Miracle-dz/UniFAR-FTUs huggingface dataset:
Study the role and simultaneous effects of the type of ownership on efficiency and value of the listed companies in Tehran Stock Exchange

In the present study, the role and separate and simultaneous effects of concentration and type of ownership on two factors; efficiency and value of the listed companies in Tehran Sock Exchange have been studied. The statistical sample of the research includes 70 companies during the period of 2003 to 2009. In this research in order to study the effect of each given factor on the efficiency and value of the companies, two methods have been applied; static panel data and dynamic panel data. The research findings indicate a significant linear relationship between the two factors of ownership concentration and the companies’ efficiency with lack of significant relationship between concentrated ownership and companies’ value. On the other hand the results related to the test of the effects of the ownership type shows that unlike the reverse relation between stock returns and ratio of state ownership, there is a direct and significant relation between ratio of individual, corporate and private ownership with efficiency. However the variable of ownership concentration in all the models had a linear and direct relation with stock returns. The test of the relation between types of ownership with company value also indicated the same results as was expressed for the efficiency. [panahi E, panahi S, Eghbali Amoghin A, Gholami,A. Study the role and simultaneous effects of the type of ownership on efficiency and value of the listed companies in Tehran Stock Exchange. Life Sci J 2013; 10(4s): 276-284] (ISSN: 1097-8135). http:www.lifesciencesite. com.41
Clues on pulsar characteristics from cosmic-ray and gravitational wave observations

Recent positron and high-energy cosmic-ray observations allow us to set limits on pulsar birthrate and initial periods. The initial period of pulsars is one of the most important parameters affecting circumpulsar disk formation. We show that pulsar parameters inferred from cosmic-ray measurements are consistent with the possibility that a large sample of galactic pulsars is surrounded by disks. Finally, in case of circumpulsar disk precession, we study the emission of gravitational waves and their possible detection with future space interferometers.
Development of earthquake scenarios for use in earthquake risk analysis for lifeline systems

In the most common probabilistic approach to multi-site seismic risk assessment, system response (losses, downtime, etc.) are computed for a comprehensive set of earthquake simulations (or scenarios), referred to here as an ‘event set’, to account for the potential risks from earthquakes in a region. Detailed models of large lifeline systems are often quite complex, so it may not be practical (or even possible) to analyze the system in detail for an exhaustive set of earthquake scenarios. This paper presents an improved methodology based on Chang et al. (2000) that better incorporates the ground motion uncertainty in the process of selecting a reduced set of hazard-consistent scenarios, and demonstrates its application to the Los Angeles Department of Water and Power network systems.
A Content-Analysis Approach for Exploring Usability Problems in a Collaborative Virtual Environment 

: As Virtual Reality (VR) products are becoming more widely available in the consumer market, improving the usability of these devices and environments is crucial. In this paper, we are going to introduce a framework for the usability evaluation of collaborative 3D virtual environments based on a large-scale usability study of a mixed-modality collaborative VR system. We first review previous literature about important usability issues related to collaborative 3D virtual environments, supplemented with our research in which we conducted 122 interviews after participants solved a collaborative virtual reality task. Then, building on the literature review and our results, we extend previous usability frameworks. We identified twelve different usability problems, and based on the causes of the problems, we grouped them into three main categories: VR environment, device interaction, and task-specific problems. The framework can be used to guide the usability evaluation of collaborative VR environments.
Tunable BW/Gain Circuit Design of Four-Channel Bio-Signal Acquisition

Due to properties of low-amplitude and non-stationary, most of biomedical signals are easily influenced by examined persons, measured environment, and electronic devices. A novel analog circuit design is proposed in this thesis, which is suitable for various biomedical signal acquisitions. In addition to the consideration of low power and low noise, the multi-channel analog front-end integrated circuit (AFEIC) is designed with high common-mode rejection ratio (CMRR) and high power supply ratio (PSRR). This circuit is realized into a single chip without any external component. It can not only reduce the number of outer components, but also enhance a better signal-to-noise ratio enormously. In addition, to select system gain and bandwidth corresponding to different amplitude and frequency of biomedical signals, the controllable digital interface was also designed and integrated into AFEIC. In this thesis, AFEIC design is composed of four current-balancing instrumentation amplifiers (CBIA), one analog multiplexer, one switched-capacitor low-pass filter (SCLPF), one non-overlapping clock generator, and one programmable gain amplifier (PGA). These circuits have been integrated into a single chip of the total area of 0.823×0.953mm by using TSMC 0. 18μm COMS Mixed-Signal RF General purpose MiM Al 1P6M 1.8&3.3V process. For the simulation results, the proposed chip can achieve 135dB of CMRR, 105dB of PSRR+, and 112dB of PSRRat 50Hz. The total power consumption is about 112. 68μW under ±0.75V supply, and the power consumption is about 28. 17μW per channel. Keyword: Biomedical signal, electroencephalogram (EEG), current-balancing instrumentation amplifier (CBIA), switched-capacitor low-pass filter (SCLPF), programmable gain amplifier (PGA).
The Economic Drivers and Environmental Outcomes of the Clean Development Mechanism in Vietnam

The Clean Development Mechanism (CDM) is the principal source of carbon offsets in the global market, and is intended to be a key driver of sustainable development and technical transformation in developing countries. The distribution of CDM projects by country has been skewed, with over 75% of registered projects having taken place in just four countries, namely China, India, Brazil and Mexico. A change in this pattern of development may be occurring, however, as smaller developing countries become increasingly active in the carbon market. An example of this is the rapid rise in the number of CDM projects based in Vietnam since early 2009. This paper investigates factors contributing to the growth of CDM projects in Vietnam and describes some of the key features of the projects that have been developed. Hydropower projects are found to dominate new CDM project development in Vietnam. It is suggested that CDM project development in Vietnam may be a tool to support domestic energy security rather than being primarily driven by the intended climate change mitigation and sustainable development objectives of the CDM. It is also possible that Vietnam is emulating the development strategy of China, and may serve as a model for other members of the Least Developed Countries group. A country’s domestic policy choices are critical in determining its attractiveness as a host country for offset projects, and Vietnam’s policy strategies are successfully harnessing synergies between domestic agendas and regulated foreign markets.
ANALYSIS OF VIBRATIONS IN INDUCTION MOTORS USING MACHINE LEARNING

The classical multiple signal classification method has been widely used in induction machine fault detection and diagnosis. This method can extract meaningful frequencies but cannot give accurate amplitude information of fault harmonics. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses in prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning. Machine learning can also be unsupervised and be used to learn and establish baseline behavioral profiles for various entities and then used to find meaningful anomalies. Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data. In this work, the integration of machine learning for the predictive analysis of health in induction motors is proposed so that the overall effectiveness of the system can be escalated.
DETECTION OF LOCAL WEATHER EVENTS FROM MULTIWAVELENGTH LIDAR MEASUREMENTS DURING THE EARLI 09 CAMPAIGN

This paper aims to show the capability of lidar systems to detect atmospheric phenomena taking place within the Planetary Boundary Layer (PBL) and the Free Troposphere (FT). Usually, lidar systems can measure a variety of atmospheric parameters including aerosols optical and geometrical properties, temperature and wind velocity. Moreover, the Mixing Layer Height (MLH), cloud heights, mineral dust and other aerosols layers can be determined from lidar measurements. The Bucharest Multiwavelength Raman Lidar (RALI) performed measurements during the EArlinet Reference LIdars campaign 2009 – EARLI09. The campaign was organized at the Institute for Tropospheric Physics, in Leipzig, Germany, from May 4 to May 29, 2009. One interesting local atmospheric phenomenon related to a frontal passage was observed on RALI Range Corrected Signal (RCS) from 26 of May 2009. This phenomenon was also confirmed by meteorological observations. Combining Lidar observations with models, we were able to evidence, with a high confidence level, a dust intrusion event and a local extreme weather phenomenon.
SIMULATION OF DYNAMIC RESPONSE OF SATURATED SANDS USING MODIFIED DSC MODEL

A modified disturbed state concept (DSC) model to simulate the dynamic behavior of saturated sands was proposed in this paper. Laboratory dynamic tests were performed to verify the modified DSC model. Based on the test results, it is concluded that the modified DSC model simulates reasonably well dynamic responses of saturated sands including excess pore water pressure, stress degradation, initial liquefaction occurrence, and post-liquefaction behavior. A numerical back-predict program based on the incremental solution of the modified DSC model was also developed.
A GaN HEMT Class AB RF Power Amplifier

In this article, an RF power amplifier which has a crucial importance for RF transceivers is designed and implemented. The main aim of the design is making the power amplifier linear at the center frequency 1.8 GHz. Linearity was measured with two tone test and according to the result of the test, the Carrier-to-Intermodulation (C/I) ratio should have been above 30 dB and two fundamental carriers with the 5 MHz space should be at least 1.25 Watt. Also, efficiency was tried to be kept as high as possible. Considering the three issues; linearity, output power and efficiency; the circuit was biased to the conditions of deep class AB. GaN transistor which has been very popular in recent years was used as an active device. The simulations and the layout of the circuit were all done with AWR Microwave Office. Taconic TSM30 600 was used as a substratum in the circuit. After the circuit was implemented, the measurements results were compared to simulations. Keywords-component; formatting; RF Power Amplifier, Linearity, GaN HEMT.
PARALLELRENDERING FOR EFERENCE

In computer graphics, rendering is the process by which an abstract description of a scene is converted to an image. When the scene is complex, or when high-quality images or high frame rates are required, the rendering process becomes computationally demanding. To provide the necessary levels of performance, parallel computing techniques must be brought to bear. Although parallelism has been exploited in computer graphics since the early days of the field, its initial use was primarily in specialized applications. The VLSI revolution of the late 1970's and the advent of scalable parallel computers during the late 1980's changed this situation. Today, parallel hardware is routinely used in graphics workstations, and numerous software-based rendering systems have been developed for general-purpose parallel architectures. This article provides a broad introduction to the subject of parallel rendering, encompassing both hardware and software systems. The focus is on the underlying concepts and the issues which arise in the design of parallel rendering algorithms and systems. We examine the different types of parallelism and how they can be applied in rendering applications. Concepts from parallel computing, such as data decomposition, task granularity, scalability, and load balancing, are considered in relation to the rendering problem. We also explore concepts from computer graphics, such as coherence and projection, which have a significant impact on the structure of parallel rendering algorithms. Our survey covers a number of practical considerations as well, including the choice of architectural platform, communication and memory requirements, and the problem of image assembly and display. We illustrate the discussion with numerous examples from the parallel rendering literature, representing most of the principal rendering methods currently used in computer graphics. This work was supported in part by the National Aeronautics and Space Administration under Contract No. NAS1-19480 while the author was in residence at the Institute for Computer Applications in Science and Engineering (ICASE), M/S 132C, NASA Langley Research Center, Hampton, VA 23681-0001. E-mail: tom@icase.edu Worm Wide Web: http://www.icase.edu/-tom/
Theoretical perspectives on the outsourcing of information systems

Critics have argued that the field of information systems (IS) lacks a coherent theoretical framework. This paper attempts to further the theoretical development of a critical and pervasive contemporary phenomenon, outsourcing of IS functions, by synthesizing four theoretical models (resource-based theory, resource-dependence theory, transaction cost theory and agency theory) that are useful for understanding determinants of a firm's outsourcing strategy. From these theoretical models, a contingency model of outsourcing is developed which can be used to direct empirical research.
A Route Guidance Model Based on System Optimality Level and Deterministic Route Choice Behavior

Abstract: Traffic networks around the world, especially in densely populated areas, have experienced a growing rise in commuting time due to increasing levels of traffic. The increased congestion seen in many major cities represents a serious problem for roadway operators and commuters every day. Transportation authorities are looking for new traffic management techniques to better manage traffic and reduce congestion, delay and long queues in urban networks. To this end, a route guidance system that is a part of intelligent transportation systems would provide travelers with information on the best route to their destinations.
On-line Process Data-driven Diagnostics Using Statistical Techniques

Intelligent monitoring and diagnosis of production processes based on multivariate statistical methods has been one of important tasks for safety and quality issues. This is due to the fact that faults and unexpected events may have serious impacts on the operation of processes. This study proposes a diagnostic scheme based on effective representation of process measurement data and is evaluated using simulation process data. The effects of utilizing a preprocessing step and nonlinear statistical methods are also tested using fifteen faults of the simulation process. Results show that the proposed scheme produced more reliable results and outperformed other tested schemes with none of the filtering step and nonlinear methods. The proposed scheme is expected to be robust to process noises and easy to develop due to the lack of required rigorous mathematical process models or expert knowledge. 요 약 생산 공정의 다변량 데이터에 기반한 지능적 공정 감시 및 진단 시스템은 조업의 안정성과 고품질의 제품을 달성하고 경쟁력을 유지하기 위해서는 필수적인 업무 중 하나로 간주되고 있는데, 이와 같은 추세는 공정 이상이 발생하는 경우 안정 적이고 경제적인 조업에 큰 영향을 미치는 것에 기인한다. 본 연구에서는 다변량 공정 데이터에 기반한 진단기법을 제시하고 이를 시뮬레이션 공정 데이터를 활용하여 그 성능을 평가하고자 한다. 또한 원 데이터의 전처리 과정의 유무와 비선형 방법 론의 활용이 진단 성능에 마치는 영향을 시뮬레이션 공정에서 제시된 15개의 공정 이상에 대해 평가하였다. 그 결과 제안된 방법론이 신뢰할 만한 결과를 주었으며 다른 비교 방법론인 전처리 과정이 없거나 선형 방법론을 사용한 타 방법론 대비 우월한 성능을 보여주었다. 제시된 방법론은 공정 데이터에 기반한 방법론으로서 공정에 대한 수학적 모델이나 지식 모델에 비하여 상대적으로 모델링이 간편하며 공정 데이터의 잡음에 강건하다는 장점을 가진다.
A Cross Level Research on Doctor Professional Competence , Patient Trust and Satisfaction

After the establishment of the national health insurance (NHI) in Taiwan, the ecology of the medical care industry significantly changes in many ways, such as patients’ easy access to hospitals, and their decreased payables for medical treatments through the NHI payments, as well as their attention of patient rights. All the above shifts cause patients’ increasing quarrels with doctors against medical treatments. Consequently, the doctor-patient relationship becomes a critical issue. Inspired by many researches focusing on the effect of customer trust on satisfaction, we propose a cross level framework to test the relationship between doctor professional competence and patient satisfaction with trust serving as a mediator. Our findings indicate that a complete mediation effect exists, implying that doctor competence indirectly affect patient satisfaction through trust. It is therefore suggested that a doctor attempting to promote patient satisfaction should not only learn and demonstrate more professional skills, but also build patient trust by treating patients carefully and affectionately _____________________________________________________________________
A novel mode of DNA recognition by a β‐sheet revealed by the solution structure of the GCC‐box binding domain in complex with DNA

The 3D solution structure of the GCC‐box binding domain of a protein from Arabidopsis thaliana in complex with its target DNA fragment has been determined by heteronuclear multidimensional NMR in combination with simulated annealing and restrained molecular dynamic calculation. The domain consists of a three‐stranded anti‐parallel β‐sheet and an α‐helix packed approximately parallel to the β‐sheet. Arginine and tryptophan residues in the β‐sheet are identified to contact eight of the nine consecutive base pairs in the major groove, and at the same time bind to the sugar phosphate backbones. The target DNA bends slightly at the central CG step, thereby allowing the DNA to follow the curvature of the β‐sheet.
Jasmonate – a blooming decade

The plant hormone jasmonate not only helps plants to defend against necrotrophic fungi and insect attacks, but also regulates many growth and developmental events. The landmark breakthrough in research in this field was the identification of JAZ proteins in 2007, providing the long-sought central signalling molecules bridging perception to downstream transcriptional regulation. Recognizing 10 years of research on JAZ proteins, the reviews in this special issue celebrate what we have learnt, interpret recent discoveries, and provide stimulating new perspectives.
A way-halting cache for low-energy high-performance systems

Caches contribute to much of a microprocessor system's power and energy consumption. We have developed a new cache architecture, called a way-halting cache, that reduces energy while imposing no performance overhead. Our way-halting cache is a four-way set-associative cache that stores the four lowest-order bits of all ways' tags into a fully associative memory, which we call the halt tag array. The look-up in the hall tag array is done in parallel with, and is no slower than, the set-index decoding. The hall tag array pre-determines which tags cannot match due to their low-order four bits mismatching. Further accesses to ways with known mismatching tags are then halted, thus saving power. Our halt tag array has an additional feature of using static logic only, rather than dynamic logic used in highly associative caches. We provide data from experiments on 17 benchmarks drawn from MediaBench and Spec 2000, based on our layouts in 0.18 micron CMOS technology, On average, 55% savings of memory-access related energy were obtained over a conventional four-way set-associative cache. We show that energy savings are greater than previous methods, and nearly twice that of highly-associative caches, while imposing no performance overhead and only 2% cache area overhead.
Metacognitive training for schizophrenia patients (MCT): A pilot study on feasibility, treatment adherence, and subjective efficacy

Objectives: A plethora of studies has confirmed that several cognitive biases (e.g., attributional style, jumping to conclusions, bias against disconfirmatory evidence, theory of mind, over-confidence in errors, need for closure, and low selfesteem) may play a pathogenetic role in the emergence and/or maintenance of the disorder, particularly delusions. The present study explored the safety, acceptance and subjective efficacy of a newly developed intervention program aimed at increasing awareness of, and possibly ameliorating, cognitive and behavioural biases in schizophrenia. Metacognitive training (MCT) builds upon inferences drawn from basic research on cognition and metacognition in schizophrenia. Methods: Forty outpatients were randomized to MCT and a control intervention (cognitive remediation, CogPack). Treatment in either group was performed twice weekly for an entire duration of 4 weeks (i.e., 8 sessions each lasting 45-60 minutes). At the end of the training, participants were asked to evaluate the subjective utility and efficacy of the program. In addition, treatment adherence and adverse events were documented. Results: MCT yielded superior scores relative to CogPack on several subjective parameters. Treatment adherence was comparable and no adverse events were noted during either intervention. Conclusions: The present study underscores the feasibility and acceptance of metacognitive training in psychosis. Future trials are warranted to verify the impact of MCT on the amelioration of metacognition assumed to exert a positive influence on symptomatology (German J Psychiatry 2007; 10: 69–78).
Frequency peak features for low-channel classification in motor imagery paradigms

The expansion of brain-computer interfaces (BCIs) to outside the research laboratory has historically been hampered by their difficulty of use. Well-functioning BCIs often require many channels, which can be difficult to properly prepare and require expert support. Low-channel setups, however, can lead to poor or unreliable classification of intent. Here we introduce a novel method for extracting more information from a single EEG channel and test it on a ten subject motor imagery dataset. Instead of looking at bandpower or phase synchrony, we test the average frequency within each trial to see if there are task-dependent changes in the spectral locations of neural frequency peaks. We show that using this feature in combination with standard bandpower features is significantly better than bandpower features alone across subjects, both for standard electrodes and electrodes that include a Laplacian filter.