Miracle-dz/UniFAR-FTUs huggingface dataset:
Stabilization and privatization in Poland : an economic evaluation of the shock therapy program

Part One: Stabilization Program and Economic Recession. 1. Poland's Transition to Capitalism: Shock and Therapy. 2. Poland's Quest for Economic Stabilization, 1988-1991 - Interaction of Political Economy and Economics: B. Milanovic. 3. Taking Stock of the "Big Bang", K. Crane. Part Two: Foreign Trade Sector: Reform and Policies. 4. The CMEA Demise, Trade Restructuring, and Trade Destruction in Eastern Europe: Initial Assessment, D.K. Rosati. 5. The New East and Old Trade and Payment Problems, J.M. van Brabant. 6. Liberalizing Foreign Trade in a Socialist Economy: the Problem of Negative Value Added, R.I. McKinnon. Part Three: Privatization of State Capital Assets. 7. East European Transformation: the Supply Side W.W. Charemza. 8. Inflation Tax, Household Wealth, and Privatization in Poland: P.T. Gajdecka. 9. The Economic Transformation of Eastern Europe: the Case of Poland J Sachs. Part Four: Alternative Approaches to Economic Transition. 10. Evolutionary and Radical Approaches to Economic Reform, P. Murrell. 11. Transition to Market in a Comparative Perspective: an Historian's Point of View, J. Kochanowicz. 12. Is there a J-Curve for the Economic Transition from Socialism to Capitalism? , J.C. Brada, A.E. King.
PoS-tagging Italian texts with CORISTagger

This paper presents an evolution of CORISTagger [1], an high-performance PoS-tagger for Italian developed at the University of Bologna. The system is composed of a second-order Hidden Markov Model tagger followed by a Transformation Based tagger. The use of such a stacked structure, paired with a powerful morphological analyser based on a large lexicon composed of 120,000 lemmas, allowed the tagger to obtain good performances in the EVALITA 2009 PoS-tagging task. The performances of the tagger and the most common classification errors are discussed in detail.
Coordination via Interaction Constraints I: Local Logic

Wegner describes coordination as constrained interaction. We take this approach literally and define a coordination model based on interaction constraints and partial, iterative and interactive constraint satisfaction. Our model captures behaviour described in terms of synchronisation and data flow constraints, plus various modes of interaction with the outside world provided by external constraint symbols, on-the-fly constraint generation, and coordination variables. Underlying our approach is an engine performing (partial) constraint satisfaction of the sets of constraints. Our model extends previous work on three counts: firstly, a more advanced notion of external interaction is offered; secondly, our approach enables local satisfaction of constraints with appropriate partial solutions, avoiding global synchronisation over the entire constraints set; and, as a consequence, constraint satisfaction can finally occur concurrently, and multiple parts of a set of constraints can be solved and interact with the outside world in an asynchronous manner, unless synchronisation is required by the constraints. This paper describes the underlying logic, which enables a notion of local solution, and relates this logic to the more global approach of our previous work based on classical logic.
Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking

Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.
CorMASS: A Compact and Efficient Near‐Infrared Spectrograph for Studying Low‐Mass Objects

CorMASS (Cornell Massachusetts Slit Spectrograph) is a compact, low‐resolution (R∼300), double‐pass prism cross‐dispersed near‐infrared (NIR) spectrograph in operation on the Palomar Observatory 60 inch telescope. Its two‐dimensional spectral format provides simultaneous coverage of λ∼0.75 μm to λ∼2.5 μm (źJHK bands). A remotely operated cold flip mirror permits its NICMOS3 detector to function as a Ks slit viewer to assist object placement into the 2′′ × 15′′ slit. CorMASS was primarily designed for the rapid spectral classification of low‐mass stellar and substellar objects identified by the Two‐Micron All Sky Survey (2MASS). The efficiency and resolution of CorMASS also make it a versatile instrument for the spectral observation and classification of many other types of bright objects (K<14) including quasars, novae, and emission‐line objects.
Network Completion for Static Gene Expression Data

We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.
Agent interface enhancement: making multiagent graphical models accessible

Multiagent probabilistic reasoning with multiply sectioned Bayesian networks requires interfacing agent subnets (the modeling task) subject to a set of conditions. To specify the interfaces such that they are both valid and efficient is non-trivial. We present multiagent interface enhancement that relieves agent designers from the burden of model efficiency so that multiagent graphical models become more accessible.
Network-based identification of microRNAs as potential pharmacogenomic biomarkers for anticancer drugs

As the recent development of high-throughput technologies in cancer pharmacogenomics, there is an urgent need to develop new computational approaches for comprehensive identification of new pharmacogenomic biomarkers, such as microRNAs (miRNAs). In this study, a network-based framework, namely the SMiR-NBI model, was developed to prioritize miRNAs as potential biomarkers characterizing treatment responses of anticancer drugs on the basis of a heterogeneous network connecting drugs, miRNAs and genes. A high area under the receiver operating characteristic curve of 0.820 ± 0.013 was yielded during 10-fold cross validation. In addition, high performance was further validated in identifying new anticancer mechanism-of-action for natural products and non-steroidal anti-inflammatory drugs. Finally, the newly predicted miRNAs for tamoxifen and metformin were experimentally validated in MCF-7 and MDA-MB-231 breast cancer cell lines via qRT-PCR assays. High success rates of 60% and 65% were yielded for tamoxifen and metformin, respectively. Specifically, 11 oncomiRNAs (e.g. miR-20a-5p, miR-27a-3p, miR-29a-3p, and miR-146a-5p) from the top 20 predicted miRNAs were experimentally verified as new pharmacogenomic biomarkers for metformin in MCF-7 or MDA-MB-231 cell lines. In summary, the SMiR-NBI model would provide a powerful tool to identify potential pharmacogenomic biomarkers characterized by miRNAs in the emerging field of precision cancer medicine, which is available at http://lmmd.ecust. edu.cn/database/smir-nbi/.
Sublinear Algorithms for Earth Mover ' s Distance Khanh

We study the problem of estimating the Earth Mover's Distance (EMD) between probability distributions when given access only to samples. We give closeness testers and additive-error estimators over domains in [0, A], with sample complexities independent of domain size permitting the testability even of continuous distributions over infinite domains. Instead, our algorithms depend on other parameters, such as the diameter of the domain space, which may be significantly smaller. We also prove lower bounds showing our testers to be optimal in their dependence on these parameters. Additionally, we consider whether natural classes of distributions exist for which there are algorithms with better dependence on the dimension, and show that for highly clusterable data, this is indeed the case. Lastly, we consider a variant of the EMD, defined over tree metrics instead of the usual L 1 metric, and give optimal algorithms.
MVSS: Mobile Visual Search Based on Saliency

With development of content-based image retrieval (CBIR), mobile visual search (MVS) is a promising application. In typical MVS, similar images are retrieved from the database maintained by the server, given a query image taken by mobile devices. Different from general CBIR, the problem of transmission latency should be considered in MVS. In existing work, the progressive transmission is proposed to minimize the data size in transmission by low-dimensional feature descriptors and compression coding in order to reduce the transmission latency in MVS. Although the retrieval speed is improved by existing progressive transmission methods, the result accuracy is decreased because of the information loss in these methods. To address this problem, this paper proposes a novel framework for MVS which consists of a new progressive transmission model based on image saliency (MVSS) and a new distance metric corresponding to the proposed progressive transmission model. In our framework, we use SIFT descriptors to represent images, which can preserve more information than other low-dimensional feature descriptors and compression coding. Although SIFT is high-dimensional descriptor, we only transmit the SIFT descriptors in salient regions of image to reduce the transmission latency. We evaluate our framework on Stanford image set, and the results demonstrate that our framework not only reduces the transmission latency but also achieves a better retrieval accuracy.
Measurement of dissolved hydrogen concentration with clark electrode

Clark electrode is a well-known sensor for measuring concentration of dissolved oxygen in a water solution. This type of electrochemical sensor has an advantage of enabling detection of very low oxygen concentration. Although Clark electrode is typically used for measurement of dissolved oxygen, our research showed that the same electrodes can be successfully applied for measurement of other dissolved gases. We investigated a possibility of applying the same principle to dissolved hydrogen concentration measurement, and also the possibility of simultaneous measurement of both dissolved oxygen and hydrogen concentrations in the same water solution. We adapted Clark electrode sensor to measure dissolved hydrogen by choosing the appropriate polarization voltage level. We studied the influences on dissolved hydrogen measurement, such as choice of polarization voltage, temperature, salinity, and solution pH. We investigated the polarization voltage influence on sensor sensitivity and observed hysteresis in sensitivity that occurs with cyclic increase and decrease of polarization voltage. We proposed and described measurement setup that was used for experimental verification of proposed measurement method and sensor characteristics. The measurement results of sensor characteristics are presented, regarding the influences of polarization voltage, temperature dependence, salinity (fresh water and 380/00 NaCl solution) and pH value (6, 7, 8).
Funds of Knowledge: An Approach to Studying Latina(o) Students' Transition to College

A feature of the existing literature on minority students' transition to college is the preponderance of models that have “imagined” what students (and their families) need to have in order to be successful. In this paper we discuss how the theoretical framework of funds of knowledge can be used by researchers in higher education to challenge these models and to study Latina(o) students' college preparation, college access, and development of career aspirations.
An Investigation of High School Counseling Programs as a Reflection of a College-Going Culture

Title of Dissertation: AN INVESTIGATION OF HIGH SCHOOL COUNSELING PROGRAMS AS A REFLECTION OF A COLLEGE-GOING CULTURE Denise Park, Doctor of Philosophy, 2012 Dissertation directed by: Professor Courtland C. Lee Department of Counseling, Higher Education, and Special Education The purpose of this study is to investigate high school counseling programs as a reflection of a college-going culture. A qualitative thematic analysis is used to examine four school counseling programs at high schools in a school district located along the Eastern seaboard of the United States. In order to increase the likelihood of identifying aspects of school counseling programs that are successful in reflecting a college-going culture, only high schools with high college-going percentage rates were selected for this study. College-going culture theory, including the nine college-going culture principles, as proposed by McClafferty, McDonough, and Nunez (2002) is used as a framework for this study. The college-going culture principles operate as themes to help categorize school counselor activities and measure whether the school counseling programs reflect a college-going culture in the schools. A methodological triangulation is employed to
An Improved Algorithm to Generate High Quality Progressive Animation Models

In computer graphics, investigation has been made in many years in progressive models generation to alleviate the workload of visualization processing. However, most of the existing algorithms only focus on static meshes, and very little works are to deal with animation models. In this paper, we propose an improved method for generating progressive multiresolution animation models. By the method we first use a normal deviation parameter to improve the famous QEM method as our basic edge contraction metric to generate a base hierarchy. The sequence of the simplified models is generated progressively from the first frame to the last one. Based on the edge contraction sequence in the previous frame, the contraction order in the current frame is adjusted according to the deformation degree. We demonstrate that our method works efficiently and can generate better approximations with well-preserved features than previous methods.
Robust recognition of traffic signals

In this paper a general system for real-time detection and recognition of traffic signals is proposed. The key sensor is a camera installed in a moving vehicle. The software system consists of three main modules: detection, tracking, and sample-based classification. Additional sensor information, such as vehicle data, GPS, and enhanced digital maps, or a second camera for stereo vision, are used to enhance the performance and robustness of the system. Since the detection step is the most critical one, different detection schemes are compared. They are based on color, shape, texture and complete-object classification. The color system, with a high dynamic range camera and precise location information of the vehicle and the searched traffic signals, offers valuable and reliable help in directing the driver's attention to traffic signals and, thus, can reduce red-light running accidents.
The impact of rate heterogeneity on inference of phylogenetic models of trait evolution

Rates of trait evolution are known to vary across phylogenies; however, standard evolutionary models assume a homogeneous process of trait change. These simple methods are widely applied in small‐scale phylogenetic studies, whereas models of rate heterogeneity are not, so the prevalence and patterns of potential rate variation in groups up to hundreds of species remain unclear. The extent to which trait evolution is modelled accurately on a given phylogeny is also largely unknown because studies typically lack absolute model fit tests. We investigated these issues by applying both rate‐static and variable‐rates methods on (i) body mass data for 88 avian clades of 10–318 species, and (ii) data simulated under a range of rate‐heterogeneity scenarios. Our results show that rate heterogeneity is present across small‐scaled avian clades, and consequently applying only standard single‐process models prompts inaccurate inferences about the generating evolutionary process. Specifically, these approaches underestimate rate variation, and systematically mislabel temporal trends in trait evolution. Conversely, variable‐rates approaches have superior relative fit (they are the best model) and absolute fit (they describe the data well). We show that rate changes such as single internal branch variations, rate decreases and early bursts are hard to detect, even by variable‐rates models. We also use recently developed absolute adequacy tests to highlight misleading conclusions based on relative fit alone (e.g. a consistent preference for constrained evolution when isolated terminal branch rate increases are present). This work highlights the potential for robust inferences about trait evolution when fitting flexible models in conjunction with tests for absolute model fit.
Downside Risk of Derivative Portfolios With Mean-Reverting Underlyings

We carry out a Monte-Carlo simulation of a standard portfolio management strategy involving derivatives, to estimate the sensitivity of its downside risk to a change of mean-reversion of the underlyings. We find that the higher the intensity of mean-reversion, the lower the probability of reaching a pre-determined loss level. This phenomenon appears of large statistical significance for large enough loss levels. We also find that the higher the mean-reversion intensity of the underlyings, the longer the expected time to reach those loss levels. The simulations suggest that selecting underlyings with high mean-reversion effect is a natural way to reduce the downside risk of those widely traded assets.
An Energy Efficient Strong Head Clustering Algorithm for Wireless Sensor Networks

Clustering algorithms are frequently used for wireless sensor networks with the increasing network capacity now. In this paper, we proposed an energy efficient strong head clustering algorithm (EESH) to improve the performance for prolonging the network lifetime. In the algorithm, cluster head election depends on strong nodes not only with more energy, but also with large costs determined by neighbors. Nodes with more amounts of nodes nearby, with weaker energy and shorter distance neighbors may get more opportunities to become cluster heads. By means of head election, strong nodes can contribute more as cluster heads, while energy consumption of weak nodes can be decreased accordingly. The simulation results show that EESH can prolong the network lifetime, and reducing the network usage rate dropping at early stage.
Four New Chloro-Eremophilane Sesquiterpenes from an Antarctic Deep-Sea Derived Fungus, Penicillium sp. PR19N-1

A new chloro-trinoreremophilane sesquiterpene 1, three new chlorinated eremophilane sesquiterpenes 2–4, together with a known compound, eremofortine C (5), were isolated from an Antarctic deep-sea derived fungus, Penicillium sp. PR19N-1. Structures were established using IR, HRMS, 1D and 2D NMR techniques. In addition, the plausible metabolic network of these isolated products is proposed. Compound 1 showed moderate cytotoxic activity against HL-60 and A549 cancer cell lines.
Work motivation : models for developing countries

Foreword - Pradip N Khandwalla Introduction - Rabindra N Kanungo and Manuel Mendonca Motivational Models for Developing Societies PART ONE: UNDERSTANDING MOTIVATION AT THE INDIVIDUAL LEVEL Bases of Work Motivation in Developing Societies - Sasi Misra and Rabindra N Kanungo A Framework for Performance Management Motivation Through Effective Reward Management in Developing Countries - Manuel Mendonca and Rabindra N Kanungo Designing Work in Developing Countries - Sanjay T Menon The PI Motive - Pradip N Khandwalla A Resource for Socio-Economic Transformation of Developing Societies Middle Management Motivation - S Ramnarayan A State of Choked Potential PART TWO: UNDERSTANDING MOTIVATION AT THE ORGANIZATIONAL LEVEL Empowering the People for Social Achievement - Prayag Mehta Motivation Through Participative Management - Manuel Mendonca and Rabindra N Kanungo Power Dynamics in Indian Organizations - Jai B P Sinha Management Education and Work Motivation in Developing Societies - Nidhi Srinivas Looking in, Looking Out Organization Development - Kalburgi M Srinivas Maya or Moksha Conclusion - Manuel Mendonca and Rabindra N Kanungo The Issue of Culture Fit
Fiber delivery of femtosecond pulses from a Ti:sapphire laser.

We propose a way to deliver nanojoule-energy, 100-fs pulses at 800 nm through a few meters of standard optical fiber. Pulses from a mode-locked laser are compressed temporally, and then spectrally, to produce the desired pulses at the end of the fiber. Initial experiments agree well with calculations and demonstrate the benefits of this technique: For an energy of ~0.5 nJ , the delivered pulses are ~5 times shorter than those delivered by other techniques. The issues that must be addressed to scale the technique up to delivered pulse energies of 5 nJ are identified, and the apparatus employs only readily available components. Thus we expect it to find use in the many applications that would benefit from fiber delivery of femtosecond pulses.
Correlating Process Corners and Temperature in Deep Nano-scale CMOS

Simulating variations pre-Si can be very time consuming. Running enough Monte Carlo simulations at the five process corners takes a non-trivial amount of time, particularly for larger designs. This paper describes a method for decreasing time for simulating process variations by reducing the number of required simulations. Through noise-analysis and Monte Carlo simulations conducted in commercial 28nm Fully Depleted Silicon On Insulator (FDSOI), we demonstrate that this method results in a reduction as large as one half in simulation time, depending on the size and type of circuit. Keywords—process compensation; process corners; manufacturing process variability; temperature compensation; subthreshold; 28 nm FDSOI; nano-scale CMOS