Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute Metabolic Response to High-Carbohydrate, High-Starch Meals Compared With Moderate-Carbohydrate, Low-Starch Meals in Subjects With Type 2 Diabetes

OBJECTIVE The monosaccharides resulting from the digestion of ingested carbohydrates are glucose, fructose, and galactose. Of these three monosaccharides, only ingested glucose resulted in a large increase in the plasma glucose concentration. Fructose (Metabolism 41:510–517, 1992) and galactose (Metabolism 42:1560–1567, 1993) had only a minor effect. Therefore, we were interested in determining whether we could design a mixed meal, using foods of known monosaccharide, disaccharide, and starch composition, the ingestion of which would result in only a small rise in plasma glucose concentration. RESEARCH DESIGN AND METHODS The experimental meal was composed of very little readily digestible starch but rather large amounts of fruits and vegetables. It contained 43% carbohydrate, 22% protein, and 34% fat. The results were compared with a second type of meal that contained 55% carbohydrate, 15% protein, and 30% fat, with an emphasis on complex carbohydrates (starch). It also was compared with a third meal that contained 40% carbohydrate, 20% protein, and 40% fat, typical of that consumed by the average American. The test meals were ingested in random order by people with type 2 diabetes who were not treated with oral hypoglycemic agents or insulin. Each subject ingested each type of meal. The same identical meal was ingested at 0800, 1200, and 1700. RESULTS The integrated 24-h plasma glucose area response was statistically significantly smaller (P < 0.05) after ingestion of the low-starch meals compared with the high-starch, highcarbohydrate meals or the typical American meals. The 24-h integrated serum insulin area response also was statistically significantly less (P < 0.05) after ingestion of the low-starch meals compared with the high-starch meals or the typical American meals. The serum triglyceride area response was similar after ingestion of all three test diets. CONCLUSIONS A diet in which fruits, nonstarch vegetables, and dairy products are emphasized may be useful for people with type 2 diabetes.
Active user detection and channel estimation in uplink CRAN systems

Cloud Radio Access Network (CRAN) is proposed as a promising network architecture for future mobile communications. In this paper, we consider the topic of active user detection (AUD) and channel estimation (CE) in uplink CRAN systems with sparse active users. Different from conventional AUD and CE approaches which require the length of uplink pilots to scale with the number of users times the number of antennas per user, a novel algorithm will be proposed to substantially reduce the uplink training overhead by leveraging the technique of compressive sensing (CS). To achieve this goal, we first transform the problem of AUD and CE into standard CS problems. We then propose a modified Bayesian compressive sensing (BCS) algorithm to conduct AUD and CE in CRAN, which exploits not only the active user sparsity, but also the innate heterogeneous path loss effects and the joint sparsity structures in multi-antenna uplink CRAN systems.
New signature schemes in the standard model based on publicly verifiable CCA-secure public key encryption

Till now, there are not many ways to construct signature schemes in the standard model and recently many researchers show great interest in construction secure signatures in the standard model. CCA secure publicly verifiable public key encryption in the standard model PVPKE is a new interesting primitive, in which the ciphertext's validity/integrity can be publicly verified. In this paper, we propose a new way to construct signature schemes in the standard model. That is, transforming CCA secure publicly verifiable public key encryption schemes into signature schemes. Our transformation based on the following facts: 1 the signature scheme and CCA secure publicly verifiable public key encryption scheme share the same 'publicly verifiability' property; 2 the signature scheme requires the signatures can not be malleable, and CCA secure publicly verifiable public key encryption also require the ciphertexts can not be malleable; 3 public key encryption and digital signature schemes can be viewed as dual of each other. By utilising these facts, we try to give a new way to construct signature scheme in the standard model.
Elastic wave propagation along a set of parallel fractures

Previous studies on elastic wave propagation in fractured media have demonstrated that a single planar fracture supports fracture interface waves and that two plane parallel fractures support fracture channel waves. Here, the results are presented for plane wave propagation through an infinite number of plane parallel fractures with equal fracture spacing and fracture stiffnesses. Analysis of the dispersion equations for this fractured system demonstrates that these waves exhibit symmetric and antisymmetric particle motions, degenerate to classical Rayleigh‐Lamb plate waves when the fractures are completely open, and possess dispersive velocities that are functions of both the fracture stiffness and spacing. Time‐frequency analysis performed on a series of laboratory ultrasonic transmission measurements on a fractured rock analog shows good agreement with the theoretical predictions.
Real‐time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location

Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits.
Evaluation of renal masses detected by excretory urography: cost-effectiveness of sonography versus CT.

OBJECTIVE The purpose of this study was to compare the cost-effectiveness of sonography and CT for the evaluation of renal masses discovered at excretory urography. MATERIALS AND METHODS The records of 225 patients with a renal mass shown by urography who then had either sonography or CT within 3 months were reviewed retrospectively. The number, location, and size of lesions; initial and subsequent imaging tests; and final diagnoses were determined. Using the current Medicare reimbursements for sonography and CT, we calculated the economic implications of using sonography or CT as the initial examination. Any effect of the location or size of the lesion on the most cost-effective examination was also determined. RESULTS Twenty-one percent of patients had both initial sonography and follow-up CT because of indeterminate findings or detection of a solid mass that required further staging. When CT was done first, CT findings were equivocal in 12%, necessitating follow-up sonography. At the prevailing charges, CT would have to be needed in 70% of patients initially imaged with sonography to justify the use of CT as the initial examination. The location and size of the lesion did not affect the need for CT at a rate (greater than 70%) that would economically justify use of CT as the first imaging test. Eighty-six percent of patients with a mass detected by urography had either a simple cyst or no evidence of a mass on sonography or CT. CONCLUSION Sonography is the most cost-effective imaging method for the workup of a renal mass detected at urography. The number of sonographic examinations in which findings are indeterminate or positive (for a solid mass) is not sufficiently high to warrant replacement of sonography by CT, regardless of the size and location of the lesion. CT should be reserved for a limited number of specific indications.
Synaptic noise facilitates the emergence of self-organized criticality in the Caenorhabditis elegans neuronal network

ABSTRACT Avalanches with power-law distributed size parameters have been observed in neuronal networks. This observation might be a manifestation of self-organized criticality (SOC). Yet, the physiological mechanisms of this behaviour are currently unknown. Describing synaptic noise as transmission failures mainly originating from the probabilistic nature of neurotransmitter release, this study investigates the potential of this noise as a mechanism for driving the functional architecture of the neuronal networks towards SOC. To this end, a simple finite state neuron model, with activity dependent and synapse specific failure probabilities, was built based on the known anatomical connectivity data of the nematode Ceanorhabditis elegans. Beginning from random values, it was observed that synaptic noise levels picked out a set of synapses and consequently an active subnetwork that generates power-law distributed neuronal avalanches. The findings of this study bring up the possibility that synaptic failures might be a component of physiological processes underlying SOC in neuronal networks.
An analytical model for MOSFET local oxide capacitance

Practically all methods for extraction of the lateral interface state density profile N<inf>it</inf>(x) from charge-pumping data employ the oxide capacitance C<inf>ox</inf> [1–3] as a crucial parameter. Although Lee et al. [2] claimed that the coordinate dependence of the capacitance C<inf>ox</inf>(x) due to the fringing effect should be respected, usually C<inf>ox</inf> is treated as a constant parameter of the device [3]: C<inf>ox</inf>=ε<inf>ox</inf>/t<inf>ox</inf>, (1), where t<inf>ox</inf> is the oxide thickness at the center of the device and ε<inf>ox</inf> is the dielectric permittivity. However, the electric field non-uniformity is of special importance for the extraction of the interface state density profile after hot-carrier stress because the N<inf>it</inf>(x) peak is located near the drain end of the gate [4] where the capacitor non-ideality is most pronounced.
A Sensitive Skin for Robotic Companions Featuring Temperature, Force, and Electric Field Sensors

As robots become an everyday part of the complicated environment of the human world it will be important for such systems to feature a full body sense of touch capable of detecting a wide variety of tactile inputs. Such "sensitive skins" can provide much benefit in human robot interaction, specifically in the realm of robotic companions for therapeutic or service applications. In this paper we present a set of design criteria for how such "skins" should be designed. Based on this criteria, a "skin" which features temperature, force, and electric field sensing is described. Results from early experiments with this skin show how the sensors of the multi-modal skin complement each other and allow the distinction between social and affective classes of touch to be distinguished from touch with physical objects
USING THE TRANSPIRATION REGIME TO ESTIMATE BIOMASS PRODUCTION

The design and implementation of a new or improved irrigation or drainage system should be preceded by a study of the soil water regime (SWR) to define the need for such a system and to optimize its design. This requires estimates of appropriate parameters characterizing the long-term (multiyear) dynamics of the SWR and its relation to biomass production. Parameters that could be used for this purpose are the water content or pressure head at one or several points in the soil root zone or the average water content of the root zone, as affected by precipitation and evapotranspiration or other variables. Because these variables change from year to year, it is necessary to characterize somehow statistically the SWR during a relatively long period. Because the water content is not easily related directly to biomass production, we used the calculated seasonal transpiration rate as an indirect characteristic of the canopy water regime. This article presents a method for estimating plant production as a function of the seasonal transpiration rate as calculated retrospectively with the HYDRUS-ET software package. New in our approach is the use of an empirical relationship between seasonal transpiration and yield. The cumulative frequency distribution of seasonal transpiration was chosen as the basic characteristic of the SWR as a source of water for plants. The approach allows one to estimate cumulative frequency curves of actual and potential yields. The difference between these two curves is the cumulative frequency distribution of yield to be optimized by the irrigation system. The method permits a better cost-benefit analysis by comparing expected yield increases with the investment and operational expenses of the newly designed irrigation system, or of newly invoked water management practices. The approach is illustrated using a 31-year time series of data for a corn crop (Zea mays L.) grown on loess soil in Slovakia.
Intelligent tutors for all: Constraint-based modeling methodology, systems and authoring

Intelligent Tutoring Systems (ITS) have revolutionized online education by providing individualized instruction tailored towards each student. Constraint-based tutors model instructional domains at an abstract level, a novel approach that simplifies the development of ITSs. We have developed many effective constraint-based tutors over the last decade in a number of instructional domains of various characteristics, some of which have been successfully commercialized. Constraint-based tutoring is now a mature and successful approach to providing adaptive learning environments. Our authoring tools aim to make this technology widely available to teachers and students everywhere.
DATA AS DEMONSTRATOR with Applications to System Identification

Machine learning techniques for system identification and time series modeling often phrase the problem as the optimization of a loss function over a single timestep prediction. However, in many applications, the learned model is recursively applied in order to make a multiple-step prediction, resulting in compounding prediction errors. We present DATA AS DEMONSTRATOR [15], an approach that reuses training data to make a no-regret learner robust to errors made during multistep prediction. We present results on the task of linear system identification applied to a simulated system and to a real world dataset.
Overview on automatic detection of human body

Automatic detection of human in a video sequence is a canonical instance of object detection. It's considered as a nonrigid object; it has many appearances at different perspectives. Different approaches are used by several methods to combine what is specific to the pedestrian detection, and what is common to the object recognition. A robust solution to this problem would have numerous applications to design smart systems, including video surveillance, power management, vehicle driver assistance systems, and evaluation of advertising policies. In this article we will discuss the main techniques of human (pedestian) detection on video sequence. Especially those how are learning-based methods. Then we describe in general terms the type of information that can be extracted once the detection is performed.
Effects of Self-Efficacy on Transfer of Cross-Cultural Training and Expatriate Performance

The presented study focused on the effect of self-efficacy, as well as other selected demographic variables, on the transfer of cross-cultural training and expatriate performance. Selected independent variables include self-efficacy, expatriate tenure, level of education, gender, age, marital status, level of foreign language competency and level of formal cross-cultural experience. Expatriates employed by multinational company that were on their current assignments were selected to be the studied sample. The design of this study employed a quantitative research method. A survey instrument crafted specifically for this study was digitized and was made accessible for participants via the Internet. After the data was automatically collected, appropriate statistical analysis tools such as descriptive statistics, correlations of means, Analysis of Variance, and a reliability test such as Cronbach’s alpha were used for data analysis purposes. Expatriate’s perceived self-efficacy was found to interactive with the transfer of cross-cultural training (CCT). While demographic variables such as expatriate tenure, level of education, gender, age, martial status, level of foreign language competency, and level of formal cross-cultural experience were found having no correlation with the transfer of CCT, the test results show self-efficacy to have strong impact on expatriate’s performance. Based on the conclusions, a set of recommendations has been made for future researchers. Implications for HRD practitioners and multinational organizations have also been explored.
Maximizing the Information Content of Experiments in Systems Biology

Our understanding of most biological systems is in its infancy. Learning their structure and intricacies is fraught with challenges, and often side-stepped in favour of studying the function of different gene products in isolation from their physiological context. Constructing and inferring global mathematical models from experimental data is, however, central to systems biology. Different experimental setups provide different insights into such systems. Here we show how we can combine concepts from Bayesian inference and information theory in order to identify experiments that maximize the information content of the resulting data. This approach allows us to incorporate preliminary information; it is global and not constrained to some local neighbourhood in parameter space and it readily yields information on parameter robustness and confidence. Here we develop the theoretical framework and apply it to a range of exemplary problems that highlight how we can improve experimental investigations into the structure and dynamics of biological systems and their behavior.
Adaptive weak approximation of stochastic differential equations

Adaptive time‐stepping methods based on the Monte Carlo Euler method for weak approximation of Itô stochastic differential equations are developed. The main result is new expansions of the computational error, with computable leading‐order term in a posteriori form, based on stochastic flows and discrete dual backward problems. The expansions lead to efficient and accurate computation of error estimates. Adaptive algorithms for either stochastic time steps or deterministic time steps are described. Numerical examples illustrate when stochastic and deterministic adaptive time steps are superior to constant time steps and when adaptive stochastic steps are superior to adaptive deterministic steps. Stochastic time steps use Brownian bridges and require more work for a given number of time steps. Deterministic time steps may yield more time steps but require less work; for example, in the limit of vanishing error tolerance, the ratio of the computational error and its computable estimate tends to 1 with negligible additional work to determine the adaptive deterministic time steps. © 2001 John Wiley & Sons, Inc.
Oncologic outcomes in rectal cancer with close distal resection margins: a retrospective analysis

Purpose The assurance of a negative resection margin is significant in rectal cancer as it indicates a reduced risk of local recurrence; thus, sufficient length of the resection margin is strongly required. The purpose of this study was to analyze the relationship between the length of the distal resection margin (DRM) and local recurrence or survival rate and to evaluate the possibility of performing sphincter-conserving surgery. Methods The medical records of 218 rectal cancer patients were analyzed. Patients were classified into three groups according to the length of the DRM as follows: group 1, DRM < 1 cm; group 2, 1 cm ≤ DRM ≤ 2 cm; and group 3, DRM > 2 cm. Results Of 218 patients enrolled, 81 were in group 1, 66 in group 2, and 71 in group 3. The 5-year survival rates were 78.2%, 78.2%, and 76.8% for groups 1, 2, and 3, respectively, and there were no statistically significant differences in survival (P = 0.913). Local recurrence was found in 2 patients in group 1, 1 patient in group 2, and 1 patient in group 3; there were no statistically significant differences in local recurrence (P = 0.908). Conclusion A DRM of < 1 cm did not impair the oncologic outcomes of rectal cancer patients. Our results indicated that surgeons should keep in mind to consider the option of sphincter-conserving surgery with adjuvant chemoradiotherapy even in very low rectal cancer.
Advances in Brief S 100 Family Members and Trypsinogens Are Predictors of Distant Metastasis and Survival in Early-Stage Non-Small Cell Lung Cancer

Distant metastasis is the predominant cause of death in early-stage non-small cell lung cancer (NSCLC). Currently, it is impossible to predict the occurrence of metastasis at early stages and thereby separate patients who could be cured by surgical resection alone from patients who would benefit from additional chemotherapy. In this study, we applied a comparative microarray approach to identify gene expression differences between early-stage NSCLC patients whose cancer ultimately did or did not metastasize during the course of their disease. Transcriptional profiling of 82 microarrays from two patient groups revealed differential expression of several gene families including known predictors of metastasis (e.g., matrix metalloproteinases). In addition, we found S100P, S100A2, trypsinogen C (TRY6), and trypsinogen IVb (PRSS3) to be overexpressed in tumors that metastasized during the course of the disease. In a third group of 42 patients, we confirmed the induction of S100 proteins and trypsinogens in metastasizing tumors and its significant correlation with survival by real-time quantitative reverse transcriptionPCR. Overexpression of S100A2, S100P, or PRSS3 in NSCLC cell cultures led to increased transendothelial migration, corroborating the role of S100A2, S100P, and PRSS3 in the metastatic process. Taken together, we provide evidence that expression of S100 proteins and trypsinogens is associated with metastasis and predicts survival in early stages of NSCLC. For the first time, this implicates a role of S100 proteins and trypsinogens in the metastatic process of early-stage NSCLC.
An adaptive speed term based on generalized fuzzy operator for level set segmentation

The major problem of level set segmentation is boundary leakage when a weak boundary or missing part of a boundary occurs. Some efforts, e.g., adding extra stopping criteria or region information, have been used to avoid such problem. However, in existing level-set techniques, the gradient information is used as stopping criteria for curve evolution, and also provides the attracting force to the zero level set from a target boundary, which can never fully stop the level set evolution even for ideal edges and thereby makes leakage unavoidable. In this paper, we proposed an adaptive speed term based on generalized fuzzy operator (GFO), as a replacement for traditional gradient-based edge map applied in level set segmentation techniques. The proposed GFO provides more robust edge estimation and more reliable criteria for adaptively changing the advent speed. Therefore, by using this term, the leakage problem can be avoided effectively in most cases compared to traditional level set methods. Additionally, the computation of the adaptive approach proposed in this paper is fast and its extension to the 3-D case is straightforward.
Performance enhancement of I/O scheduler for Solid State Devices

Due to the benefits of Solid State Drive (SSD), it has been called a pivotal technology on data storage systems. But, current device level I/O schedulers are not optimized for SSD. In this paper, we suggest a new I/O scheduler, called STB, to exploit the performance potential of SSDs. Our STB scheduler categorizes I/O requests into two groups and sets timers on each request. We implement STB scheduler in Linux 2.6. 30, and the set of benchmark programs shows that STB scheduler provides better bandwidth up to 30% with low response time of each request.