates. Nanoscale control of the metal-insulator transition at the LaAlO3/SrTiO3 interface, achieved using conductive atomic force microscope lithography, is demonstrated to be possible through the graphene layer. LaAlO3/SrTiO3-based electric field effects using a graphene top gate are also demonstrated. The ability to create functional field-effect devices provides the potential of graphene-complex-oxide heterostructures for scientific and technological advancement.
StormWatch (1995)

Recent research has offered programmers increased options for programming parallel computers by exposing system policies (e.g., memory coherence protocols) or by providing several programming paradigms (e.g. message passing and shared memory) on the same platform. Increased flexibility can lead to higher performance, but it is also a double-edged sword that demands a programmer understand his or her application and system at a more fundamental level. Our system, Tempest, allows a programmer to select or implement communication and memory coherence policies that fit an application's communication patterns. With it, we have achieved substantial performance gains without making major changes in programs. However, the process of selecting, designing, and implementing coherence protocols is difficult and time consuming, without tools to supply detailed information about an application's behavior and interaction with the memory system. StormWatch is a new visualization tool that aids a programmer through four mechanisms: tightly-coupled bidirectionally linked views, interactive filters, animation, and performance slicing. Multiple views present several aspects of program behavior simultaneously and show the same phenomenon from different perspectives. Real-time linking between views enables a programmer to explore levels of abstraction by changing a view and observing the effect on other views. Interactive filters, along with bidirectional linking, can isolate the effects of statements, loops, procedures, or files. StormWatch can also animate a program's dynamic behavior to show the evolution of program execution and communication. Finally, performance slicing captures causality among events. The examples in the paper illustrate how StormWatch helped us substantially improve the performance of two applications.
Paced QRS morphology predicts incident left ventricular systolic dysfunction and atrial fibrillation (2019)

Longer durations of all tested parameters in lead I were associated with increased rates of left ventricular systolic dysfunction. ICD implantation and CRT upgrade were also linked to increased TPC and pID durations. Paradoxically, patients with longer pID and pQRS had less incident atrial fibrillation.
Improved spectral flatness and sub-two-cycle pulse generation in octave-spanning Kerr frequency combs using micro-resonators with two zero-dispersion wavelengths (2013)

We show spectral flatness of Kerr frequency combs can be improved with a power fluctuation of &lt;20 dB over one-octave bandwidth, using flattened dispersion profile with two ZDWs. Sub-two-cycle optical pulses (7.5 fs) are generated from the combs.
Er doped As<inf>2</inf>S<inf>3</inf> photoresist for 3-D direct laser fabrication of 3-D nanostructures (2008)

We present a novel high-index-of-refraction (2.45) photoresist material based on erbium doped arsenic trisulfide. It shows room temperature photoluminescence at 1.5 microns wavelength, and can directly be used for direct laser writing.
Architecture and Performance of the Hardware Accelerators in IBM’s PowerEN Processor (2014)

Computation at the edge of a datacenter has unique characteristics. It deals with streaming data from multiple sources, going to multiple destinations, often requiring repeated application of one or more of several standard algorithmic kernels. These kernels, related to encryption, compression, XML Parsing and regular expression searching on the data, demand a high data processing rate and power efficiency. This suggests the use of hardware acceleration for key functions. However, robust general purpose processing support is necessary to orchestrate the flow of data between accelerators, as well as perform tasks that are not suited to acceleration. Further, these accelerators must be tightly integrated with the general purpose computation in order to keep invocation overhead and latency low. The accelerators must be easy for software to use, and the system must be flexible enough to support evolving networking standards.In this article, we describe and evaluate the architecture of IBM’s PowerEN processor, with a focus on PowerEN’s architectural enhancements and its on-chip hardware accelerators.PowerEN unites the throughput of application-specific accelerators with the programmability of general purpose cores on a single coherent memory architecture. Hardware acceleration improves throughput by orders of magnitude in some cases compared to equivalent computation on the general purpose cores. By offloading work to the accelerators, general purpose cores are freed to simultaneously work on computation less suited to acceleration.
Neural Subgraph Matching (2020)

Subgraph matching is the problem of determining the presence and location(s) of a given query graph in a large target graph. Despite being an NP-complete problem, the subgraph matching problem is crucial in domains ranging from network science and database systems to biochemistry and cognitive science. However, existing techniques based on combinatorial matching and integer programming cannot handle matching problems with both large target and query graphs. Here we propose NeuroMatch, an accurate, efficient, and robust neural approach to subgraph matching. NeuroMatch decomposes query and target graphs into small subgraphs and embeds them using graph neural networks. Trained to capture geometric constraints corresponding to subgraph relations, NeuroMatch then efficiently performs subgraph matching directly in the embedding space. Experiments demonstrate NeuroMatch is 100x faster than existing combinatorial approaches and 18% more accurate than existing approximate subgraph matching methods.
Data from Discovery of Candidate DNA Methylation Cancer Driver Genes (2023)

&lt;div&gt;Abstract&lt;p&gt;Epigenetic alterations, such as promoter hypermethylation, may drive cancer through tumor suppressor gene inactivation. However, we have limited ability to differentiate driver DNA methylation (DNAme) changes from passenger events. We developed DNAme driver inference–MethSig–accounting for the varying stochastic hypermethylation rate across the genome and between samples. We applied MethSig to bisulfite sequencing data of chronic lymphocytic leukemia (CLL), multiple myeloma, ductal carcinoma &lt;i&gt;in situ&lt;/i&gt;, glioblastoma, and to methylation array data across 18 tumor types in TCGA. MethSig resulted in well-calibrated quantile–quantile plots and reproducible inference of likely DNAme drivers with increased sensitivity/specificity compared with benchmarked methods. CRISPR/Cas9 knockout of selected candidate CLL DNAme drivers provided a fitness advantage with and without therapeutic intervention. Notably, DNAme driver risk score was closely associated with adverse outcome in independent CLL cohorts. Collectively, MethSig represents a novel inference framework for DNAme driver discovery to chart the role of aberrant DNAme in cancer.&lt;/p&gt;Significance:&lt;p&gt;MethSig provides a novel statistical framework for the analysis of DNA methylation changes in cancer, to specifically identify candidate DNA methylation driver genes of cancer progression and relapse, empowering the discovery of epigenetic mechanisms that enhance cancer cell fitness.&lt;/p&gt;&lt;p&gt;&lt;i&gt;This article is highlighted in the In This Issue feature, p. 2113&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;
Why offensive security needs engineering textbooks (2014)

Offensive security—or, in plain English, the practice of ­exploitation—has greatly enhanced our understanding of what it means for computers to be trustworthy. Having grown from hacker conventions that fit into a single room into a distinct engineering discipline in all but the name, offensive computing has so far been content with a jargon and an informal “hacker curriculum.” Now that it is unmistakably an industry, and an engineering specialization, it faces the challenge of defining itself as one, in a language that is understood beyond its own confines—most importantly, by makers of law and policy.
Glucose-6-phosphatase inhibitors for the treatment of Type 2 diabetes (2001)

Much biological knowledge has been gained over the years as to the role of glucose-6-phosphatase, (G-6-pase), enzyme complex in glucose homeostasis and in Type 2 diabetes. Glucose-6-phosphatase is mainly located in the liver and catalyses the terminal step in both gluconeogenesis and glycogenolysis. Another interesting feature is that the enzyme activity is several fold higher in diabetic animals and probably also in diabetic humans and therefore could be an important key player in the elevated hepatic glucose production seen in Type 2 diabetes. During the last nine years substantial efforts have been made, primarily by scientists at Hoechst (now Aventis) and Novo Nordisk, in order to discover novel compounds which inhibit the glucose-6-phosphatase enzyme complex and could be applied therapeutically in the treatment of Type 2 diabetes. These compounds, as well as other compounds published with inhibitory action on glucose-6-phosphatase, are reviewed. No compounds yet have been reported to be in clinical development.
Coronary Thrombi Increase PTCA Risk (1996)

The presence of intracoronary thrombus associated with coronary stenoses is significantly underestimated by angiography. Angioscopic intracoronary thrombi, the majority of which were not detected by angiography, are associated with an increased incidence of adverse outcomes after coronary angioplasty.
638: The Genetics of Renal Oncocytosis: A Possible Model for Neoplastic Progression to Chromophobe RCC (2005)

You have accessJournal of UrologyDiscussed Poster, Monday, May 23, 2005, 8:00 am - 12:00 pm1 Apr 2005638: The Genetics of Renal Oncocytosis: A Possible Model for Neoplastic Progression to Chromophobe RCC Robert G. Uzzo, Paul Cairns, Essel A. Dulaimi, Madelyn Feder, Joseph R. Testa, and Tahseen Al-Saleem Robert G. UzzoRobert G. Uzzo More articles by this author , Paul CairnsPaul Cairns More articles by this author , Essel A. DulaimiEssel A. Dulaimi More articles by this author , Madelyn FederMadelyn Feder More articles by this author , Joseph R. TestaJoseph R. Testa More articles by this author , and Tahseen Al-SaleemTahseen Al-Saleem More articles by this author View All Author Informationhttps://doi.org/10.1016/S0022-5347(18)34878-XAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "638: The Genetics of Renal Oncocytosis: A Possible Model for Neoplastic Progression to Chromophobe RCC." The Journal of Urology, 173(4S), p. 174 © 2016 by American Urological AssociationFiguresReferencesRelatedDetails Volume 173Issue 4SApril 2005Page: 174 Advertisement Copyright & Permissions© 2016 by American Urological AssociationMetricsAuthor Information Robert G. Uzzo More articles by this author Paul Cairns More articles by this author Essel A. Dulaimi More articles by this author Madelyn Feder More articles by this author Joseph R. Testa More articles by this author Tahseen Al-Saleem More articles by this author Expand All Advertisement PDF DownloadLoading ...
Analysis and experimental validation of a hybrid anti-lock braking controller for agricultural tractors (2022)

The anti-lock braking system (ABS) is one of the most important active safety systems in vehicles. The main purpose of the ABS is to avoid wheel locking in strong braking maneuvers while minimizing the stopping distance. While braking control is a well-solved problem in the automotive context, for the class of forestry vehicles it is still in its infancy, and detailed homologation rules have been provided only recently for agricultural tractors. The terrain roughness and variety, the possible large additional loads and trailers, the different size of front and rear wheels and the peculiar tyre properties make the ABS design for these vehicles quite challenging. This paper presents and compare the design of a wheel slip and wheel deceleration controller for tractors' automated braking, with its performance validated experimentally on different road friction conditions. A discussion on pros and cons of both solutions is provided, with the aim of informing the design of ABS controllers for these vehicles.
Iterative training of neural networks for intra prediction (2020)

This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising from the codec partitioning of images, each paired with its context. Then, iteratively, blocks are collected from the partitioning of images via the codec including the neural networks trained at the previous iteration, each paired with its context, and the neural networks are retrained on the new pairs. Thanks to this training, the neural networks can learn intra prediction functions that both stand out from those already in the initial codec and boost the codec in terms of rate-distortion. Moreover, the iterative process allows the design of training data cleansings essential for the neural network training. When the iteratively trained neural networks are put into H.265 (HM-16.15), -4.2% of mean dB-rate reduction is obtained. By moving them into H.266 (VTM-5.0), the mean dB-rate reduction reaches -1.9%.
Free space diffraction on active gratings with balanced phase and gain/loss modulations (2012)

A theoretical analysis of asymmetrical diffraction in Raman-Nath, intermediate and Bragg diffraction regimes is presented. The asymmetry is achieved by combining matched periodic modulations of the phase and of the loss/gain of the material, which enables the breakdown of optical symmetry and redirects all resulting optical energy in only positive or only negative diffraction orders, depending on the quarter period shift directions between the phase and the loss/gain modulations. Analytic expressions for the amplitudes of the diffraction orders are derived based on rigorous multimode coupled mode equations in slowly varying amplitude approximation.
Economic complexity unfolded: Interpretable model for the productive structure of economies (2018)

Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. It resides on the premise of hidden capabilities-fundamental endowments underlying the productive structure. In general, measuring the capabilities behind economic complexity directly is difficult, and indirect measures have been suggested which exploit the fact that the presence of the capabilities is expressed in a country's mix of products. We complement these studies by introducing a probabilistic framework which leverages Bayesian non-parametric techniques to extract the dominant features behind the comparative advantage in exported products. Based on economic evidence and trade data, we place a restricted Indian Buffet Process on the distribution of countries' capability endowment, appealing to a culinary metaphor to model the process of capability acquisition. The approach comes with a unique level of interpretability, as it produces a concise and economically plausible description of the instantiated capabilities.
A Spatial Basis Coverage Approach For Uplink Training And Scheduling In Massive MIMO Systems (2018)

Massive multiple-input multiple-output (massive MIMO) can provide large spectral and energy efficiency gains. Nevertheless, its potential is conditioned on acquiring accurate channel state information (CSI). In time division duplexing (TDD) systems, CSI is obtained through uplink training which is hindered by pilot contamination. The impact of this phenomenon can be relieved using spatial division multiplexing, which refers to partitioning users based on their spatial information and processing their signals accordingly. The performance of such schemes depend primarily on the implemented grouping method. In this paper, we propose a novel spatial grouping scheme that aims at managing pilot contamination while reducing the required training overhead in TDD massive MIMO. Herein, user specific decoding matrices are derived based on the columns of the discrete Fourier transform matrix (DFT), taken as a spatial basis. Copilot user groups are then formed in order to obtain the best coverage of the spatial basis with minimum overlapping between decoding matrices. We provide two algorithms that achieve the desired grouping and derive their respective performance guarantees. We also address inter-cell copilot interference through efficient pilot sequence allocation, leveraging the formed copilot groups. Various numerical results are provided to showcase the efficiency of the proposed algorithms.
Antibody to VLA-4, but not to L-selectin, protects neuronal M2 muscarinic receptors in antigen-challenged guinea pig airways. (1997)

Antigen challenge of sensitized guinea pigs decreases the function of inhibitory M2 muscarinic autoreceptors on parasympathetic nerves in the lung, potentiating vagally induced bronchoconstriction. Loss of M2 receptor function is associated with the accumulation of eosinophils around airway nerves. To determine whether recruitment of eosinophils via expression of VLA-4 and L-selectin is critical for loss of M2 receptor function, guinea pigs were pretreated with monoclonal antibodies to VLA-4 (HP1/2) or L-selectin (LAM1-116). Guinea pigs were sensitized and challenged with ovalbumin, and M2 receptor function was tested. In controls, blockade of neuronal M2 muscarinic receptors by gallamine potentiated vagally induced bronchoconstriction, while in challenged animals this effect was markedly reduced, confirming M2 receptor dysfunction. Pretreatment with HP1/2, but not with LAM1-116, protected M2 receptor function in the antigen-challenged animals. HP1/2 also inhibited the development of hyperresponsiveness, and selectively inhibited accumulation of eosinophils in the lungs as measured by lavage and histology. Thus, inhibition of eosinophil influx into the lungs protects the function of M2 muscarinic receptors, and in so doing, prevents hyperresponsiveness in antigen-challenged guinea pigs.
Aggregation Suppression of Proteins by Arginine During Thermal Unfolding (2006)

Arginine has been used to suppress aggregation of proteins during refolding and purification. We have further studied in this paper the aggregation-suppressive effects of arginine on two commercially important proteins, i.e., interleukine-6 (IL-6) and a monoclonal antibody (mAb). These proteins show extensive aggregation in aqueous buffers when subjected to thermal unfolding. Arginine suppresses aggregation concentration-dependently during thermal unfolding. However, this effect was not specific to arginine, as guanidine hydrochloride (GdnHCl) at identical concentrations also was effective. While equally effective in aggregation suppression during thermal unfolding, arginine and GdnHCl differed in their effects on the structure of the native proteins. Arginine showed no apparent adverse effects on the native protein, while GdnHCl induced conformational changes at room temperature, i.e., below the melting temperature. These additives affected the melting temperature of IL-6 as well; arginine increased it concentration-dependently, while GdnHCl increased it at low concentration but decreased at higher concentration. These results clearly demonstrate that arginine suppresses aggregation via different mechanism from that conferred by GdnHCl.
Understanding Road Layout from Videos as a Whole (2020)

In this paper, we address the problem of inferring the layout of complex road scenes from video sequences. To this end, we formulate it as a top-view road attributes prediction problem and our goal is to predict these attributes for each frame both accurately and consistently. In contrast to prior work, we exploit the following three novel aspects: leveraging camera motions in videos, including context cuesand incorporating long-term video information. Specifically, we introduce a model that aims to enforce prediction consistency in videos. Our model consists of one LSTM and one Feature Transform Module (FTM). The former implicitly incorporates the consistency constraint with its hidden states, and the latter explicitly takes the camera motion into consideration when aggregating information along videos. Moreover, we propose to incorporate context information by introducing road participants, e.g. objects, into our model. When the entire video sequence is available, our model is also able to encode both local and global cues, e.g. information from both past and future frames. Experiments on two data sets show that: (1) Incorporating either globalor contextual cues improves the prediction accuracy and leveraging both gives the best performance. (2) Introducing the LSTM and FTM modules improves the prediction consistency in videos. (3) The proposed method outperforms the SOTA by a large margin.