Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Polarity Classification Using Statistical Data Compression Models

With growing availability and popularity of user generated content, the discipline of sentiment analysis has come to the attention of many researchers. Existing work has mainly focused on either knowledge based methods or standard machine learning techniques. In this paper we investigate sentiment polarity classification based on adaptive statistical data compression models. We evaluate the classification performance of the loss less compression algorithm Prediction by Partial Matching (PPM) as well as compression based measures using PPM-like character n-gram frequency statistics. Comprehensive experiments on three corpora show that compression based methods are efficient, easy to apply and can compete with the accuracy of sophisticated classifiers such as support vector machines.
Macular Ganglion Cell Analysis Determined by Cirrus HD Optical Coherence Tomography for Early Detecting Chiasmal Compression

Purpose To evaluate the performance of macular ganglion cell-inner plexiform layer (mGCIPL) measurement with Cirrus high-definition (HD) optical coherence tomography (OCT) for early detection of optic chiasmal compression. Methods Forty-six eyes of 46 patients with optic chiasmal compression caused by a pituitary adenoma (PA group), 31 eyes of 31 patients with normal tension glaucoma (NTG group), and 32 eyes of 32 normal participants (control group) were enrolled. The PA group was subdivided into two subgroups, which comprised patients with temporal visual field (VF) defects (perimetric PA group, 34 eyes) and without VF defect (preperimetric PA group, 12 eyes). The mGCIPL thickness and circumpapillary retinal nerve fiber layer (cpRNFL) thickness were measured using Cirrus HD-OCT. We calculated the number of patients who had an abnormal GCA sector map, defined as at least one yellow or red sector. Results Eyes in the perimetric PA group had significantly decreased mGCIPL thickness in all sectors. Eyes in the preperimetric PA group had significantly thinner mGCIPL in the superior, superonasal, inferonasal, and inferior sectors than eyes in control group, but no changes in cpRNFL parameters were observed. The mGCIPL thickness in inferonasal area showed the greatest AUC value (0.965), followed by the superonasal area (0.958) for discriminating preperimetric PA group from the control group. A higher reduction rate of mGCIPL thickness was noted in the nasal sector compared to other sectors, which was irrespective of temporal visual field defects. The mGCIPL thickness maps showed superonasal (P = 0.003) and inferonasal thinning in the PA group (P = 0.003), while inferotemporal thinning was revealed in the NTG group (P = 0.001). Conclusions Macular GCIPL thickness parameters obtained with the Cirrus HD-OCT were useful in early detection of chiasmal compression and differentiating from NTG by characteristic nasal mGCIPL thinning.
Design Artifact to Support Knowledge-Driven Predictive and Explanatory Decision Analytics

In this paper, we develop a novel design artifact to support knowledge-driven predictive and explanatory decision analytics for a complex business process. Following Design Science research guidelines in Hevner et al, (2004), we show the development of the design artifact and evaluate the artifact’s effectiveness in providing intelligent decision support for a complex business process. We present a design artifact that provides predictive and explanatory analytics to support intelligent decision-making. We use a large, automated, continuous manufacturing process as the problem domain where the continual monitoring of the process using knowledgedriven, intelligent tools is useful for process monitoring and quality control problems. This research contributes to design science by explicating a novel artifact with predictive and explanatory features that are useful in intelligent systems design. It provides sophisticated and adaptable intelligent decision support to the problem domain of process control.
Smooth Support Vector Machines

Smoothing methods, extensively used for solving important mathematical programming problems and applications, are proposed here to generate and solve an unconstrained smooth reformulation of support vector machines for pattern classification using completely arbitrary kernels. We term such reformulations smooth support vector machines (SSVMs). A fast Newton-Armijo algorithm for solving the SSVMs converges globally and quadratically. Numerical results and comparisons are given to demonstrate the effectiveness and speed of the algorithm. On six publicly available datasets, tenfold cross validation correctness of SSVM was the highest compared with four other methods as well as the fastest on five of these datasets. Using nonlinear kernels, SSVMs also obtained very distinct nonlinear separations for the checkerboard and the two-spiral datasets. A medical application is also proposed here. A linear support vector machine (SVM) is used to extract 6 features from a total of 31 features in a dataset of 253 breast cancer patients. Five features are nuclear features obtained during a non-invasive diagnostic procedure while one feature, tumor size, is obtained during surgery. The linear SVM selected the 6 features in the process of classifying the patients into node-positive (patients with some metastasized lymph nodes) and nodenegative (patients with no metastasized lymph nodes). The 6 features were then used in a Gaussian kernel nonlinear SVM to classify the patients into three prognostic groups: good (node-negative), intermediate (1 to 4 metastasized nodes) and poor (more than 4 metastasized nodes). Very well separated Kaplan-Meier survival curves were constructed for the three groups with pairwise p-value of less than 0.009 based on the logrank statistic. New patients can be assigned to one of these three prognostic groups with its associated survival curve, based only on 6 features obtained before and during surgery, but without the potentially risky procedure of removing lymph nodes to determine how many of them have metastasized.
Turbo Equalization without MMSE Filtering

The filter-based turbo equalization scheme has been proposed in several papers to avoid the prohibitive complexity imposed by the trellis-based turbo equalization. In the existing literature,the filter-based approach has been solely implemented by a linear MMSE filter, the coeffi cients of which are updated to minimize the mean-square error for every output symbol of the equalizer. A new turbo equalization algorithm is introduced in this paper. It has a lower computational complexity compared to most of the existing MMSE filter-based turbo equalization schemes. The complexity reduction is accomplished by deriving log-likelihood ratios (LLRs) directly from the output of an interference canceler, thus avoiding the MMSE filtering and its inherent matrix inversion for each symbol estimate. Numerical results show that the proposed scheme enables ISI-free transmission for some frequency selective channels.
H0 from an orientation-unbiased sample of Sunyaev–Zel'dovich and X-ray clusters

We have observed the Sunyaev-Zel'dovich (SZ) effect in a sample of five moderate-redshift clusters with the Ryle Telescope, and used them in conjunction with X-ray imaging and spectral data from ROSAT and ASCA to measure the Hubble constant. This sample was chosen with a strict X-ray flux limit using both the Bright Cluster Sample and the Northern ROSAT All-Sky Survey (RASS) cluster catalogues to be well above the surface brightness limit of the RASS, and hence to be unbiased with respect to the orientation of the cluster. This controls a major potential systematic effect in the SZ/X-ray method of measuring H 0 . Taking the weighted geometric mean of the results and including the main sources of error, namely the noise in the SZ measurement, the uncertainty in the X-ray temperatures and the unknown ellipticity and substructure of the clusters, we find H 0 = 59 +10 -9 (random) +8 -7 (systematic) km s -1 Mpc -1 assuming a standard cold dark matter model with Ω M = 1.0, Ω A = 0.0 or H 0 = 66 +11 +9 -10 -8 km s -1 Mpc -1 if Ω M = 0.3, Ω A = 0.7.
Cricket-based robots

This article describes the development of an autonomous hybrid microrobot that uses legs for propulsion and support of the rear half of the body and a pair of wheels for support of the front half. McKibben artificial muscles actuate the legs, and compressed air is generated by an onboard power plant. Control is also onboard in the form of a PIC microcontroller, from Microchip Technology Inc., that controls the actuators through four three-way valves that are each made up of a pair of microelectromechanical system devices. Its motion resembles that of a cricket.
Measuring Emotions A comparison of the PAD scale , Premo and checklist

The emotional feelings evoked by advertisements/products exert a powerful influence on consumer and decision making (Isen at al. 1982; Clark & Isen 1982). For instance, several studies provide evidence for the strong effect of emotions on brand attitudes (e.g., Williams & Aaker 2002). For practitioners and researchers, knowledge about how consumers’ emotions influence their behavior and brand attitudes can be of considerable importance. As a result, it is of major concern that emotions are reliably measured so that one can predict the effect of the evoked emotions on advertisement/product acceptability. In this regard, this study compares three often used self-report measurement techniques: two verbal-based techniques, namely the PAD-scale (Pleasure –Arousal – Dominance scale) (Russell & Mehrabian 1977; Mehrabian 1995), and the Checklist (which consists of a list of emotions from which respondents choose the emotion which expresses their feeling the closest) (Russell & Mehrabian 1977), and a visual-based technique, namely the Product Emotion Measure (PrEmo) (Desmet, Hekkert & Jacobs 2000; Desmet 2003).
IN HONOUR OF NICK HANDY Hybrid variational – perturbation method for calculating ro-vibrational energy levels of polyatomic molecules

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System-on-chip integration of embedded automotive controllers

Automotive embedded systems today fulfill a large variety of tasks -- from simple mechanisms like window regulators to the control of complex multimedia systems. Current high-end cars use more than 70 microcontrollers, connected over one or more common bus systems. Many of these controllers are comparatively simple 8- or 16-bit systems. The availablility of large-scale FPGAs enables system designers to replace several of these systems with an implementation as software cores. This paper examines novel possibilities for and problems encountered with the integration of several such smaller control components onto an FPGA. Special focus is set on reusability of software by using instruction-compatible CPU cores and interfacing to physical controller units. The paper examines the amount of control systems that can be integrated onto different FGPAs, methods for saving space by including only required on-chip peripherals and the achievable overall performance of the integrated system.
The Effects of Subjective and Objective Competitive Outcomes on Intrinsic Motivation

The present study was designed to assess the effects of subjective and objective competitive outcomes on intrinsic motivation following completion of a one-on-one basketball jump-shooting competition. Researchers all too often operationalize competitive outcomes in terms of winning and losing, and neglect to examine performance from the subjective perspective of the individual. The intrinsic motivation of winners and losers and individuals high and low in perceived success were compared by employing a multidimensional measure of intrinsic motivation. Results indicated that both winners and high success individuals displayed significantly greater intrinsic motivation than losers and low. success individuals, respectively. However, multivariate analyses of variance demonstrated significant differences only between the perceived success groups when intrinsic motivation was examined at a multidimensional level. Specifically, high success individuals perceived themselves as trying; harder, being more competent.
The Lung Inflammation and Skeletal Muscle Wasting Induced by Subchronic Cigarette Smoke Exposure Are Not Altered by a High-Fat Diet in Mice

Obesity and cigarette smoking independently constitute major preventable causes of morbidity and mortality and obesity is known to worsen lung inflammation in asthma. Paradoxically, higher body mass index (BMI) is associated with reduced mortality in smoking induced COPD whereas low BMI increases mortality risk. To date, no study has investigated the effect of a dietary-induced obesity and cigarette smoke exposure on the lung inflammation and loss of skeletal muscle mass in mice. Male BALB/c mice were exposed to 4 cigarettes/day, 6 days/week for 7 weeks, or sham handled. Mice consumed either standard laboratory chow (3.5 kcal/g, 12% fat) or a high fat diet (HFD, 4.3 kcal/g, 32% fat). Mice exposed to cigarette smoke for 7 weeks had significantly more inflammatory cells in the BALF (P<0.05) and the mRNA expression of pro-inflammatory cytokines and chemokines was significantly increased (P<0.05); HFD had no effect on these parameters. Sham- and smoke-exposed mice consuming the HFD were significantly heavier than chow fed animals (12 and 13%, respectively; P<0.05). Conversely, chow and HFD fed mice exposed to cigarette smoke weighed 16 and 15% less, respectively, compared to sham animals (P<0.05). The skeletal muscles (soleus, tibialis anterior and gastrocnemius) of cigarette smoke-exposed mice weighed significantly less than sham-exposed mice (P<0.05) and the HFD had no protective effect. For the first time we report that cigarette smoke exposure significantly decreased insulin-like growth factor-1 (IGF-1) mRNA expression in the gastrocnemius and tibialis anterior and IGF-1 protein in the gastrocnemius (P<0.05). We have also shown that cigarette smoke exposure reduced circulating IGF-1 levels. IL-6 mRNA expression was significantly elevated in all three skeletal muscles of chow fed smoke-exposed mice (P<0.05). In conclusion, these findings suggest that a down-regulation in local IGF-1 may be responsible for the loss of skeletal muscle mass following cigarette smoke exposure in mice.
Data Abstraction In Cognitive Models for Compositional Design in Painting

In this paper, we discuss the design of painting data, which is neutral emotionally, for use in the training and building of models of cognition. The data will provide training examples for visual cortex and emotion modules. There are two goals to this research: first, model the process of artistic design for eventual use in the development of an autonomous painting composition program; and second, use the painting model as a quantitative means of training the visual cortex portion and associated emotional circuits of a general model of cognition. ∗Department of Mathematical Sciences, Martin Hall BOX 0975, Clemson University, Clemson SC 296340975, email: petersj@clemson.edu †Department of Performing Arts, Brooks Center BOX 0525, Clemson University, Clemson SC 29634-0525, email: ldzuris@clemson.edu
Analysis of Mixed Production Line Based on Complex Weighted Network

Mixed production line is a complex system which comprises various dynamic elements and complicated structure, so it is difficult to describe and model. In this paper complex weighted network is presented, while mixed production line is simplified to vertices and directed edges in a weighted networks. Manufacturing units are regarded as vertices to denote various resources, such as equipments and workers. In network model the production process acts as a topological generator to create directed edges and network structure. Weight is assigned to represent the intensity of directed process relationships from one vertex to another. Some feature vectors and matrixes are constructed to characterize mathematic model of mixed production line. Moreover some statistical properties might uncover its dynamic status and to obtain important vertices and edges. Especially the connectivity of vertices could exhibit their effects on the whole system. Then corresponding controlling strategies are suggested to maintain stability of mixed production line. Finally an actual mixed production line as an example is analyzed in this paper to exhibit method and approach of complex weight network.
Characteristics Research on Double LCC Compensation Converter in the Inductive Energy Transfer System

Double LCC compensation resonant converter is effectively applicable to inductively coupled energy transfer, for the advantages of perfect symmetry and simple design. However, the system gain characteristics and output characteristics of the circuit overall structure were ignored in the previous study of double LCC compensation converter. In this paper, impedance analysis method is used to determine gain characteristic of system, finding that the system has a constant current source output characteristics in addition to purely resistance at a fixed frequency point, which is independent of the load and the coupling coefficient. Two methods of parameters optimization are proposed in this paper, which are used to realize ZVS (Zero Voltage Switch) for the full-bridge inverter. Subsequently, the effects of different methods on the gain characteristics are compared. A design idea of a double LCC compensation topology under different working conditions is provided. The whole optimization method is simple, accurate and practical. Finally, a 3.3 kW double LCC resonant converter is completed. The characteristics of the converter and optimization method are verified from simulation and experimental results.
A 0.5-μm CMOS 4.0-Gbit/s serial link transceiver with data recovery using oversampling

A 4-Gbit/s serial link transceiver is fabricated in a MOSIS 0.5-/spl mu/m HPCMOS process. To achieve the high data rate without speed critical logic on chip, the data are multiplexed when transmitted and immediately demultiplexed when received. This parallelism is achieved by using multiple phases tapped from a PLL using the phase spacing to determine the bit time. Using an 8:1 multiplexer yields 4 Gbits/s, with an on-chip VCO running at 500 MHz. The internal logic runs at 250 MHz. For robust data recovery, the input is sampled at 3/spl times/ the bit rate and uses a digital phase-picking logic to recover the data. The digital phase picking can adjust the sample at the clock rate to allow high tracking bandwidth. With a 3.3-V supply, the chip has a measured bit error rate (BER) of <10/sup -14/.
A light non-standard Higgs boson: to be or not to be at a (Super) B factory?

A light non-standard Higgs boson decaying mainly into $\tau^+\tau^-$ has not been yet ruled out by LEP searches in several scenarios. We verify that, in the context of the Next-to-Minimal-Supersymmetric Standard Model, a low-mass CP-odd (mostly but not completely singlet-like) Higgs boson can couple strongly enough to down-type fermions to be detected in radiative $\Upsilon$ decays into tauonic pairs at a high-luminosity B factory. Possible spectroscopic effects of a mixing with $\eta_b$ resonances are also analyzed
System Design of a Quadrupedal Galloping Machine

In this paper we present the system design of a machine that we have constructed to study a quadrupedal gallop gait. The gallop gait is the preferred high-speed gait of most cursorial quadrupeds. To gallop, an animal must generate ballistic trajectories with characteristic strong impacts, coordinate leg movements with asymmetric footfall phasing, and effectively use compliant members, all the while maintaining dynamic stability. In this paper we seek to further understand the primary biological features necessary for galloping by building and testing a robotic quadruped similar in size to a large goat or antelope. These features include high-speed actuation, energy storage, on-line learning control, and high-performance attitude sensing. Because body dynamics are primarily influenced by the impulses delivered by the legs, the successful design and control of single leg energetics is a major focus of this work. The leg stores energy during flight by adding tension to a spring acting across an articulated knee. During stance, the spring energy is quickly released using a novel capstan design. As a precursor to quadruped control, two intelligent strategies have been developed for verification on a one-legged system. The Levenberg-Marquardt on-line learning method is applied to a simple heuristic controller and provides good control over height and forward velocity. Direct adaptive fuzzy control, which requires no system modeling but is more computationally expensive, exhibits better response. Using these techniques we have been successful in operating one leg at speeds necessary for a dynamic gallop of a machine of this scale. Another necessary component of quadruped locomotion is high-resolution and high-bandwidth attitude sensing. The large ground impact accelerations, which cause problems for any single traditional sensor, are overcome through the use of an inertial sensing approach using updates from optical sensors and vehicle kinematics.
Bone morphogenetic protein-5 and early endothelial outgrowth cells (eEOCs) in acute ischemic kidney injury (AKI) and 5/6-chronic kidney disease.

Early endothelial outgrowth cells (eEOCs) reproducibly have been shown to act protectively in acute ischemic kidney injury (AKI) and chronic kidney injury. Bone morphogenetic protein-5 (BMP-5) acted antifibrotically in human hypertensive nephropathy. The aim of the current study was to analyze effects of BMP-5 treatment in an eEOC-based therapy of murine AKI and 5/6-nephrectomy. Male C57/Bl6N mice were either subjected to unilateral renal artery clamping postuninephrectomy or to 5/6-nephrectomy. Untreated or BMP-5-pretreated murine eEOCs were injected into recipient animals at the time of reperfusion (AKI) or at 2 and 5 days after 5/6-nephrectomy. Analysis of renal function and morphology was performed at 48 h and at 6 wk (AKI) or at 8 wk (5/6 model). Cellular consequences of eEOC treatment were evaluated using different in vitro assays. AKI was mitigated significantly by injecting BMP-5-pretreated eEOCs. Renal function was improved at 48 h [corrected] after cell therapy. In 5/6-nephrectomy, the cells failed to act renoprotectively, [corrected] but proteinuria was reduced after administering untreated eEOCs. " Next, the original version read as "BMP-5 acts as a potent eEOC agonist in murine AKI in the short [corrected] term. Cell effects in 5/6-nephrectomy are heterogenous, but untreated cells act antifibrotically [corrected] without any impact on EnMT.