Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability of a Thin Solid Film with Interactions

We investigate the question of stability of a solid thin film which experiences external interactions such as van der Waals forces from a contacting surface or forces from an external electric field. Both perfectly elastic and viscoelastic material behaviours are considered in linear stability analysis performed here. These analyses indicate that for sufficiently soft (shear modulus between 1 and 10 MPa) and nearly incompressible films (Poisson's ratio close to 0.5), bifurcations are possible, i.e., the surface of the film becomes non-planar. The modes of bifurcation and rates of growth of perturbations are determined as a function of material parameters. The results of this study are of significance in understanding the adhesive properties between a soft material (such as rubber) and a comparatively rigid solid (such as steel), and the behaviour of soft solid films in an electric field.
A Novel Fault Feature Extraction Method of Analog Circuit Based on Improved KPCA

The Kernel Principal Component Analysis (KPCA) extracts the principal components by computing the population variance, which doesn't consider the difference between one class and the others. So, it makes against the fault diagnosis. For solving this problem, the study introduced Fisher classification function into The KPCA and proposed an improved FKPCA with the class information. Then, the algorithm was applied in analog-circuit fault feature extraction and the neural network was applied to diagnose the faults. The results indicate the classification effect of the principal components extracted by the algorithm is more better. It improves the rate of fault diagnosis and reduces the test time.
The Impact of Deviations from Random Walk in Security Prices on Option Prices

This paper examines the effects of deviations from random walk in asset prices on option prices. Several approaches can be taken to model asset price processes as non-random walk processes. We choose to model the equity prices as fractional Brownian motions (FBM). Though FMB is not the most ideal model for the behavior of security prices, it offers many advantages namely it allows for short-term and long-term memory in asset prices. This paper uses Monte Carlo simulations to determine option prices under the assumption that equity prices follow FBM. The simulated prices and their implied volatilities are then compared to prices that one would obtain using the Black-Scholes-Merton option price model. The results show that even a small deviation from random walk can have a significant impact on option prices. The volatilities implied by the simulated prices generally increase as the call options go deeper into the money when security prices have short-term memory. In other words, short-term memory in security prices contributes to the presence of the so-called "smile" effect in implied volatilities.
Echo‐planar BOLD fMRI of mice on a narrow‐bore 9.4 T magnet

The feasibility of BOLD fMRI in association with electrical somatosensory stimulation on spontaneously breathing, isoflurane‐anesthetized mice was investigated using spin‐echo, echo‐planar imaging (EPI) on a vertical narrow‐bore 9.4 T magnet. Three experiments were performed to derive an optimal fMRI protocol. In Experiment 1 (n = 9), spin‐echo BOLD responses to 10% CO2 challenge under graded isoflurane (0.25–1.25%) ranged from 10 ± 2% to 3.5 ± 0.9%; the optimal BOLD contrast‐to‐noise ratio peaked at 0.75% isoflurane. In Experiment 2 (n = 6), hindpaw somatosensory stimulations using 1–7 mA under 0.75% isoflurane revealed the optimal BOLD response was at 6 mA. In Experiment 3 (n = 5), BOLD responses to 4 and 6 mA stimulation under 0.75% and 1% isoflurane were evaluated in detail, confirming the optimal conditions in Experiment 2. These results demonstrated that BOLD fMRI using single‐shot, spin‐echo EPI in a mouse somatosensory stimulation model could be routinely performed on high‐field, vertical, narrow‐bore magnets. This protocol might prove useful for fMRI studies of transgenic mice. Magn Reson Med 52:430–434, 2004. © 2004 Wiley‐Liss, Inc.
THE INDUSTRIALIZATION OF AGRICULTURE: IMPLICATIONS FOR FUTURE POLICY

Farming is in the midst of a major transformation—not only in technology and production practices, but also in size of business, resource (land) control and operation, business model and linkages with buyers and suppliers. This paper describes the fundamental drivers of today’s structural change in U.S. agriculture. The impact of the drivers are illustrated by describing some illustrations of the kinds of innovative farming operations that are developing in agriculture, not the typical farms but those who appear to be leading and shaping the new agriculture. Finally, farm policy implications of the transformation of farming to an industrial manufacturing model are discussed.
Pattern Classification With Class Probability Output Network

The output of a classifier is usually determined by the value of a discriminant function and a decision is made based on this output which does not necessarily represent the posterior probability for the soft decision of classification. In this context, it is desirable that the output of a classifier be calibrated in such a way to give the meaning of the posterior probability of class membership. This paper presents a new method of postprocessing for the probabilistic scaling of classifier's output. For this purpose, the output of a classifier is analyzed and the distribution of the output is described by the beta distribution parameters. For more accurate approximation of class output distribution, the beta distribution parameters as well as the kernel parameters describing the discriminant function are adjusted in such a way to improve the uniformity of beta cumulative distribution function (CDF) values for the given class output samples. As a result, the classifier with the proposed scaling method referred to as the class probability output network (CPON) can provide accurate posterior probabilities for the soft decision of classification. To show the effectiveness of the proposed method, the simulation for pattern classification using the support vector machine (SVM) classifiers is performed for the University of California at Irvine (UCI) data sets. The simulation results using the SVM classifiers with the proposed CPON demonstrated a statistically meaningful performance improvement over the SVM and SVM-related classifiers, and also other probabilistic scaling methods.
Collagen Cross-Linking: Current Status and Future Directions

Collagen cross-linking (CXL) using UVA light and riboflavin (vitamin B2) was introduced as a clinical application to stabilize the cornea by inducing cross-links within and between collagen fibers. CXL has been investigated extensively and has been shown clinically to arrest the progression of keratoconic or post-LASIK ectasia. With its minimal cost, simplicity, and proven positive clinical outcome, CXL can be regarded as a useful approach to reduce the number of penetrating keratoplasties performed. Small case series have also indicated that CXL is beneficial in corneal edema by reducing stromal swelling behavior and in keratitis by inhibiting pathogen growth. Despite these encouraging results, CXL remains a relatively new method that is potentially associated with complications. Aspects such as side effects and recurrence rates have still to be elucidated. In light of the growing interest in CXL, our paper summarizes present knowledge about this promising approach. We have intentionally endeavored to include the more relevant studies from the recent literature to provide an overview of the current status of CXL.
TBBench: A Micro-Benchmark Suite for Intel Threading Building Blocks

Task-based programming is becoming the state-of-the-art method of choice for extracting the desired performance from multi-core chips. It expresses a program in terms of lightweight logical tasks rather than heavyweight threads. Intel Threading Building Blocks (TBB) is a task-based parallel programming paradigm for multi-core processors. The performance gain of this paradigm depends to a great extent on the efficiency of its parallel constructs. The parallel overheads incurred by parallel constructs determine the ability for creating large-scale parallel programs, especially in the case of fine-grain parallelism. This paper presents a study of TBB parallelization overheads. For this purpose, a TBB micro-benchmarks suite called TBBench has been developed. We use TBBench to evaluate the parallelization overheads of TBB on different multi-core machines and different compilers. We report in detail in this paper on the relative overheads and analyze the running results.
Cost-effectiveness of isoniazid chemoprevention in close contacts

The aim of the present study was to perform a cost-effectiveness analysis in young and middle-aged adults with latent tuberculosis (TB) infection in Germany. A Markov model simulated the progression of 20- and 40-yr-old close contacts of active TB cases over 20 yrs. Health and economic outcomes of isoniazid (INH) chemoprevention versus no intervention were compared. The analysis determined the incremental cost-effectiveness ratio in terms of cost per quality-adjusted life year and the difference between numbers of TB cases and of TB-related deaths. INH chemoprevention prevented 79% of expected TB cases in both age groups, and saved €9,482 and €9,142 in the lower and higher age groups, respectively, per case prevented. Quality-adjusted life expectancy was slightly extended by 8 days in the lower age group and 7 days in the higher age group, at a cost saving of €417 and €375, respectively, per person. Annual savings were €20,862 and €18,742 per 1,000 contacts, respectively. The number needed to be treated to prevent one TB case in the lower age group was 23 and 25 in the higher age group. The programme also prevented three TB-related deaths in the younger and two in the older cohort. The results are highly sensitive to treatment-cost assumptions. In conclusion, isoniazid chemoprevention in Germany is a highly cost-effective approach for reducing the burden of tuberculosis in recently converted young and middle-aged adults.
Communications based train control with Ad-hoc networks

Metro intelligent transport city systems should ensure a high train cadence and have increased safety in high traffic conditions. Current signaling systems CBTC can provide a safe minimum distance between two successive trains −50 m theoretically but practically 200 m due to delays in the transmission chain of processing and transmission of data, which includes the central server, interlocking equipments by local stations and adjacent systems. The new system aims to reduce the gap by using direct communication between successive trains so as to eliminate delays due to communication equipment exclusively at reserve and subsequently lock the route.
Adaptive impulsive noise mitigation using Multi Mode Compressive Sensing for powerline communications

We propose an adaptive algorithm based on Compressive Sensing (CS) to mitigate impulsive noise (IN) from Orthogonal Frequency Division Multiplexing (OFDM) based systems. In recent CS literature on IN mitigation, the sparsity of IN is assumed to be constant and thereby the number of pilots to reconstruct IN is also fixed. However, in practical systems especially in Power Line Communications (PLC) the sparsity of IN changes significantly over time. This limits the application of traditional CS algorithms. Therefore, we develop a Multi Mode Compressive Sensing (MMCS) scheme that adaptively changes the number of pilots used to reconstruct the IN depending on the IN's current severity. The scheme not only stabilizes the Bit Error Rate (BER) in stern IN conditions but also improves overall system throughput.
Evaluation of plasma concentration changes of nitric oxide metabolites during glucose tolerance test in type II diabetic rats

Introduction: Repeated hyperglycemia play an important role in development of atherosclerosis in diabetic patients. Endothelium is the first-line defense against atherosclerosis and nitric oxide has a major role in this task. In this study, changes in plasma concentration of nitric oxide metabolites (NOx) during glucose tolerance test were evaluated in type II diabetic rats. Methods: Male neonatal Wistar rats were divided into control and diabetic groups. Type II diabetes was induced by administration of Streptozotocin (100 mg/kg, i.p.) to neonatal rats on day 2. Plasma glucose and NOx concentration were measured on days 7, 30, 45, 60, and 75. Intravenous glucose tolerance test was done in adult rats and blood samples were collected 0, 5, 10, 30, and 60 min after glucose infusion for determining plasma glucose, insulin, and NOx. Two-way mixed (between-within) ANOVA was used for comparing data. Results: Plasma glucose was returned to basal values 60 min after glucose injection in the control group, while in diabetic rats it was higher than basal levels (P < 0.001). After glucose injection, plasma insulin concentration was increased to 4.5 and 1.9 folds in control and diabetic groups, respectively. Basal NOx concentration was higher in diabetic rats (50.4 ± 6.4 vs. 28.8 ± 3.8 ∝mol/l, P < 0.05). During glucose tolerance test there was 35 and 62 % fall in plasma NOx concentration in control and diabetic groups, respectively. This reduction returned to basal values after 30 min in the control group, while in diabetic rats it was 17% less than basal levels 60 min after glucose injection. Conclusion: Decreased nitric oxide production or increased degradation may be the cause of endothelial dysfunction and atherosclerosis in type II diabetes.
DTB-MAC: Dynamic Token-Based MAC Protocol for reliable and efficient beacon broadcasting in VANETs

Most applications developed for vehicular environments rely on broadcasting as the main mechanism to disseminate their messages. However, in IEEE 802.11p, which is the most widely accepted Medium Access Control (MAC) protocol for vehicular communications, all transmissions remain unacknowledged if broadcasting is used. Furthermore, safety message transmission requires a strict delay limit and a high reliability, which is an issue for random access MAC protocols like IEEE 802.11p. Therefore, transmission reliability becomes the most important issue for broadcast-based services in vehicular environments. In this paper, we propose a hybrid MAC protocol, referred as Dynamic Token-Based MAC Protocol (DTB-MAC). DTB-MAC uses both a token passing mechanism and a random access MAC protocol to prevent channel contention as much as possible, and to improve the reliability of safety message transmissions. Our proposed protocol tries to select the best neighbouring node as the next transmitter, and when it is not possible, or when it causes a high overhead, the random access MAC protocol is used instead. Based on simulation experiments, we show that the DTB-MAC protocol can achieve better performance compared with IEEE 802.11p in terms of channel utilization and beacon delivery ratio.
Involvement of Type 1 Angiontensin II Receptor (AT1) in Cardiovascular Changes Induced by Chronic Emotional Stress: Comparison between Homotypic and Heterotypic Stressors

Consistent evidence has shown an important role of emotional stress in pathogenesis of cardiovascular diseases. Additionally, studies in animal models have demonstrated that daily exposure to different stressor (heterotypic stressor) evokes more severe changes than those resulting from repeated exposure to the same aversive stimulus (homotypic stressor), possibly due to the habituation process upon repeated exposure to the same stressor. Despite these pieces of evidence, the mechanisms involved in the stress-evoked cardiovascular dysfunction are poorly understood. Therefore, the present study investigated the involvement of angiotensin II (Ang II) acting on the type 1 Ang II receptor (AT1) in the cardiovascular dysfunctions evoked by both homotypic and heterotypic chronic emotional stresses in rats. For this purpose, we compared the effect of the chronic treatment with the AT1 receptor antagonist losartan (30 mg/kg/day, p.o.) on the cardiovascular and autonomic changes evoked by the heterotypic stressor chronic variable stress (CVS) and the homotypic stressor repeated restraint stress (RRS). RRS increased the sympathetic tone to the heart and decreased the cardiac parasympathetic activity, whereas CVS decreased the cardiac parasympathetic activity. Additionally, both stressors impaired the baroreflex function. Alterations in the autonomic activity and the baroreflex impairment were inhibited by losartan treatment. Additionally, CVS reduced the body weight and increased the circulating corticosterone; however, these effects were not affected by losartan. In conclusion, these findings indicate the involvement of angiotensin II/AT1 receptors in the autonomic changes evoked by both homotypic and heterotypic chronic stressors. Moreover, the present results provide evidence that the increase in the circulating corticosterone and body weight reduction evoked by heterotypic stressors are independent of AT1 receptors.
2009 2nd International Conference on Power Electronics and Intelligent Transportation System Simulation Based Multi-objective Evolutionary Algorithm for Electronic Reconnaissance Satellites Scheduling Problem

A multi-objective chance constrained programming model(MOCCPM) for electronic reconnaissance satellites scheduling problem(ERSSP) is presented. MOCCPM takes the uncertainties in the course of satellite electronic reconnaissance into account, as well as the capabilities and usage restrictions of the electronic reconnaissance satellites. Then a Monte Carlo simulation based multi-objective evolutionary algorithm (MCBMOEA) is proposed. Taking full advantage of the heuristic information related to the target, the MCBMOEA can construct the initial solutions and avoid converging slowly in the process of evolution. Penalty function based fitness assignment and Pareto optimality based selection ensures the efficient optimization effort of the algorithm. Elitism mechanism is adopted to prevent losing non-dominated individuals generated during the evolutionary process and speed up the convergence of the algorithm. Problem specific sequence swap crossover and mutation operator ensures the feasibility and diversity of the offspring so as to prevent the algorithm from falling into local optimum. Monte Carlo sampling is to address the stochastic nature of ERSSP. The experiment results show that MCBMOEA can solve the problem effectively. Electronic Reconnaissance Satellite (ERS) is a type of Earth Observation Satellite which collects electronic signals from the area in the vicinity of its ground track and transmits the data in its solid state recorder (SSR) to ground when passing through the ground station. When the ERS shoots a target , the working pattern of the electronic signal receiver(sensor) must be specified. Because of complicated electromagnetic environment, even though the working pattern is identical , the data quantity collected is uncertain when the receiver shoots the same area . This is a major characteristic of ERSSP.
The Application Implementation of Digital Packaging Design

With the development, diffusion and application of digital technology, it not only affects all fields of art designs, but also promotes the development of packaging design. This article, probing into cultural and creative products and their packaging design of Nanjing Museum which are devised by a team led by me, analyzes the implementation process of digital packing design and consider the digital design of packaging design deeply.
Speckle contrast diffuse correlation tomography of complex turbid medium flow.

PURPOSE Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans. METHODS A highly sensitive CCD camera was integrated into a reflectance-based optical system. Four long-coherence laser source positions were coupled to an optical switch for sequencing of tomographic data acquisition providing multiple projections through the sample. This system was investigated through incorporation of liquid and solid tissue-like phantoms exhibiting optical properties and flow characteristics typical of human tissues. Computer simulations were also performed for comparisons. A uniquely encountered smear correction algorithm was employed to correct point-source illumination contributions during image capture with the frame-transfer CCD and reflectance setup. RESULTS Measurements with scDCT on a homogeneous liquid phantom showed that speckle contrast-based deep flow indices were within 12% of those from standard DCT. Inclusion of a solid phantom submerged below the liquid phantom surface allowed for heterogeneity detection and validation. The heterogeneity was identified successfully by reconstructed 3D flow contrast tomography with scDCT. The heterogeneity center and dimensions and averaged relative flow (within 3%) and localization were in agreement with actuality and computer simulations, respectively. CONCLUSIONS A custom cost-effective CCD-based reflectance 3D flow imaging system demonstrated rapid acquisition of dense boundary data and, with further studies, a high potential for translatability to real tissues with arbitrary boundaries. A requisite correction was also found for measurements in the fashion of scDCT to recover accurate speckle contrast of deep tissues.
Gravitational Lens Time Delays in Cold Dark Matter

In standard cold dark matter (CDM) halo models, the time delay of a gravitational lens is determined by the cold baryon mass fraction, fb = Ωb, cold/Ω0, of the visible galaxy relative to the overall halo. The observed time delays in PG 1115+080, SBS 1520+530, B1600+434, and HE 2149-2745 give Hubble constants consistent with the Hubble Space Telescope Key Project value of H0 = 72 ± 8 km s-1 Mpc-1 only if fb ≳ 0.2 (one-sided 68% confidence), which is larger than the upper bound of fb, max = Ωb/Ω0 = 0.15 ± 0.05 estimated from the cosmic microwave background. If all available baryons cool and fb = fb, max, then the time delays imply H0 = 65 ± 6 km s-1 Mpc-1 (95% confidence). If local inventories of cold baryons, fb ≃ 0.013/h70, are correct, then H0 = 52 ± 6 km s-1 Mpc-1 and the halo parameters closely match isothermal mass models. Isothermal models are also consistent with strong and weak lens studies, stellar dynamics, and X-ray observations on these scales, while significantly more centrally concentrated models are not. There is a conflict between gravitational lens time delays, the local distance scale, and standard CDM halo models.
On available bandwidth measurement implementation and experiment

We summarize the implementation and experiment of the available bandwidth measurement algorithm (He et al. (2001)). Our experiment shows that, compared with other measurement techniques, this algorithm can achieve better performance, lower overhead and fast convergence. It can also self-adapt to any bandwidth and respond to resolution requirements. Therefore, no prior knowledge about bottleneck bandwidth is required and measurement resolution can be specified to meet application requirements, which is important for applications and services designed for high speed networks and multimedia applications due to the wide range of bandwidths that may be required.