gebhart/patrepeval huggingface dataset:
Dynamic local models for stable multi-contact haptic interaction with deformable objects (2003)

This paper describes a new technique for allowing multiple users to haptically interact with a set of deformable slowly-simulated objects in a stable manner Stability has been approached in the past by various researchers using passivity theory in order to avoid having to model the human operator closing the haptic loop. None of these solutions however can work well without the use of high update rates and thus break down in the case of haptic interaction with slowly simulated virtual environments such as the ones featuring highly precise deformable objects. This is particularly true for the case of surgical simulation with force feedback, where precision is a key issue and where complexity can reach high levels. The techniques presented in this paper are based on the concepts of local model for haptic interaction adapted to deformable objects. Such approach allows multiple users to stably interact with a same object while feeling the influence of other users on the same object. Experimental results employing a PHANTOM haptic interface are proposed for a simple example.
Using RPL Headers Without IP-in-IP (2010)

Routing for Low Power and Lossy Networks (RPL) is a routing protocol
designed for Low power and Lossy Networks (LLNs). RPL includes routing
information in IPv6 data plane datagrams to help maintain the routing
topology. When forwarding a datagram into a RPL domain, a RPL router
may need to expand the datagram to include routing information in IPv6
Extension headers. A generic solution has been defined that uses IP-
in-IP tunneling to include RPL routing information. This document
describes an alternative to inserting and removing RPL information in
datagrams without the use of IP-in-IP tunneling.
Characterisation and Modelling of 22-nm FD-SOI Transistors Operating at Cryogenic Temperatures (2022)

The semiconductor approach to quantum computing appears the best positioned in the race for fully integrated quantum cores incorporating both the qubit structures and electronics necessary to read and control them. One of the major limitations hampering the efforts is the lack of semiconductor device models compatible with commercial EDA tools that can accurately predict the effects of cryogenic temperatures over integrated devices electrical parameters. To obtain such models, the devices must be measured at that extremely low temperature over a wide range of operating conditions. This paper presents preliminary characterisation results of devices used in a quantum processing unit in a 22-nm fully depleted silicon-on-insulator (FD-SOI) CMOS process, as well as simulation results using a Verilog-A model based on measured I/V curves for different FD-SOI transistors.
Deep Learning–Generated Synthetic MR Imaging STIR Spine Images Are Superior in Image Quality and Diagnostically Equivalent to Conventional STIR: A Multicenter, Multireader Trial (2023)

Synthetically created STIR spine MR images were diagnostically interchangeable with acquired STIR, while providing significantly higher image quality, suggesting routine clinical practice potential.
Efficient Inverse Design of Large-Area Metasurfaces for Incoherent Light (2022)

Incoherent light is ubiquitous, yet designing optical devices that can handle its random nature is very challenging, since directly averaging over many incoherent incident beams can require a huge number of scattering calculations. We show how to instead solve this problem with a reciprocity technique that leads to 3 orders of magnitude speedup: one Maxwell solve (using any numerical technique) instead of thousands. This improvement enables us to perform efficient inverse design, large-scale optimization of metasurfaces for applications such as light collimators and concentrators. We show the impact of the angular distribution of incident light on the resulting performance and show especially promising designs for the case of “annular” beams distributed only over nonzero angles.
Optimization of Perturbation Parameters for Simulated Free Shear Layer Flow (2014)

This paper provides details on the optimization of phase and amplitude of perturbations for simulated free shear layer flows. The goal of the optimization is to maximize or minimize the rate of growth of the shear layer, based upon first-principles physics-based simulations that represent solutions to the fully nonlinear Navier-Stokes equations. These simulations have been obtained using a unique method [1, 2] that considerably reduces the computational burden normally associated with obtaining such solutions. In fact, the development of active flow control methodologies is often based upon reduced order models of the Navier-Stokes equations to avoid this computational overhead. Various regression methods were used to approximate the shear layer thickness as a function of the phase and amplitude of perturbations used to excite the flow dynamics as a proxy for using a simulation based upon first principles, in order to reduce computational burden even further. It was found that nonlinear regression methods...
Barrier heights and Fermi level pinning in metal contacts on p-type GaN (2020)

In this work, we investigate the current–voltage (I–V) characteristics of various metal contacts such as Ni/Au, Ir/Au, Ru/Au, Mo/Au, and W/Au on p-GaN. For this, we fabricated different bilayer metal contacts on the same epitaxial heterostructure of GaN, which ensures the uniformity of the experimental data. I–V measurements were then carried out for circular and/or linear contact pads with different spacing values. In each case, the Schottky barrier height of the metal contacts is calculated using the reverse I–V method. A strong Fermi level pinning was found in all these structures on p-GaN, with a pinning factor of ∼0.15. In addition, a very low Ohmic contact resistivity of 3.45 × 10−6 Ω cm2 was measured for the Ru/Au contacts on p-GaN.
A Synergy of a Closed-Loop DVFS Controller and CPU Hot-Plug For Run-Time Thermal Management in Multicore Systems (2019)

In the era of nanoelectronic circuits, temperature largely affects reliability and static power consumption of systems. In fact, temperature control in modern circuits is considered as a crucial system function, along with low-power operation. To this end, numerous thermal management approaches exist on the hardware, firmware and software layer. A widely used technique for that matter is dynamic voltage and frequency scaling (DVFS), aiming to control temperature by proper voltage and frequency decisions. CPU hot-plug is another technique brought from reliability and fault-tolerance domain that can be utilized for thermal management purposes. To this end, our work examines the thermal profile of an NXP IMX6Q board when different DVFS and CPU hot-plug actuations are applied. In addition, we move further and propose a synergy between the two methods while studying their effect on chip temperature, performance and energy consumption.
Invasion of the neurovascular bundle by prostate cancer: evaluation with MR imaging. (1991)

Preservation of the neurovascular bundle (NVB) and potency without compromising tumor control are current objectives of radical retropubic prostatectomy as treatment for prostate cancer, but preoperative determination of whether cancer has invaded the NVB can be difficult. The use of conventional body-coil magnetic resonance (MR) imaging to make this preoperative determination was evaluated in 50 patients with biopsy-proved cancer. All patients underwent radical retropubic prostatectomy after MR imaging. MR imaging, surgical, and pathologic data were correlated relative to tumor location and volume, Gleason grade, presence of capsular penetration, and depth of NVB invasion. The sensitivity of MR imaging for invasion was 68%, specificity was 59%, and overall accuracy was 64%. Results of this study indicate that MR imaging can help identify the NVB and predict invasion of the NVB by tumor, but the usefulness of the technique is limited by the lack of spatial resolution associated with use of the whole-body coil.
Plasma Substance-P in Neuroendocrine Tumors and Idiopathic Flushing: The Value of Pentagastrin Stimulation Tests and the Effects of Somatostatin Analog* (1990)

We examined the role of the potent vasoactive kinin substance-P (SP) in flushing derived from various causes. SP was measured in plasma after acetone/ether extraction using an antiserum directed at the carboxy-terminal 5-11 amino acid region of undecapeptide SP. The antiserum had less than 1% cross-reaction with the other neurokinins, neurokinin-A and neuropeptide-K, that derive from the beta-preprotachykinin gene and share carboxy-terminal residues. Basal and pentagastrin-stimulated SP levels were measured in 22 healthy controls, 11 patients with histologically proven carcinoid tumors, 8 patients with tumors other than carcinoid, and 7 patients with idiopathic flushing (IF). Basal SP levels were less than 10 pg/mL in normal subjects. All patients with midgut carcinoid tumors had SP levels greater than 25 pg/mL, as did 7 of 8 patients with noncarcinoid tumors and 5 of 7 patients with IF. Using 50 pg/mL as the cutoff point, the sensitivity was 63% for detection of a tumor, and 100% of nontumor patients were excluded. Pentagastrin administration uniformly induced flushing and caused a rise in SP levels greater than 150 pg/mL in 5 of 10 patients with carcinoid tumors, 3 of 8 with noncarcinoid tumors, and 0 of 7 with IF, i.e. a SP rise of more than 100 pg/mL suggests a tumor. Administration of somatostatin (150 micrograms) 0.5 h before the pentagastrin abolished flushing in all carcinoid patients and reduced SP levels, but not into the normal range. Long term treatment with SMS significantly reduced flushing and lowered SP levels, but did not restore these to normal. We conclude that 90% of patients with carcinoid/noncarcinoid tumor have raised COOH-terminal SP levels. A basal level above 50 pg/mL or a pentagastrin-stimulated rise of more than 100 pg/mL distinguishes carcinoid from IF. The dissociation between SP concentrations and flushing suggests that SP may not be the only kinin involved in the flushing associated with carcinoid tumors.
Abstract WMP86: Novel, High-tech Walking Recovery Program Improves Motor Recovery (2013)

Introduction: Although there are a number of research studies investigating walking recovery after stroke, most focus on one intervention or piece of equipment in order to achieve a controlled experimental environment. Such studies have yet to produce a comprehensive clinical practice guideline (CPG) for gait training. To fill this void, we implemented a clinical program for walking recovery, iWalk™, using a variety of advanced technologies, and an evidence-based CPG to assist in making assessment and intervention decisions. This study compares outcomes of patients treated using a traditional therapy program to those treated with the iWalk program. Hypothesis: The systematic application of a novel, evidence-based CPG for walking recovery will result in superior motor performance when compared to traditional therapy in patients post stroke. Methods: This study included all stroke survivors admitted to a rehab facility during a 24 month period, with the cohort split into two groups. The control group received traditional rehabilitation (n=152) and the experimental group received the iWalk protocol (n=165). Since full implementation of the protocol could not be assigned a specific date, a buffer group (n=50) between the two groups was excluded from this analysis. Results: Functional Independence Measure: An interaction between age and treatment program was detected (p&lt;0.001). Motor FIM scores showed greater improvement for younger patients in iWalk than in the traditional therapy program. Length of Stay: When examining LOS as an outcome, an interaction between treatment group and total FIM score was detected (p=0.073). Patients who were lower functioning on admission were more likely to be discharged home if they were in the iWalk program. Examining LOS as a predictor, the difference in timed-up-and-go scores between the treatment groups reveals that iWalk seems to be better for a LOS around 3 weeks, but is not significant (p&gt;0.05). Conclusions: This study demonstrates outcome differences that favor iWalk. Additionally, there may be a LOS range which optimizes motor recovery. It is unclear whether a patient’s LOS is a reflection of the improvement of clinical variables or practical reasons. Further work is necessary on this topic.
Channel Training & Estimation for Reconfigurable Intelligent Surfaces: Exposition of Principles, Approaches, and Open Problems (2023)

Reconfigurable intelligent surfaces (RIS) are passive controllable arrays of small reflectors that direct electromagnetic energy towards or away from the target nodes, thereby allowing better management of signals and interference in a wireless network. The RIS has the potential for significantly improving the performance of wireless networks. Unfortunately, RIS also multiplies the number of Channel State Information (CSI) coefficients between the transmitter and receiver, which magnifies the challenges in estimating and communicating the channel state information. Furthermore, the simplicity and cost-effectiveness of the passive RIS also implies that the incoming links are not locally estimated at the RIS, and fresh pilots are not inserted into outgoing RIS links. This introduces new challenges for training and estimation of channel state information. The rapid growth of the literature on CSI acquisition in RIS-aided systems has been accompanied by variations in the underlying assumptions, models, and notation, which can obscure the similarities and differences of various techniques, and their relative merits. This paper presents a comprehensive exposition of principles and approaches in RIS channel estimation. The basic ideas underlying each class of techniques are reduced to their simplest form under a unified model and notation, and various approaches within each class are discussed. Several open problems in this area are identified and highlighted.
Two-degrees-of-freedom speed controller based on doubly coprime factorization and speed observer (2002)

This paper proposes a new two-degrees-of-freedom speed controller based on doubly coprime factorization and speed observer. The proposed system individually defines a reference response and a disturbance rejection response considering a robust stability. The free parameter Q(s) of the proposed two-degrees-of-freedom control system is defined by doubly coprime factorization and the new free parameter g(s) in this paper. In an ultra low speed range, the speed sensor based on a rotary encoder cannot detect a motor speed. In this paper, the speed information is estimated by the proposed instantaneous speed observer whose input variables are an armature voltage and an armature current. The proposed total speed control system regulates a motor speed robustly and has a desired response in the whole speed range.
73.2: Distinguished Paper : Compact Three Panel LED Projector Engine (2006)

Abstract The development of a LED projection engine based on a three t‐ LCD panel architecture is discussed. The compactness and optical efficiency have been optimized in view of portable applications. The optical design parameters influencing the projector brightness as well as the image quality (uniformity) are discussed. We show how the contrast can be significantly increased by using a wavelength selective reflection screen. The projector delivers 50 lm to screen at SVGA resolution. The optical engine has a consumption of 18 W for a volume of 190 cc.
Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages (2020)

Technology-assisted platforms provide reliable solutions in almost every field these days. One such important application in the medical field is the skin cancer classification in preliminary stages that need sensitive and precise data analysis. For the proposed study the Kaggle skin cancer dataset is utilized. The proposed study consists of two main phases. In the first phase, the images are preprocessed to remove the clutters thus producing a refined version of training images. To achieve that, a sharpening filter is applied followed by a hair removal algorithm. Different image quality measurement metrics including Peak Signal to Noise (PSNR), Mean Square Error (MSE), Maximum Absolute Squared Deviation (MXERR) and Energy Ratio/ Ratio of Squared Norms (L2RAT) are used to compare the overall image quality before and after applying preprocessing operations. The results from the aforementioned image quality metrics prove that image quality is not compromised however it is upgraded by applying the preprocessing operations. The second phase of the proposed research work incorporates deep learning methodologies that play an imperative role in accurate, precise and robust classification of the lesion mole. This has been reflected by using two state of the art deep learning models: Inception-v3 and MobileNet. The experimental results demonstrate notable improvement in train and validation accuracy by using the refined version of images of both the networks, however, the Inception-v3 network was able to achieve better validation accuracy thus it was finally selected to evaluate it on test data. The final test accuracy using state of art Inception-v3 network was 86%.
Unraveling the Complex Subsurface with a High-Resolution Earth Model in the Taranaki Basin, New Zealand (2021)

Summary The Taranaki Basin is located west of New Zealand’s North Island and contains most of the country’s proven oil and gas reserves. The basin has experienced a complex geological evolution with multiple phases of extensional and compressional tectonic activity. Legacy imaging efforts have struggled to overcome all of the imaging challenges that are present across the basin. These challenges include significantly varying overburden, complex extensional and compressional fault networks, and shallow gas clouds. As a result of these challenges, there are impacts on the interpretability of deeper producing reservoir intervals, but also prospective un-targeted intervals. This has resulted in the necessity to ensure that shallow intervals are imaged correctly through a detailed and targeted velocity model building strategy. This case study demonstrates the successful application of full-waveform inversion (FWI) using refraction and reflection energy, complemented by Q-FWI and common image point tomography, to deliver a high-resolution, geologically-plausible earth model that explains the seismic data and well data. The detailed earth model enabled the final Q-Kirchhoff prestack depth migration to compensate for the kinematic distortions and gas-related absorption effects observed in the survey. The results enabled better understanding and improved interpretation of the proven and unproven plays in Taranaki basin.
Imaging of the Inner Ear using Inner Volume 3D-RARE (2002)

A fast inner volume 3D-RARE scheme is applied to inner ear imaging to get sub-millimeter spatial resolution and high contrast for the cochlea and the semicircular canals.A short TR using TR flip-back pulses and a small number of acquired matrix lines using an inner volume excitation allows for a scan time of about Imin.The MPR images had lower flow ghosts and magnetic susceptibility artifacts than 3D-CISS images.On the MIP images, the cochlea and the semicircular canals are clearly delineated.
Comparison between whole exome sequencing (WES) and single nucleotide polymorphism (SNP)-based tumor mutation burden analysis. (2019)

2634 Background: Immune checkpoint inhibitors (ICI) block proteins which enable cancer cells to evade the immune system. Recent studies have shown that the higher the tumor mutation burden (TMB) the greater the likelihood of response to ICI therapy. Analysis of TMB has focused on WES of paired tumor and normal samples. This study tests the feasibility of measuring TMB from a SNP-based resequencing assay (myChoice HRD Plus). Methods: WES and myChoice HRD Plus were performed on matched tumor and normal DNA from 44 breast and 12 colon tumors. myChoice HRD Plus combines homologous recombination deficiency analysis with resequencing of 108 genes and microsatellite instability analysis. WES-based TMB was calculated by identifying all variants in paired samples, and subtracting germline variants. Two SNP-based TMB (SbTMB) methods were utilized to calculate TMB. The first used germline subtraction similar to the WES-based method. The second utilized an algorithm which removed background germline variants. Median sequence length to calculate TMB was 9.7 Mb for WES, 4.6 Mb for SbTMB (germline subtraction), and 1.9 Mb for SbTMB (algorithm). Results: Correlation coefficients for WES vs. SbTMB (germline subtraction) and SbTMB (algorithm) were 0.895 and 0.908, respectively. The two SbTMB methods had a correlation coefficient of 0.834. SbTMB measures of TMB were generally higher than WES-based TMB with a mean increase in score of 1.6 variants/Mb for SbTMB (germline subtraction; p = 4.6x10 -6 ) and 1.5 variants/MB for SbTMB (algorithm; p = 1.2x10 -5 ). No significant difference in magnitude of TMB score between the SbTMB measures was observed (0.04 variants/Mb; p = 0.88). Conclusions: SNP-based methods for calculating TMB produced highly concordant scores compared to WES-based methods. SbTMB assays produced elevated TMB scores, consistent with selective pressure against mutations in coding regions of genes, necessitating a higher score threshold for when using a SbTMB assay. This SbTMB analysis expands the utility of myChoice HRD Plus, and provides a method for calculation of TMB without sequencing a germline comparator.
Extraction of system functions from 1-D simulation component libraries (2014)

This paper presents a bottom-up approach for the extraction of system functions from simulation component libraries; this step is desirable and necessary for the integration of system-level 1D simulation tools with product lifecycle management systems (PLM). The presented approach performs a port, structural (e.g., equational/algorithmic), parameter, and internal variable analysis to extract functionality from simulation components. The implementation of our algorithm in a research prototype has been validated on more than 4,000 components of the Amesim library with the successful extraction of more than 60,000 system functions. Our results show that the extraction of functions is a practical and viable foundation for associating requirements to system-level simulation models, and for harmonizing concept designs to detailed designs.
Building Trust in Deep Learning System towards Automated Disease Detection (2019)

Though deep learning systems have achieved high accuracy in detecting diseases from medical images, few such systems have been deployed in highly automated disease screening settings due to lack of trust in how well these systems can generalize to out-of-datasets. We propose to use uncertainty estimates of the deep learning system’s prediction to know when to accept or to disregard its prediction. We evaluate the effectiveness of using such estimates in a real-life application for the screening of diabetic retinopathy. We also generate visual explanation of the deep learning system to convey the pixels in the image that influences its decision. Together, these reveal the deep learning system’s competency and limits to the human, and in turn the human can know when to trust the deep learning system.
Retraction: A Metal–Organic Framework with Exceptional Activity for C−H Bond Amination (2022)

the C H amination reactions described were not reproducibly dependent on catalytic activity from the reported metal-organic framework based on experiments by their own laboratories.As a result, the authors and the journal have agreed that the conclusions are inaccurate.