Miracle-dz/UniFAR-FTUs huggingface dataset:
Adverse Outcomes Associated With Stimulator-Based Peripheral Nerve Blocks With Versus Without Ultrasound Visualization

Background and Objectives: In this retrospective study, we queried our Quality Improvement database of anesthetic-related complications to evaluate the frequency of noncatheter peripheral nerve block-related adverse occurrences. We hypothesized that adverse complications of nerve blockade are less common when ultrasonography is used in conjunction with peripheral nerve stimulation to guide needle placement, when compared with the sole use of physical landmarks and nerve stimulation. Methods: We queried our departmental Quality Improvement electronic database for adverse outcomes associated with peripheral nerve blocks. Billing records were used to provide the denominator of the total number of blocks using both techniques of neurolocation. The types of blocks considered in this analysis were interscalene, axillary, femoral, sciatic, and popliteal sciatic blocks. The total numbers of complications of nerve blockade with each type of guidance were then compared, as were specific subsets of adverse effects. Results: There were 5436 consecutive peripheral noncatheter block cases (interscalene, axillary, femoral, sciatic, popliteal) during the 28-month period surveyed, with 3290 guided by landmark-nerve stimulation, and 2146 by ultrasound-nerve stimulation. Eight adverse outcomes occurred among patients having blocks guided by landmark-nerve stimulation technique, including 5 seizures and 3 nerve injuries. There were no such occurrences in the ultrasound-nerve stimulation group. When comparing the 4 brachial plexus block-related seizures that occurred with landmark guidance versus none with ultrasound guidance, the associated risk of seizures reached statistical significance (P = 0.044 by Fisher exact test). There was no difference between the 2 groups in the number of seizures occurring with lower extremity blocks, or in the frequency of neurologic injury. Conclusions: High-definition ultrasonography offers potential advantages in the administration of peripheral nerve blockade. The significant difference in major central nervous system local anesthetic toxicity observed in this study supports the use of ultrasound guidance in conjunction with peripheral nerve stimulation to provide brachial plexus peripheral nerve blockade in an academic, ambulatory anesthesia practice.
Influence of batch or fed‐batch growth on Staphylococcus epidermidis biofilm formation

Aims: To make a quantitative evaluation of the differences in biofilm formation by Staphylococcus epidermidis using batch and fed‐batch growth systems and to correlate this with production of the major biofilm polysaccharide, poly‐N‐acetyl glucosamine (PNAG).
Robust Convex Approximation Methods for TDOA-Based Localization Under NLOS Conditions

In this paper, we develop a novel robust optimization approach to source localization using time-difference-of-arrival (TDOA) measurements that are collected under non-line-of-sight (NLOS) conditions. A key feature of our approach is that it does not require knowledge of the distribution or statistics of the NLOS errors, which are often difficult to obtain in practice. Instead, it only assumes that the NLOS errors have bounded supports. Based on this assumption, we formulate the TDOA-based source localization problem as a robust least squares (RLS) problem, in which a location estimate that is robust against the NLOS errors is sought. Since the RLS problem is non-convex, we propose two efficiently implementable convex relaxation-based approximation methods to tackle it. We then conduct a thorough theoretical analysis of the approximation quality and computational complexity of these two methods. In particular, we establish conditions under which they will yield a unique localization of the source. Simulation results on both synthetic and real data show that the performance of our approach under various NLOS settings is very stable and is significantly better than that of several existing non-robust approaches.
On leader-following consensus under communication failure

It is well-known that the communication among agents plays an important role in leader-following consensus. When the communication fails, it will greatly degrade the performance of the leader-following consensus. As technology develops, memory components are quite cheap. Thus it is very natural to use the information before the communication failure to enhance the robustness of leader-following consensus. This paper proposes an effective communication protocol re-design method to handle the communication failure. The re-design method uses a structure similar to “zero-order hold” to remember the input before the communication failure. Thus the leader-following consensus with communication failure can be treated as a time-varying delay system. Less conservative sufficient conditions to ensure the closed loop stability are provided in terms of the restriction of frequency and length rate of communication failures. Simulation results including the diving consensus of the unmanned underwater vehicles (UUVs) demonstrate the effectiveness of the obtained results.
Sparse Log Gaussian Processes via MCMC for Spatial Epidemiology

Log Gaussian processes are an attractive manner to construct intensity surfaces for the purposes of spatial epidemiology. The intensity surfaces are naturally smoothed by placing a Gaussian process (GP) prior over the relative log Poisson rate, and the spatial correlations between areas can be included in an explicit and natural way into the model via a correlation function. The drawback with using a Gaussian process is the computational burden of the covariance matrix calculations. To overcome the computational limitations a number of approximations for Gaussian process have been suggested in the literature. In this work a fully independent training conditional sparse approximation is used to speed up the computations. The posterior inference is conducted using Markov chain Monte Carlo simulations and the sampling of the latent values is sped up by a transformation taking into account their posterior covariance. The sparse approximation is compared to a full GP with two sets of mortality data.
MTHFR C677T variant reduces risk of sporadic Parkinson's disease in ethnic Chinese

Genetic variability of methylenetetrahydrofolate reductase (MTHFR) may be associated with Parkinson's disease (PD). Its role in ethnic Chinese population is still unclear. Our study aimed to investigate whether MTHFR C677T variation was linked to PD risk in a Han Chinese population from mainland China.
A partitioning programming environment for a novel parallel architecture

The paper presents a partitioning and parallelizing programming environment for a novel parallel architecture. This universal embedded accelerator is based on a reconfigurable datapath hardware. The partitioning and parallelizing programming environment accepts C programs and carries out both a profiling-driven host/accelerator partitioning for performance optimization in a first step, and in a second step a resource-driven sequential/structural partitioning of the accelerator source code to optimize the utilization of its reconfigurable resources.
Investment, Capacity Utilization and the Real Business Cycle

This paper adopts Keynes' view that shocks to the marginal efficiency of i nvestment are important for business fluctuations, but incorporates i t in a neoclassical framework with endogenous capacity utilization. I ncreases in the efficiency of newly produced investment goods stimula te the formation of "new" capital and more intensive utilization and accelerated depreciation of "old" capital. Theoretical and quantitat ive analysis suggests that the shocks and transmission mechanism stud ied here may be important elements of business cycles. Copyright 1988 by American Economic Association.
Synthesis and Catalytic Activity of Crown Jewel‐Structured (IrPd)/Au Trimetallic Nanoclusters

Crown-jewel-structured (IrPd)/Au trimetallic nanoclusters are prepared by a galvanic replacement reaction using Ir/Pd nanoclusters with a structure of Ir rich in the core and Pd rich in the shell as mother clusters. The catalytic activity of the top Au atoms for aerobic glucose oxidation of the trimetallic nanoclusters is the highest ever reported among all supported and colloidal catalysts.
A Biomechanical Comparison of Lateral and Posterior Approaches to Sacroplasty

Study Design. Biomechanical cadaveric bench study. Objective. To measure the augmentation effect and extravasation risk of posterior and lateral approaches to sacroplasty. Summary of Background Data. The biomechanical stabilizing effect of sacroplasty is unknown. Methods. Using a sacral insufficiency fracture model, we performed sacroplasty in 15 osteoporotic cadaveric pelves. Five served as controls, and 10 were each injected with 4 mL of a polymethylmethacrylate cement (5 via a posterior approach, 5 via a lateral approach). Cement extravasation was assessed using computed tomography. Restored strength and stiffness were defined as the ratios of treatment to initial strength and to stiffness, respectively. Between-group differences in restoration parameters were checked for significance (P < 0.05) using an analysis of variance followed by Tukey’s test. Results. We found no significant differences between groups in terms of restored strength (∼61%) and stiffness (∼77%). Both injection methods produced extravasation into the anterior sacrum, the posterior sacrum, the sacroiliac joint, and the neural foramens. Conclusion. Sacroplasty with 4 mL of cement does not restore the strength or stiffness of the sacrum in a cadaveric model, regardless of the approach used.
Phase-Field Modeling of Electro-Chemo-Mechanical Behavior of Li-ion Battery Electrodes

Lithium-ion batteries, with their high energy densities and light-weight designs, have found broad applications in portable electronics and electric vehicles. However, their mechanisms and operation are not yet fully understood, which has motivated a wide span of multi-physical models from different disciplines. In this thesis, a thermodynamically consistent phase-field framework is presented, to investigate the electro-chemo-mechanical behavior of lithium-ion battery electrode materials. Within this framework, a series of coupled models is developed sequentially towards the more realistic modeling. Firstly, a mechanically coupled two-phase model of a single particle is proposed, based on a thorough study of the chemical phase separation of this particle. Thereby, the effect of large strains and the concentration-dependent elastic properties are considered, which has been proved in this thesis to have a great impact on the phase separation. A more comprehensive model is formulated, which deals additionally with the electrochemical reaction on the particle surface and the orthotropic phase separation. The reaction rate is governed by a modified Butler--Volmer equation, which takes both chemical and mechanical states into account. Based on this model, we further investigate the fracture in the particle by the phase-field approach, where the reaction on the newly cracked surfaces is also taken into consideration. Finally, the model of the particle embedded in a polymer matrix is presented to study the interaction between the particle and the surrounding materials. For the implementation two novel finite element methods are used: isogeometric analysis and the B-Spline based finite cell method. Isogeometric analysis is employed in order to treat the fourth-order Cahn--Hilliard equation and the third-order drifting term in a straightforward fashion. To deal with the additional boundary constraint, which states that the normal gradient of the concentration equals to zero, and which arises from the Cahn--Hilliard equation, we propose two variational formulations based on the Lagrange multiplier method and the Nitsche method, respectively, as the weak imposition. Moreover, we also employ finite cell method with Cartesian B-Spline meshes to simulate the composite electrode with complex geometries. In this thesis, the chemical and mechanical fields are fully resolved in a variety of three-dimensional simulations. These simulations demonstrate the influence of the phase separation on the stress field, the fracture and the reaction rate. We find that the phase separation results in, among others, an intensified stress field and enhanced reaction rate near the phase interface, and in severe cases it also leads to crack propagation and branching. Moreover, intensive discussions are carried out to explore the factors that contribute to phase separation and suppression, such as the particle size, charge rate and material stiffness.
Microfibrillation of pulp fibres : the effects of compression-shearing, oxidation and thermal drying

Cellulose microand nanofibrils are elongated, flexible nano-scale particles produced from natural fibres with intensive mechanical treatments, usually in the form of dilute aqueous suspensions. Due to the recalcitrant structure of the fibres, mechanical, chemical and enzymatic pre-treatments are often used to loosen the fibre wall structure so as to facilitate the mechanical liberation of microand nanofibrils and reduce the high amount of mechanical energy needed. However, it is still unclear how different chemistries affect the disintegration phenomena and how mechanical action starts to unravel the fibre structure, and thus how microand nanofibrillation could best benefit from the pre-treatments. In addition, the high water content used in the process increases the production and transportation costs of the material, so that the solids content should be increased. Reducing the water content before or after production would be challenging, however, due to changes in fibre properties during drying (hornification) and the tendency for the resulting nanofibrils to agglomerate. Also, the effect of high solids content and temperature on the reduction of fibres to nanoand microfibrils is still not well understood. The aims of this work were to follow the changes in fibre morphology after mechanical, chemical and thermal modification and address their effects on the disintegration phenomena of the fibres to microfibrils. Mechanical compression-shearing, two selective oxidations and thermal drying in combination with TEMPO oxidation were used to modify the fibre structure before mechanical disintegration in a high-shear homogenizer or ball mill. The results showed that sufficient swelling of the fibre cell walls was a prerequisite for successful microfibrillation. Swelling can be promoted by loosening the hydrogen bonding network with compression and shearing forces or by increasing the charge density. Different charge thresholds were observed for microfibrillation depending on the chemistry used. Extremely hornified fibres were also successfully microfibrillated with the aid of TEMPO oxidation. Different fibre disintegration mechanisms were seen depending on the modification type and disintegration conditions. In addition, microand nanofibrils and nanocrystals were successfully produced under high solids (≥ 50%) conditions.
Accurate Prediction of Transposon-Derived piRNAs by Integrating Various Sequential and Physicochemical Features

Background Piwi-interacting RNA (piRNA) is the largest class of small non-coding RNA molecules. The transposon-derived piRNA prediction can enrich the research contents of small ncRNAs as well as help to further understand generation mechanism of gamete. Methods In this paper, we attempt to differentiate transposon-derived piRNAs from non-piRNAs based on their sequential and physicochemical features by using machine learning methods. We explore six sequence-derived features, i.e. spectrum profile, mismatch profile, subsequence profile, position-specific scoring matrix, pseudo dinucleotide composition and local structure-sequence triplet elements, and systematically evaluate their performances for transposon-derived piRNA prediction. Finally, we consider two approaches: direct combination and ensemble learning to integrate useful features and achieve high-accuracy prediction models. Results We construct three datasets, covering three species: Human, Mouse and Drosophila, and evaluate the performances of prediction models by 10-fold cross validation. In the computational experiments, direct combination models achieve AUC of 0.917, 0.922 and 0.992 on Human, Mouse and Drosophila, respectively; ensemble learning models achieve AUC of 0.922, 0.926 and 0.994 on the three datasets. Conclusions Compared with other state-of-the-art methods, our methods can lead to better performances. In conclusion, the proposed methods are promising for the transposon-derived piRNA prediction. The source codes and datasets are available in S1 File.
Simulation study on one leg jumping for biped running

The fast movement of biped robot can be achieved by the fast walking, but the further fast motion can be achieved only by the biped running. To pursue this target, one leg running robot is modeled, analyzed and developed. First, it is theoretically analyzed in the one and two dimensional sagital plane models, secondly, the derived mathematical model is simulated by digital computers, and finally a 3-axis experimental robot is developed.
Using Formal Modeling With an Automated Analysis Tool to Design and Parametrically Analyze a Multirobot Coordination Protocol: A Case Study

Many robot systems employ logic-based or reactive controllers, making them hybrid systems (i.e., mixed discrete continuous). However, designing such control laws in a systematic manner remains a challenging task. In this paper, we apply the formal modeling paradigm to a team of mobile robots. The linear hybrid automata modeling framework is used to describe the high-level design, and the verification software HyTech is used for symbolic analysis of the description. The goal is to symbolically quantify system-level performance as a function of the design parameters, for the purpose of optimizing and synthesizing design parameters, verifying safe operation, and quantitatively exploring tradeoff issues. In order to make the analysis tractable, a series of restrictive assumptions and simplifications must be made-some dictated by the linear hybrid automata model and others necessitated by computational cost. We comment on the restrictiveness of these assumptions and the overall utility of this automated analysis approach in designing complex robotic systems
Influence functions and goal‐oriented error estimation for finite element analysis of shell structures

In this paper, we first present a consistent procedure to establish influence functions for the finite element analysis of shell structures, where the influence function can be for any linear quantity of engineering interest. We then design some goal‐oriented error measures that take into account the cancellation effect of errors over the domain to overcome the issue of over‐estimation. These error measures include the error due to the approximation in the geometry of the shell structure. In the calculation of the influence functions we also consider the asymptotic behaviour of shells as the thickness approaches zero. Although our procedures are general and can be applied to any shell formulation, we focus on MITC finite element shell discretizations. In our numerical results, influence functions are shown for some shell test problems, and the proposed goal‐oriented error estimation procedure shows good effectivity indices. Copyright © 2005 John Wiley & Sons, Ltd.
DTNLite : A Reliable Data Transfer Architecture for Sensor Networks

We present a network architecture, DTNLite, for reliable message delivery in sensor networks facing problems of high mobility, frequent disconnections and unreliable nodes . It is based on the DTN( Delay Tolerant Networking) architecture and its main features are asynchronous message delivery combined with custody transfer on an overlay network of sensor motes. We present an implementation of this architecture for the TinyOS platform targeting data collection applications. We also explore the various issues in reliable custody transfer and investigate the particular issue of querying and selection of custody hops in detail. Our simulation results show that selection criteria that use energy or delay as metrics are able to profitably exploit asymmetries in the network.
Investigation of radiation damage in the SLD CCD vertex detector

Early in the operation of the SLD CCD vertex detector (VXD3) at the SLC, radiation damage to the CCDs was observed. It is well known that low-energy light particles (electrons and photons) are a few orders of magnitude less effective than heavy particles (neutrons or heavy charged particles) in the generation of radiation damage effects in silicon. The SLD environment was known to be dominated by electrons and photons with a small fraction of neutrons. The estimated radiation damage by these particles cannot account for the observed damage. Therefore, this damage is puzzling. A CCD-based detector is a leading option for vertex detection at the future linear collider (LC). A full understanding of background models in LCs and the associated damage is needed. Earlier results on neutron damage to an SLD CCD were reported at the 1999 IEEE NSS, and these new results complement our old results. In addition to tests on controlled exposures of individual CCDs, we have studied the nature of the traps produced in the SLD vertex detector to assess their origin-whether heavy or light particles.
The T cell response of HLA-DR transgenic mice to human myelin basic protein and other antigens in the presence and absence of human CD4

Analysis of HLA class II transgenic mice has progressed in recent years from analysis of single chain HLA class II transgenes with expression of mixed mouse/human heterodimers to double transgenic mice expressing normal human heterodimers. Previous studies have used either HLA transgenic mice in which there is a species-matched interaction with CD4 or mice which lack this interaction. Since both systems are reported to generate HLA-restricted responses, the matter of the requirement for species-matched CD4 remains unclear. We have generated triple transgenic mice expressing three human transgenes, DRA, DRB, and CD4, and compared HLA-restricted responses to peptide between human- CD4+ (Hu-CD4+) and Hu-CD4- littermates. We saw no difference between Hu- CD4+ and Hu-CD4- groups, supporting the notion that for some responses at least the requirement for species-matched CD4 may not be absolute. Evidence for positive selection of mouse T cell receptors in HLA-DR transgenic mice came both from the acquisition of new, HLA-restricted responses to various peptides and from an increased frequency of T cells using the TCR V beta 4 gene segment. An important goal with respect to the analysis of function in HLA transgenic mice is the clarification of mechanisms which underpin the recognition of self- antigens in human autoimmune disease. As a first step towards 'humanized' disease models in HLA transgenic mice, we analyzed the responses of HLA-DR transgenic mice to the human MPB 139-154 peptide which has been implicated as an epitope recognized by T cells of multiple sclerosis patients. We obtained T cell responses to this epitope in transgenic mice but not in nontransgenic controls. This study suggests that HLA transgenic mice will be valuable in the analysis of HLA-restricted T cell epitopes implicated in human disease and possibly in the design of new disease models.