Miracle-dz/UniFAR-FTUs huggingface dataset:
Face-to-Face or Not-to-Face: A Technology Preference for Communication

This study employed the Model of Technology Preference (MTP) to explain the relationship of the variables as the antecedents of behavioral intention to adopt a social networking site (SNS) for communication. Self-administered questionnaires were distributed to SNS account users using paper-based and web-based surveys that led to 514 valid responses. The data were analyzed using structural equation modeling (SEM). The results show that two out of three attributes of the attribute-based preference (ATRP) affect attitude-based preference (ATTP). The data support the hypotheses that perceived enjoyment and social presence are predictors of ATTP. In this study, the findings further indicated that ATTP has no relationship with the behavioral intention of using SNS, but it has a relationship with the attitude of using SNS. SNS development should provide features that ensure enjoyment and social presence for users to communicate instead of using the traditional face-to-face method of communication.
Poster: can it be more practical?: improving mouse dynamics biometric performance

Mouse dynamics is the process of verifying the identity of computer users on the basis of their mouse operating characteristics, which are derived from the movement and click events. Some researchers have explored this domain and reported encouraging results, but few focused on applicability in a realistic setting. Specifically, many of the existing approaches require an impractically long verification time to achieve a reasonable accuracy. In this work, we investigate the mouse dynamics of 26 subjects under a tightly-controlled environment. Using procedural features such as speed and acceleration curves to more accurately characterize mouse activity, and adopting distance metrics to overcome the within-class variability, we achieved a promising performance with a false-acceptance rate of 8.87%, a false-rejection rate of 7.16%, and an average verification time of 11.8 seconds. We find that while this level of accuracy comes close to meeting the requirements of identity verification, a tradeoff must be made between security and user acceptability. We also suggest opportunities for further investigation through additional, controlled experimental environments.
Research of Intrusion Detection Based on Principal Components Analysis

The effective way of improving the efficiency of intrusion detection is to reduce the heavy data process workload. In this paper, the dimensionality reduction use of technology in the classic dimensionality reduction algorithm principal component to analysis large-scale data source for reduced-made features of the original data be retained and improved the efficiency of intrusion detection. And use BP neural network training the data after dimensionality reduction, will be effective in normal and abnormal data distinction, and achieved good results.
Efficacy and safety of antitumor agents plus radiotherapy compared with radiotherapy alone for brain metastases from lung cancer

The present study aimed to investigate the efficacy and safety of different therapeutic regimens for brain metastases (BMs) from lung cancer (LC). A total of 13 controlled trials (1,783 cases) involving chemotherapy, tyrosine kinase inhibitors or endostatin plus radiotherapy (combination group) vs. radiotherapy alone group were identified from PubMed. Compared with the radiotherapy alone group, the combination group resulted in a significant benefit for objective response rate (ORR) [risk ratio (RR), 1.38; 95% confidence interval (CI), 1.19–1.60; P<0.0001], notably prolonged the time to central nervous system progression [CNS-TTP; hazard ratio (HR), 0.71; 95% CI, 0.57–0.90; P=0.004] and progression-free survival (PFS; HR, 0.60; 95% CI, 0.44–0.83; P=0.002); however, failed in prolonging the overall survival (OS; HR, 0.80; 95% CI, 0.61–1.05; P=0.11) with a higher overall severe adverse events (AEs, Grade ≥3; RR, 2.57; 95% CI, 1.24–5.35; P=0.01). Notably, subgroup analysis demonstrated that targeted therapy plus radiotherapy possessed a superior OS compared with radiotherapy alone (HR, 0.58; 95% CI, 0.37–0.90; P=0.01) with mild non-hematological toxicity and without severe hematotoxicity. The present study demonstrated that targeted agents plus radiotherapy possessed desirable effects with mild adverse events. Secondary to best, chemoradiotherapy is an alternative option for patients without suitable molecular targets.
Taxonomy system for intelligent library search system

Most libraries nowadays use computerized system for searching. Observing the case at Atma Jaya Catholic University of Indonesia's library system, the results given by the search engine tends to be inaccurate or irrelevant, mostly due to insufficient input by the user. This research proposes further utilization of taxonomy system based on Dewey Decimal Classification in libwrary application. User personal taxonomy information that represents each user's interest of certain knowledge fields is created based on user actions on library collections. Results show that by combining the user's taxonomy information with the collection's knowledge field information, search results relevancies can be increased.
Oxygen uptake, respiratory exchange ratio, or total distance: a comparison of methods to equalize exercise volume in Wistar rats

This study compared strategies to equalize the volume of aerobic exercise performed with different intensities by Wistar rats, based on the distance covered during exercise bouts and energy expenditure (EE, isocaloric sessions) obtained from oxygen uptake (V̇O2) or respiratory exchange ratio (RER). Thirty-three male rats (270.5±12.8 g) underwent maximal exercise tests to determine V̇O2 reserve (V̇O2R), being randomly assigned to three groups: moderate-intensity continuous exercise at speed corresponding to 50% V̇O2R (MIC; n=11); high-intensity continuous exercise at 80% V̇O2R (HIC; n=11); and high-intensity intermittent exercise (HII; n=11) at 60% V̇O2R (3 min) and 80% V̇O2R (4 min). Exercise duration was calculated individually to elicit EE of 5 kcal in each session. No difference between groups was found for total running distance (MIC: 801±46, HIC: 734±42, HII: 885±64 m; P=0.13). Total EE measured by RER was systematically underestimated compared to values obtained from V̇O2 (HII: 4.5% and MIC: 6.2%, P<0.05). Total EE (calculated from V̇O2), and duration of HIC bouts (2.8 kcal and 30.8±2.2 min) were lower (P<0.0001) than in MIC (4.9 kcal and 64.7±1.8 min) and HII (4.7 kcal and 46.9±2.2 min). Predicted and actual values of total V̇O2, total EE, and duration of isocaloric sessions were similar in MIC and HII (P>0.05), which were both higher than in HIC (P<0.0001). In conclusion, the time to achieve a given EE in exercise bouts with different intensities did not correspond to the total distance. Therefore, the volume of aerobic exercise in protocols involving Wistar rats should be equalized using EE rather than total covered distance.
A lightweight inter-user interference mitigation method in Body Sensor Networks

Body Sensor Networks (BSNs) enable continuous and remote health monitoring in medical applications. Inter-user interference is the major cause that deteriorates the reliable data transmission in BSNs when multiple BSNs are transmitting simultaneously in close proximity to one another. This paper presents an inter-user interference mitigation (IIM) method, which enables BSNs to adaptively reschedule their transmissions or switch to another channel in a distributed manner based on the detected information from neighboring BSNs. By taking advantage of the general property of the low channel utilization of BSNs in typical medical applications, the proposed IIM method increases system utilization and thus alleviates inter-user interference. In addition, our IIM method operates in a distributed manner without the need of extra infrastructure as compared to other approaches. In this paper, we describe the detailed design of the IIM method, and provide performance comparisons through simulations. The simulation results indicate that with the proposed IIM method, the network throughput is improved by 30% on average, and the energy consumption for data transmission is reduced by 16%.
Weighted total generalized variation for compressive sensing reconstruction

Total generalized variation (TGV) is a generalization of total variation (TV). This method has gained more and more attention in image processing due to its capability of reducing staircase effects. As the existence of high order regularity, TGV tends to blur edges, especially when noise is excessive. In this paper, we propose an iterative weighted total generalized variation (WTGV) model to reconstruct images with sharp edges and details from compressive sensing data. The weight is iteratively updated using the latest reconstruction solution. The splitting variables and alternating direction method of multipliers (ADMM) are employed to solve the proposed model. To demonstrate the effectiveness of the proposed method, we present some numerical simulations using partial Fourier measurement for natural and MR images. Numerical results show that the proposed method can avoid staircase effects and keep fine details at the same time.
Forecasting Stock Market Volatility: Evidence from Fourteen Countries

This paper evaluates the out-of-sample forecasting accuracy of eleven models for weekly and monthly volatility in fourteen stock markets. Volatility is defined as within-week (within-month) standard deviation of continuously compounded daily returns on the stock market index of each country for the ten-year period 1988 to 1997. The first half of the sample is retained for the estimation of parameters while the second half is for the forecast period. The following models are employed: a random walk model, a historical mean model, moving average models, weighted moving average models, exponentially weighted moving average models, an exponential smoothing model, a regression model, an ARCH model, a GARCH model, a GJR-GARCH model, and an EGARCH model. We first use the standard (symmetric) loss functions to evaluate the performance of the competing models: the mean error, the mean absolute error, the root mean squared error, and the mean absolute percentage error. According to all of these standard loss functions, the exponential smoothing model provides superior forecasts of volatility. On the other hand, ARCH-based models generally prove to be the worst forecasting models. We also employ the asymmetric loss functions to penalize under/over-prediction. When under-predictions are penalized more heavily ARCH-type models provide the best forecasts while the random walk is worst. However, when over-predictions of volatility are penalized more heavily the exponential smoothing model performs best while the ARCH-type models are now universally found to be inferior forecasters.
THE FINE STRUCTURAL LOCALIZATION OF ACETYLCHOLINESTERASE AT THE MYONEURAL JUNCTION

A study of the cytochemical localization of acetylcholiriesterase activity, combining histochemistry with electron microscopy, showed that the final product of the reaction, which was deposited at or near enzyme sites, occurred at four places in the myoneural junction. These included: plasma membrane of the muscle covering the junctional folds, the primary and secondary synaptic clefts, parts of the plasma membrane covering the axon terminal, and vesicular structures in the terminal axoplasm. No reaction occurred in the presence of 10-4 eserine or DFP, whereas 10-5 DFP inhibited the reaction at all sites except in the vesicles of the terminal axon. These findings are discussed with reference to the histochemical method used and to the occurrence of esterolytic activity in the vesicles, as well as to some of the current hypotheses concerning the relationship of the site of acetylcholinesterase and synaptic transmission.
Multi-shell model of ion-induced nucleic acid condensation.

We present a semi-quantitative model of condensation of short nucleic acid (NA) duplexes induced by trivalent cobalt(iii) hexammine (CoHex) ions. The model is based on partitioning of bound counterion distribution around single NA duplex into "external" and "internal" ion binding shells distinguished by the proximity to duplex helical axis. In the aggregated phase the shells overlap, which leads to significantly increased attraction of CoHex ions in these overlaps with the neighboring duplexes. The duplex aggregationfree energy is decomposed into attractive and repulsive components in such a way that they can be represented by simple analytical expressions with parameters derived from molecular dynamic simulations and numerical solutions of Poisson equation. The attractive term depends on the fractions of bound ions in the overlapping shells and affinity of CoHex to the "external" shell of nearly neutralized duplex. The repulsive components of the free energy are duplex configurational entropy loss upon the aggregation and the electrostatic repulsion of the duplexes that remains after neutralization by bound CoHex ions. The estimates of the aggregationfree energy are consistent with the experimental range of NA duplex condensation propensities, including the unusually poor condensation of RNA structures and subtle sequence effects upon DNAcondensation. The model predicts that, in contrast to DNA, RNA duplexes may condense into tighter packed aggregates with a higher degree of duplex neutralization. An appreciable CoHex mediated RNA-RNA attraction requires closer inter-duplex separation to engage CoHex ions (bound mostly in the "internal" shell of RNA) into short-range attractive interactions. The model also predicts that longer NA fragments will condense more readily than shorter ones. The ability of this model to explain experimentally observed trends in NAcondensation lends support to proposed NAcondensation picture based on the multivalent "ion binding shells. "
Route-Split Routing with Resiliency to Simultaneous Failure for Mobile Ad Hoc Networks

As the performance of each node becomes higher, it is expected that the ad hoc network is used for the community network in which a few thousands of mobile nodes exist. In such a network, the number of hops between a source node and a destination node also becomes longer. However, as the route becomes longer, it is difficult to provide the robust and reliable route for mobile ad hoc networks since the multiple route breaks occur at the same time due to the topology change. Therefore, this paper proposes a route-split routing with resiliency to simultaneous failure (RSR). RSR sets up multiple subroute management nodes (SMN's) on the route and each SMN manages the subroute between the SMN and the neighboring SMN. When the multiple route breaks occur at the same time, each subroute is repaired by the SMN. Consequently, RSR can reduce the number of control packets used for the route repair and mitigate the network congestion even in case that the number of nodes in the network becomes very larger.
Cotransfer Learning Using Coupled Markov Chains with Restart

This article studies co-transfer learning, a machine learning strategy that uses labeled data to enhance the classification of different learning spaces simultaneously. The authors model the problem as a coupled Markov chain with restart. The transition probabilities in the coupled Markov chain can be constructed using the intra-relationships based on the affinity metric among instances in the same space, and the interrelationships based on co-occurrence information among instances from different spaces. The learning algorithm computes ranking of labels to indicate the importance of a set of labels to an instance by propagating the ranking score of labeled instances via the coupled Markov chain with restart. Experimental results on benchmark data (multiclass image-text and English-Spanish-French classification datasets) have shown that the learning algorithm is computationally efficient, and effective in learning across different spaces.
A bandwidth optimized SDRAM controller for the MORPHEUS reconfigurable architecture

High-end applications designed for the MORPHEUS computing platform require a massive amount of memory and memory throughput to fully demonstrate MORPHEUS's potential as a high-performance reconfigurable architecture. For example, a proposed film grain noise reduction application for high definition video, which is composed of multiple image processing tasks, requires enormous data rates due to its large input image size and real-time processing constraints. To meet these requirements and to eliminate external memory bottlenecks, a bandwidth- optimized DDR-SDRAM memory controller has been designed for use with the MORPHEUS platform and its Network On Chip interconnect. This paper describes the controller's design requirements and architecture, including the interface to the Network On Chip and the two-stage memory access scheduler, and presents relevant experiments and performance figures.
Preparation of Irinotecan-Loaded Folate-Targeted Liposome for Tumor Targeting Delivery and Its Antitumor Activity

The purpose of this study was to investigate the in vivo distribution and antitumor activity of irinotecan (camptothecin (CPT)-11)-loaded folate-targeted liposome (F-Lip) in tumor-bearing mice following i.v. administration. Folate–poly(ethylene glycol)–distearoylphosphatidylcholine (FA–PEG–DSPE) was synthesized by amide reaction of DSPE–PEG–NH2 and FA. F-Lip modified by FA–PEG–DSPE was prepared by an ammonium sulfate gradient. The mean particle size and entrapment efficiency of F-Lip with negative charge were 197.8 ± 4.58 nm and 91.39 ± 2.34 %, respectively. The distributions of CPT-11 and SN-38 in the tumor after i.v. administration of F-Lip, CPT-11-loaded liposomes (C-Lip), and CPT-11 injection (C-Inj) were far greater with the F-Lip group in comparison to the C-Inj and C-Lip, which might contribute to folate-meditated targeting uptake by the folate receptor on the surface of the tumor cells. The uptake of CPT-11 in the liver and rectum for two liposome groups were all markedly increased as compared to the C-Inj. Moreover, F-Lip exhibited a dose-dependent tumor growth inhibition and superior anticancer activity to C-Lip and C-Inj after i.v. administration. It also showed no significant body weight loss and much lower toxicity on the center immune organs. Therefore, F-Lip may be presented as potential candidates for tumor targeting drug delivery.
PR-SCTP for real time H.264/AVC video streaming

In this paper, we evaluate via real experiments the performance of the Stream Control Transmission Protocol (SCTP) and the Partial Reliability extension (PR-SCTP) for transmitting real-time H.264 video streaming over the Internet. This work looks into ways to apply the partial reliability services of PR-SCTP to exploit the implicit temporal scalability of P and B pictures in H.264/AVC video streams. We develop a simple probabilistic model that allow us to assign a limited number of retransmissions, using PR-SCTP, to each H.264/AVC frame type (e.g. I, P or B) before transmission. With our model we achieve a high probability of frame arrival at the receiver while at the same time keeping a low delay and bandwidth.
Vision-based autonomous navigation in indoor environments

The project presents robust vision-based navigation through doorways and hallways where static objects are present. A method is proposed using the fusion of colour features, edge map, motion analysis and stereo vision to help the system interpret visual cues. The system is able to detect ground plane, drop-offs, stairs and doorways, and is able to provide motion information of the camera. The results showing accurate distances to various detected indoor features, suggest that this proposed colour/edge/motion/depth approach would be useful as a navigation aid through doorways and hallways.
Can Enhanced Stock Price Informativeness Improve the Investment Efficiency of Chinese Listed Companies?

Although stock price informativeness has been posited to improve investment efficiency, there has been little empirical evidence supporting this claim to date. By the use of Chinese listed companies from 2002 to 2006 as the research sample, the effect of stock price informativeness on investment efficiency was empirically studied based on corporate level for the first time. The empirical results indicate: stock price informativeness is strongly negatively associated with both firm overinvestment and underinvestment. Further, stock price informativeness also can notably decrease the sensitivity of overinvestment to free cash flow and the sensitivity of underinvestment to financing constraints. It finally eliminates the possibility that the negative correlation is caused by the case that managers decrease stock price informativeness to conceal the investment losses.
Inequality: A Panel Data Analysis of Kuznets Curve on Western Europe (1995–2006)

Kuznets famous paper was referring to the early stages of industrialization where as countries become richer income inequality first rises and then falls. In the present paper examining Western European countries during the period 1995 – 2006 Kuznets curve has a different shape. This paper is a comment on the work of Glaeser (2005). Panel data are elaborated by means of Eviews software package.
Can Animal Spirits Solve The Forward Premium Puzzle

A DSGE two-country two-money model is fitted with Robust Control, inducing fear of model misspecification, or pessimism, in international households. The forward premium bias, produced from collapse in uncovered interest parity (UIP), is a direct function of pessimism. Under various regimes of pessimism, the forward premium estimator emulates both features of data and unbias UIP. JEL Classification Number: E32, F41, F43.
REAL-TIME SIMULATION OF SMOKE USING GRAPHICS HARDWARE

Based on earlier presented solvers for the incompressible Navier-Stokes equations, we implement a 3D fluid solver. The solver works in a few simple steps implemented in fragment shaders running entirely on theGraphic Processing Unit (GPU) of a modern graphics card. We present a simple visualization approach for rendering high-quality smoke animations in real-time. Finally, to handle interaction between fluid and stationary objects, we present a simple method for setting boundary conditions.
Function and evolution of plastid sigma factors

Chloroplasts are plant-specific organelles that perform photosynthesis and responsible for the world's primary productivity. Using light energy, chloroplasts produce many important products, including starch, amino acids, lipids, pigments and various secondary products. Therefore, chloroplasts are essential to the lives of all plants and animals alike. Chloroplast transformation is a unique technology to produce huge amount of valuable materials in chloroplasts using photosynthetic energy. In order to control chloroplasts at will, we need more information on molecular basis of chloroplast gene expression and communication between the chloroplast and nucleus. Chloroplast sigma factors are key regulators of the chloroplast gene expression and chloroplast differentiation. This review summarized recent findings on roles of chloroplast sigma factors in the chloroplast differentiation and environmental responses.