gebhart/patrepeval huggingface dataset:
Discretizing large traceable vessels and using DE‐MRI perfusion maps yields numerical temperature contours that match the MR noninvasive measurements (2001)

The success of hyperthermia treatments is dependent on thermal dose distribution. However, the three‐dimensional temperature distribution remains largely unknown. Without this knowledge, the relationship between thermal dose and outcome is noisy, and therapy cannot be optimized. Accurate computations of thermal distribution can contribute to an optimized therapy. The hyperthermia modeling group in the Department of Radiotherapy, University Medical Center Utrecht devised a Discrete Vasculature [Kotte et al., Phys. Med. Biol. 41 , 865–884 (1996)] model that accounts for the presence of vessel trees in the computational domain. The vessel tree geometry is tracked using magnetic resonance (MR) angiograms to a minimum diameter between 0.6 and 1 mm. However, smaller vessels (0.2–0.6 mm) are known to account for significant heat transfer. The hyperthermia group at Duke University Medical Center has proposed using perfusion maps derived from dynamic‐enhanced magnetic resonance imaging to account for the tissue perfusion heterogeneity [Craciunescu et al., Int. J. Hyperthermia 17 , 221–239 (2001)]. In addition, techniques for noninvasive temperature measurements have been devised to measure temperatures in vivo [Samulski et al., Int. J. Hypertherminal, 819–829 (1992)]. In this work, a patient with high‐grade sarcoma has been retrospectively modeled to determine the temperature distribution achieved during a hyperthermia treatment. Available for this model were MR depicted geometry, angiograms, perfusion maps, as necessary for accurate thermal modeling, as well as MR thermometry data for validation purposes. The vasculature assembly through modifiable potential program [Van Leeuwen et al., IEEE Trans. Biomed. Eng. 45 , 596–604 (1998)] was used in order to incorporate the traceable large vessels. Temperature simulations were made using different approaches to describe perfusion. The simulated cases were the bioheat equation with constant perfusion rates per tissue type, perfusion maps alone, tracked vessel tree and perfusion maps, and generated vessel tree. The results were compared with MR thermometry data for a single patient data set, concluding that a combination between large traceable vessels and perfusion map yields the best results for this particular patient. The technique has to be repeated on several patients, first with the same type of malignancy, and after that, on patients having malignancies at other different sites.
Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs (2003)

Intrinsic parameter fluctuations introduced by discreteness of charge and matter will play an increasingly important role when semiconductor devices are scaled to decananometer and nanometer dimensions in next-generation integrated circuits and systems. In this paper, we review the analytical and the numerical simulation techniques used to study and predict such intrinsic parameters fluctuations. We consider random discrete dopants, trapped charges, atomic-scale interface roughness, and line edge roughness as sources of intrinsic parameter fluctuations. The presented theoretical approach based on Green's functions is restricted to the case of random discrete charges. The numerical simulation approaches based on the drift diffusion approximation with density gradient quantum corrections covers all of the listed sources of fluctuations. The results show that the intrinsic fluctuations in conventional MOSFETs, and later in double gate architectures, will reach levels that will affect the yield and the functionality of the next generation analog and digital circuits unless appropriate changes to the design are made. The future challenges that have to be addressed in order to improve the accuracy and the predictive power of the intrinsic fluctuation simulations are also discussed.
Wireless micromachined ceramic pressure sensors (1999)

In high temperature applications, such as pressure sensing in turbine engines and compressors, high-temperature materials and data retrieval methods are required. The microelectronics packaging infrastructure provides well-developed, high temperature ceramic materials, processing tools, and processing techniques that have the potential for applicability in high temperature sensors. A completely passive wireless telemetry scheme, which relies on a frequency shift output, has been integrated with the sensors, thereby eliminating the need for contacts, active elements, or power supplies to be contained within the sensor. This simplicity of sensor design allows the sensor to be exposed to elevated temperatures. As a proof-of concept, a wireless micromachined ceramic pressure sensor has been designed, fabricated, tested, and, compared with theoretical models. Sensors have been operated up to 200/spl deg/C and in pressure ranges from 0-1 bar and from 0-100 bar. The measured sensitivity of a fabricated sensor, expressed in frequency shift per pressure difference, is 2.6 MHz/bar, which compares well to the theoretically determined sensitivity of 2.2 MHz/bar.
Curve-Centric Volume Reformation for Comparative Visualization (2009)

We present two visualization techniques for curve-centric volume reformation with the aim to create compelling comparative visualizations. A curve-centric volume reformation deforms a volume, with regards to a curve in space, to create a new space in which the curve evaluates to zero in two dimensions and spans its arc-length in the third. The volume surrounding the curve is deformed such that spatial neighborhood to the curve is preserved. The result of the curve-centric reformation produces images where one axis is aligned to arc-length, and thus allows researchers and practitioners to apply their arc-length parameterized data visualizations in parallel for comparison. Furthermore we show that when visualizing dense data, our technique provides an inside out projection, from the curve and out into the volume, which allows for inspection what is around the curve. Finally we demonstrate the usefulness of our techniques in the context of two application cases. We show that existing data visualizations of arc-length parameterized data can be enhanced by using our techniques, in addition to creating a new view and perspective on volumetric data around curves. Additionally we show how volumetric data can be brought into plotting environments that allow precise readouts. In the first case we inspect streamlines in a flow field around a car, and in the second we inspect seismic volumes and well logs from drilling.
Treatment for chronic depression using schema therapy. (2013)

Schema therapy (ST) is an integrative treatment approach to chronic lifelong problems with an established effectiveness for treating personality disorders. This article describes the adaptation of ST to chronic depression by reviewing the literature on the underlying risk factors to chronic depression. A model of chronic depression is presented, describing the interplay between empirically supported risk factors to chronic depression (early adversity, cognitive factors, personality pathology, interpersonal factors). We provide a treatment protocol of ST for chronic depression describing techniques that can be used in ST to target these underlying risk factors. Based on the current body of empirical evidence for the underlying risk factors to chronic depression, ST appears to be a promising new treatment approach to chronic depression, as it directly targets these underlying risk factors. © 2013 American Psychological Association.
Architectures for Digital Signal Processing (1998)

From the Publisher:
Digital Signal Processing is a rapidly expanding area for evaluation and development of efficient measures for representation, transformation and manipulation of signals. This book fuses signal processing algorithms and VLSI circuit design to assist digital signal processing architecture developers. The author also shows how this technique can be used in applications such as: signal transmission and storage, manufacturing process quality control and assurance, autonomous mobile system control and biomedical process analysis.
Fibrinogen Cleavage by the <i>Streptococcus pyogenes</i> Extracellular Cysteine Protease and Generation of Antibodies That Inhibit Enzyme Proteolytic Activity (1999)

The extracellular cysteine protease from Streptococcus pyogenes is a virulence factor that plays a significant role in host-pathogen interaction. Streptococcal protease is expressed as an inactive 40-kDa precursor that is autocatalytically converted into a 28-kDa mature (active) enzyme. Replacement of the single cysteine residue involved in formation of the enzyme active site with serine (C192S mutation) abolished detectable proteolytic activity and eliminated autocatalytic processing of zymogen to the mature form. In the present study, we investigated activity of the wild-type (wt) streptococcal protease toward human fibrinogen and bovine casein. The former is involved in blood coagulation, wound healing, and other aspects of hemostasis. Treatment with streptococcal protease resulted in degradation of the COOH-terminal region of fibrinogen alpha chain, indicating that fibrinogen may serve as an important substrate for this enzyme during the course of human infection. Polyclonal antibodies generated against recombinant 40- and 28-kDa (r40- and r28-kDa) forms of the C192S streptococcal protease mutant exhibited high enzyme-linked immunosorbent assay titers but demonstrated different inhibition activities toward proteolytic action of the wt enzyme. Activity of the wt protease was readily inhibited when the reaction was carried out in the presence of antibodies generated against r28-kDa C192S mutant. Antibodies produced against r40-kDa C192S mutant had no significant effect on proteolysis. These data suggest that the presence of the NH(2)-terminal prosegment prevents generation of functionally active antibodies and indicate that inhibition activity of antibodies most likely depends on their ability to bind the active-site region epitope(s) of the protein.
Fairness and isolation in multi-tenant storage as optimization decomposition (2013)

Shared storage services enjoy wide adoption in commercial clouds. But most systems today provide weak performance isolation and fairness between tenants, if at all. Most approaches to multi-tenant resource allocation are based either on per-VM allocations or hard rate limits that assume uniform workloads to achieve high utilization. Instead, Pisces, our system for shared key-value storage, achieves datacenterwide per-tenant performance isolation and fairness. Pisces achieves per-tenant weighted fair sharing of system resources across the entire shared service, even when partitions belonging to different tenants are co-located and when demand for different partitions is skewed or timevarying. The focus of this paper is to highlight the optimization model that motivates the decomposition of Pisces's fair sharing problem into four complementary mechanisms--- partition placement, weight allocation, replica selection, and weighted fair queuing---that operate on different time-scales to provide system-wide max-min fairness. An evaluation of our Pisces storage prototype achieves nearly ideal (0.98 Min- Max Ratio) fair sharing, strong performance isolation, and robustness to skew and shifts in tenant demand.
Adaptive Human-Robot Interactions for Multiple Unmanned Aerial Vehicles (2021)

Advances in unmanned aircraft systems (UAS) have paved the way for progressively higher levels of intelligence and autonomy, supporting new modes of operation, such as the one-to-many (OTM) concept, where a single human operator is responsible for monitoring and coordinating the tasks of multiple unmanned aerial vehicles (UAVs). This paper presents the development and evaluation of cognitive human-machine interfaces and interactions (CHMI2) supporting adaptive automation in OTM applications. A CHMI2 system comprises a network of neurophysiological sensors and machine-learning based models for inferring user cognitive states, as well as the adaptation engine containing a set of transition logics for control/display functions and discrete autonomy levels. Models of the user’s cognitive states are trained on past performance and neurophysiological data during an offline calibration phase, and subsequently used in the online adaptation phase for real-time inference of these cognitive states. To investigate adaptive automation in OTM applications, a scenario involving bushfire detection was developed where a single human operator is responsible for tasking multiple UAV platforms to search for and localize bushfires over a wide area. We present the architecture and design of the UAS simulation environment that was developed, together with various human-machine interface (HMI) formats and functions, to evaluate the CHMI2 system’s feasibility through human-in-the-loop (HITL) experiments. The CHMI2 module was subsequently integrated into the simulation environment, providing the sensing, inference, and adaptation capabilities needed to realise adaptive automation. HITL experiments were performed to verify the CHMI2 module’s functionalities in the offline calibration and online adaptation phases. In particular, results from the online adaptation phase showed that the system was able to support real-time inference and human-machine interface and interaction (HMI2) adaptation. However, the accuracy of the inferred workload was variable across the different participants (with a root mean squared error (RMSE) ranging from 0.2 to 0.6), partly due to the reduced number of neurophysiological features available as real-time inputs and also due to limited training stages in the offline calibration phase. To improve the performance of the system, future work will investigate the use of alternative machine learning techniques, additional neurophysiological input features, and a more extensive training stage.
Hydroxyatrazine <i>N</i> -Ethylaminohydrolase (AtzB): an Amidohydrolase Superfamily Enzyme Catalyzing Deamination and Dechlorination (2007)

Hydroxyatrazine [2-(N-ethylamino)-4-hydroxy-6-(N-isopropylamino)-1,3,5-triazine] N-ethylaminohydrolase (AtzB) is the sole enzyme known to catalyze the hydrolytic conversion of hydroxyatrazine to N-isopropylammelide. AtzB, therefore, serves as the point of intersection of multiple s-triazine biodegradative pathways and is completely essential for microbial growth on s-triazine herbicides. Here, atzB was cloned from Pseudomonas sp. strain ADP and its product was purified to homogeneity and characterized. AtzB was found to be dimeric, with subunit and holoenzyme molecular masses of 52 kDa and 105 kDa, respectively. The k(cat) and K(m) of AtzB with hydroxyatrazine as a substrate were 3 s(-1) and 20 microM, respectively. Purified AtzB had a 1:1 zinc-to-subunit stoichiometry. Sequence analysis revealed that AtzB contained the conserved mononuclear amidohydrolase superfamily active-site residues His74, His76, His245, Glu248, His280, and Asp331. An intensive in vitro investigation into the substrate specificity of AtzB revealed that 20 of the 51 compounds tested were substrates for AtzB; this allowed for the identification of specific substrate structural features required for catalysis. Substrates required a monohydroxylated s-triazine ring with a minimum of one primary or secondary amine substituent and either a chloride or amine leaving group. AtzB catalyzed both deamination and dechlorination reactions with rates within a range of one order of magnitude. This differs from AtzA and TrzN, which do not catalyze deamination reactions, and AtzC, which is not known to catalyze dechlorination reactions.
5GC Network and MEC UPF Data Collection Scheme Research (2021)

A rapid development of 5G network has led to the explosive growth of 5G data, the growth of data makes operators face opportunities and challenges. In order not to make operators become pipeline providers, it is very important to understand the content of data in pipelines. DPI data collection has always been an important means for operators to understand network data operation, because 5G SA network is a regional network, compared with 4G and 5G NSA network, data collection methods have a great difference, while soft collection relative to traditional DPI collection also has the characteristics of flexibility, convenient and accurate correlation, so how to choose different collection methods based on different scenarios is very important content. This paper elaborates the scheme of data collection of 5G SA network and MEC UPF network, compares the characteristics and differences of hard and soft collection in detail according to the characteristics of different network structures combined with hard and soft collection, and gives some suggestions for the construction scheme of 5G SA network and MEC UPF network.
Proposal of a support system for device driver generation (2003)

Writing device drivers is one of the most difficult tasks to develop or port operating systems (OSs). A device driver needs to be described according to the target device and OS. In the description, programmers must know information about hardware such as specifications of devices and carefully describe complex parts such as timing control. This paper proposes a support system for device driver generation. The inputs for the system are device driver specification which shows operations of the device, OS dependent specification which shows dependent parts on the OS, and device dependent specification which shows dependent parts on the device. As an example, network devices are adopted. The inputs to generate device drivers by the proposed system are described.
Catalytic Unfolding and Proteolysis of Cytochrome <i>c</i> Induced by Synthetic Binding Agents (2004)

A class of polyanionic copper porphyrin dimers is shown to selectively increase the susceptibility of cytochrome c to proteolysis through binding-induced disruption of tertiary and secondary structure. The free energy of the protein conformation leading to proteolytic attack is stabilized by about 2.4 kcal/mol in the bound state. The proteolytic acceleration is catalytic in nature, requiring only a fraction of an equivalent of metalloporphyrin to effect complete, rapid digestion in the presence of a protease.
Composite Layer-by-Layer (LBL) Assembly with Inorganic Nanoparticles and Nanowires (2008)

New assembly techniques are required for creating advanced materials with enough structural flexibility to be tuned for specific applications, and to be practical, the techniques must be implemented at relatively low cost. Layer-by-layer (LBL) assembly is a simple, versatile, and significantly inexpensive approach by which nanocomponents of different groups can be combined to coat both macroscopically flat and non-planar (e.g., colloidal core-shell particles) surfaces. Compared with other available assembly methods, LBL assembly is simpler and more universal and allows more precise thickness control at the nanoscale. LBL can be used to combine a wide variety of species--including nanoparticles (NPs), nanosheets, and nanowires (NWs)--with polymers, thus merging the properties of each type of material. This versatility has led to recent exceptional growth in the use of LBL-generated nanocomposites. This Account will focus on the materials and biological applications of introducing inorganic nanocrystals into polymer thin films. Combining inorganic NPs and NWs with organic polymers allows researchers to manipulate the unique properties in the nanomaterial. We describe the LBL assembly technique for introducing metallic NPs into polymers in order to generate a material with combined optomechanical properties. Similarly, LBL assembly of highly luminescent semiconductor NPs like HgTe or CdTe with poly(diallyldimethylammonium chloride) (PDDA) was used to create uniform optical-quality coatings made on optical fibers and tube interiors. In addition, LBL assembly with inorganic nanosheets or clay molecules is reported for fabricating films with strong mechanical and ion transport properties, and the technique can also be employed to prepare Au/TiO(2) core/sheath NWs. The LBL approach not only will be useful for assembly of inorganic nanocrystals with various polymers but can be further applied to introduce specific functions. We discuss how the expanded use of NWs and carbon nanotubes (CNTs) in nanocomposite materials holds promise in the design of conductive films and new nanoscale devices (e.g., thin-film transistors). New photonic materials, sensors, and amplifiers can be constructed using multilayer films of NPs and can enable fabrication of hybrid devices. On the biological side, inorganic nanoshells were used as assembly tools with the goal of detecting neurotransmitters (specifically, dopamine) directly inside brain cells. In addition, the stability of different cell lines was tested for fabricating biocompatible films using LBL. NP LBL assembly was also used for homogeneous and competitive fluorescence quenching immunoassay studies for biotin and anti-biotin immunoglobulin molecules. Finally, introduction of biomolecules with inorganic NPs for creating biocompatible surfaces could also lead to new directions in the field of biomedical applications.
18.1 A 20nm 9Gb/s/pin 8Gb GDDR5 DRAM with an NBTI monitor, jitter reduction techniques and improved power distribution (2016)

A 9Gb/s/pin 8Gb GDDR5 DRAM is implemented using a 20nm CMOS process. To cover operation up to 9Gb/s, which is the highest data-rate among implemented GDDR5 DRAMs [1], this work includes an NBTI monitor, a WCK clock receiver with equalizing and duty-cycle correction modes, CML-to-CMOS converters with wide range operation, active resonant loads at the end of WCK lane, and an on-chip de-emphasis circuit at a 4-to-1 multiplexer output as shown in Fig. 18.1.1. In addition, extra power pads improve the power distribution and release the frequency limitation at the memory core.
Actinomyces Species, Streptococci, and Enterococcus faecalis in Primary Root Canal Infections (2002)

The purpose of this study was to evaluate the prevalence of Actinomyces species, streptococci, and Enterococcus faecalis in primary root canal infections by using a molecular genetic method. Samples were obtained from 53 infected teeth, of which 27 cases were diagnosed as acute periradicular abscesses. DNA was extracted to evaluate the occurrence of 13 bacterial species by using whole genomic DNA probes and checkerboard DNA-DNA hybridization. Polymerase chain reaction using an ubiquitous bacterial primer was undertaken to check the presence of bacterial DNA in clinical samples. All root canal samples contained bacteria as demonstrated by polymerase chain reaction. The checkerboard DNA-DNA hybridization assay allowed the detection of streptococci in 22.6% of the samples, Actinomyces species in 9.4%, and E. faecalis in 7.5%. The most prevalent species were members of the Streptococcus anginosus group. With regard to the asymptomatic lesions, the most prevalent species were S. intermedius (11.5% of the cases), E. faecalis (11.5%), and S. anginosus (7.7%). S. constellatus was the most prevalent species in pus samples (25.9% of the cases). The other most prevalent species in abscessed teeth were A. gerencseriae (14.8%), S. gordonii (11.1%), S. intermedius (11.1%), A. israelii (7.4%), S. anginosus (7.4%), and S. sanguis (7.4%). S. constellatus was the only species positively associated with acute periradicular abscess (p < 0.01).
Adipose Tissue Protocols (2001)

Adipose tissue is recognized to be exquisitely sensitive to hormone action, and is also now recognized as a secretory and endocrine organ required for reproduction and good health. Adipocytes are "sma