Miracle-dz/UniFAR-FTUs huggingface dataset:
Induction motor stator current spectral content under sinusoidal and PWM excitation

The use of converters to feed motors instead of the direct-on-line supply has increased the need to understand the behaviour of the induction machine in different operating points. The additional losses in frequency converter fed machines are caused by the harmonic content of a PWM voltage excitation. This paper investigates closely the harmonic contents of stator supply voltage and current. Most of the earlier studies have focused on sinusoidal supply or converter supply in only a few specific load points while this study covers most of the frequency-torque plane below nominal values. A 15 kW standard squirrel-cage machine's stator current and voltage time functions and spectra are analysed in 16 different operating points with torque values of 25 %, 50 %, 75 % and 100 % of the motor's rated torque and supply frequency values of 25 %, 50 %, 75 % and 100 % of the motor's rated frequency. Measurements in all 16 operating points are performed with both sinusoidal generator supply and with a frequency converter supply.
Ultrathin CVD Cu Seed Layer Formation Using Copper Oxynitride Deposition and Room Temperature Remote Hydrogen Plasma Reduction

Cu seed layers for future interconnects must have conformal step coverage, smooth surface morphology, and strong adhesion. Conformal deposition had been achieved by chemical vapor deposition CVD, but CVD Cu films have rough surfaces and poor adhesion. In this paper, conformal, smooth, adherent, continuous, and thin 9n m Cu films were made by CVD. CuON was deposited from a Cu-amidinate precursor, H2O, and NH3 at 140‐180°C on Ru. Crystallites in the deposited film have either a Cu2 Oo r Cu3N structure depending on the ratio of H2 Ot o NH3. As-deposited CuON films have a smooth surface morphology 0.5 nm root-mean-square rms roughness and are highly conformal 95% step coverage in 40:1 aspect ratio holes . T he CuON films were then reduced with remote hydrogen plasma near room temperature to minimize agglomeration of the thin Cu films during reduction. After reduction, CuON films having a Cu2O crystal structure showed a higher density Cu film 95% than those having a Cu3N crystal structure 84%. Both reduced Cu films had a smooth morphology 1 nm rms roughness. Thus, deposition of a CuON film having a Cu2O crystal structure and then reduction with remote hydrogen plasma can make Cu layers that can serve as seed layers of future Cu interconnects.
Intergenerational Income Mobility in Sweden: What Do Tax-Data Show?

The aim of this paper is to investigate intergenerational income mobility in Sweden by means of a representative sample drawn from tax-data files. Longitudinal data on actual parent-child pairs spanning 1978-92 are employed. Regression and correlation coefficients are analyzed and transition matrices calculated in order to investigate income mobility over generations. The results achieved show high intergenerational income mobility in Sweden between fathers and sons in comparison to estimations performed in most other countries and more especially compared to the U.S. This indicates that Sweden does not only have lower cross-sectional income inequality, but also higher intergenerational income mobility than those countries. The mother's earnings influence children's earnings less than the father's. However, the mother's earnings correlate more strongly with a daughter's earnings than they do with that of a son. The major indication of immobility across generations is found in the upper income deciles. Copyright 2000 by The International Association for Research in Income and Wealth.
Recommendations, Rhetoric, and Reporting: State and NGO Behavior in the Universal Periodic Review of Human Rights

This dissertation takes a detailed look at the role of non-state “stakeholders,” overwhelmingly civil society non-governmental organizations (CSOs or NGOs), in human rights promotion within the process of the United Nations Human Rights Council’s Universal Periodic Review of Human Rights. Utilizing a mixed-method, text-heavy approach, I conduct analyses of both state behavior and NGO activity within the first cycle of the Universal Periodic Review of Human Rights and examine the monitoring and follow-up practices between review rounds through paired cases in the second round of reviews. In these analyses, first I show that NGO activity, after controlling for the amount of state activity, human rights record, region, and issue area, is related to higher rates of states rejecting recommended changes and thus the exhibition of resistance to international pressure. Second, state rejection of recommendations increases with the level of demands in the recommendation, worsening human rights records, and when the recommendation covers specific international obligations or political rights such as basic freedoms and the rule of law. Moreover, recommendations covering women’s rights or the rights of the child are more likely to be accepted. Third, I establish that states express their resistance to international human rights norms in one of two fashions: with culturally-, religiously-, or nationally-particularistic claims or with appeals to state sovereignty. Finally, I highlight the centrality of NGOs in the monitoring process between cycles of the UPR process, tying NGO engagement and participation over the duration to reporting on compliance with recommended changes from the preceding cycle of review. Recommendations, Rhetoric, and Reporting: State and NGO Behavior in the Universal Periodic Review of Human Rights by Michael J. Beckstrand B.A., St. John’s University, 2007 M.A., Syracuse University, 2009 DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Political Science in the Graduate School of Syracuse University Syracuse University August 2015 Copyright © Michael J. Beckstrand 2015 All Rights Reserved
An optimal tableau for Right Propositional Neighborhood Logic over Trees

Propositional interval temporal logics come into play in many areas of artificial intelligence and computer science. Unfortunately, most of them turned out to be (highly) undecidable. Some positive exceptions, belonging to the classes of neighborhood logics and of logics of subinterval relations, have been recently identified. In this paper, we address the decision problem for the future fragment of Propositional Neighborhood Logic (Right Propositional Neighborhood Logic) interpreted over trees and we positively solve it by providing a tableau-based decision procedure that works in exponential space. Moreover, we prove that the decision problem for the logic is EXPSPACE-hard, thus showing the optimality of the proposed procedure.
Marked Variation of the Association of ESRD Duration Before and After Wait Listing on Kidney Transplant Outcomes

Numerous studies report a strong association between pretransplant end‐stage renal disease (ESRD) duration and diminished transplant outcomes. However, cumulative waiting time may reflect distinct phases and processes related to patients’ physiological condition as well as pre‐existing morbidity and access to care. The relative impact of pre‐ and postlisting ESRD durations on transplant outcomes is unknown. We examined the impact of these intervals from a national cohort of kidney transplant recipients from 1999 to 2008 (n = 112 249). Primary factors explaining prelisting ESRD duration were insurance and race, while primary factors explaining postlisting ESRD duration were blood type, PRA% and variation between centers. Extended time from ESRD to waitlisting had significant dose–response association with overall graft loss (AHR = 1.26 for deceased donors [DD], AHR = 1.32 for living donors [LD], p values < 0.001). Contrarily, time from waitlisting (after ESRD) to transplantation had negligible effects (p = 0.10[DD], p = 0.57[LD]). There were significant associations between pre‐ and postlisting ESRD time with posttransplant patient survival, however prelisting time had over sixfold greater effect. Prelisting ESRD time predominately explains the association of waiting time with transplant outcomes suggesting that factors associated with this interval should be prioritized for interventions and allocation policy. The degree to which the effect of prelisting ESRD time is a proxy for comorbid conditions, socioeconomic status or access to care requires further study.
Verifying abstract data types a hybrid approach

At a time when software products are taking on increasingly critical functions, and are growing increasingly large and complex, the need to ensure their quality also increases significantly. Yet, despite several decades of research, the verification of software products of industrial size and complexity remains an unfulfilled challenge. In this paper, we discuss a hybrid approach to the verification of abstract data types against axiomatic specifications, which consists in deploying static techniques and dynamic techniques in a complementary manner, avoiding the drawbacks of each technique used in isolation.
Fault Diagnosis of Regenerative Water Heater Based-On Multi-class Support Vector Machines

The main idea of multi-class support vector machines (SVMs) is described. a multi-class model for regenerative water heater fault diagnosis is presented combining the fuzzy logic and SVMs. The typical faults set of regenerative water heater is built after thoroughly analyzing the relationships between performance parameters and faults. Finally, the model is inspected and verified by an example in a regenerative water heater of the turbine unit, the result of diagnosis shows that it is simple and practical; it can identify the regenerative water heater faults effectively.
A New Approach about Earnings Management and Audit Companies: Empirical Evidences from Brazilian Capital Market

The aim of this study was to evaluate whether the discretionary accruals of Brazilian public companies would reveal changes as a result of the big four firm that audits them, and whether the companies served by firms of less importance in the sector would denote different behaviors in comparison to those contracting the largest four. For this purpose was formed a sample with 7,875 observations originating from 44 quarters from the period of 1998 to 2009, emphasizing the non-inclusion of the other years due to the Brazilian IFRS harmonization. Statistical estimations were carried out based on this sample using the panel data approach. The results showed differences in the discretionary accruals regardless of the size of the audit firm, and also indicated adverse patterns between clients of the four largest firms. Thus it was established that for the Brazilian capital market, simple segregation between big four and others does not appear to make any sense, contrary to the recommendations of literature. Such benchmarking suggests that future surveys conducted in this jurisdiction, which require the use of the auditor control variable, should do so by means of the inclusion of five groups, one for each large auditing company and one for smaller audit firms.
PolyADP‐ribosylation is required for long‐term memory formation in mammals

PolyADP‐ribosylation is a post‐translational modification of nuclear proteins, catalyzed by polyADP‐ribose polymerases (PARPs). In the nucleus, polyADP‐ribosylation catalyzed by PARP‐1 alters protein–protein and protein–DNA interactions, and is implicated in chromatin remodeling, DNA transcription, and repair. Previous results linked the activation of PARP‐1 with long‐term memory formation during learning in the marine mollusk Aplysia ( Science 2004, 304:1820–1822). Furthermore, PARP‐1 was highly activated in mammalian cerebral neurons treated with neurotrophins and neurotrophic peptides promoting neurite outgrowth and synaptic plasticity. Here, we examine the possibility that PARP‐1 activation is required for memory formation during learning in mammals. Mice were tested in two learning paradigms, object recognition and fear conditioning. PolyADP‐ribosylation of PARP‐1 and histone H1 were detected in their cerebral cortex and hippocampus immediately after their training session. Moreover, in both behavioral paradigms, suppression of PARP activity in the CNS during learning impaired their long‐term memory formation, without damaging their short‐term memory. These findings implicate PARP‐1 activation in molecular processes underlying long‐term memory formation during learning.
Recombinant Procollagen II: Deletion of D Period Segments Identifies Sequences That Are Required for Helix Stabilization and Generates a Temperature-sensitive N-Proteinase Cleavage Site*

A cDNA cassette system was used to synthesize recombinant versions of procollagen II in which one of the four blocks of 234 amino acids that define a repeating D periods of the collagen triple helix were deleted. All the proteins were triple helical and all underwent a helix-to-coil transition between 25 and 42 °C as assayed by circular dichroism. However, the details of the melting curves varied. The procollagen lacking the D1 period unfolded 3 °C lower than a full-length molecule. With the procollagen lacking the D4 period, the first 25% of unfolding occurred at a lower temperature than the full-length molecule, but the rest of the structure unfolded at the same temperature. With the procollagen lacking the terminal D0.4 period, the protein unfolded 3 °C lower than the full-length molecule and a smaller fraction of the protein was secreted by stably transfected clones than with the other recombinant procollagens. The results confirmed previous suggestions that the collagen triple helix contains regions of varying stability and they demonstrated that the two D periods at the end of the molecule contain sequences that serve as clamps for folding and for stabilizing the triple helix. Reaction of the recombinant procollagens with procollagen N-proteinase indicated that in the procollagen lacking the sequences, the D1 period assumed an unusual temperature-sensitive conformation at 35 °C that allowed cleavage at an otherwise resistant Gly-Ala bond between residues 394 and 395 of the α1(II) chain.
Research of environmental modeling method of coal mine rescue snake robot based on information fusion

A coal mine rescue snake robot with four orthogonal joints is developed. Taking the robot as an experimental platform, aiming at how to model and identify the environment of the coal mine tunnel after the disaster, a multi sensor data fusion algorithm based on genetic algorithm optimization of the variable structure fuzzy neural network (GAFNN) is proposed. Firstly, the fuzzy neural network model is structured by combining fuzzy framework with neural network. Secondly, the distance information between the snake robot and obstacle can be obtained by using ultrasonic sensors and infrared sensor, and the azimuth information of the target location can be obtained by night vision device. The information is fused by the fuzzy neural network. The neural network is introduced into the inference of fuzzy rule. Due to the fuzzy rule base is adjusted by variable structure, the self-learning of fuzzy membership functions and the preferential extraction of fuzzy rules are realized. Finally, the genetic algorithm is used to optimize the learning parameters of the variable structure fuzzy neural network, and the fast and global optimization of the parameters is realized. It overcomes the shortcoming that the conventional BP algorithm is easy to fall into local optimum, and improves the optimization performance. So that the error between the actual output and the expected output of the network is minimized, and the high accuracy identifying of eight kinds of typical environmental models which are established is realized. By comparing the simulation results of environmental models identification, the GAFNN algorithm can get higher identifying accuracy than the non-optimized FNN algorithm. The GAFNN algorithm is applied to the function of obstacle avoidance of developed snake robot, and it lays the foundation for further path planning.
Safe and Resilient Multi-vehicle Trajectory Planning Under Adversarial Intruder

Provably safe and scalable multi-vehicle trajectory planning is an important and urgent problem. Hamilton-Jacobi (HJ) reachability is an ideal tool for analyzing such safety-critical systems and has been successfully applied to several small-scale problems. However, a direct application of HJ reachability to multi-vehicle trajectory planning is often intractable due to the "curse of dimensionality. " To overcome this problem, the sequential trajectory planning (STP) method, which assigns strict priorities to vehicles, was proposed, STP allows multi-vehicle trajectory planning to be done with a linearly-scaling computation complexity. However, if a vehicle not in the set of STP vehicles enters the system, or even worse, if this vehicle is an adversarial intruder, the previous formulation requires the entire system to perform replanning, an intractable task for large-scale systems. In this paper, we make STP more practical by providing a new algorithm where replanning is only needed only for a fixed number of vehicles, irrespective of the total number of STP vehicles. Moreover, this number is a design parameter, which can be chosen based on the computational resources available during run time. We demonstrate this algorithm in a representative simulation of an urban airspace environment.
Citation Clustering for Identifying Research Contribution

The h-index is an index that measures productivity and citation impact of the published work but it has been criticized because it does not consider context of citation and reason behind citation. This indicates that there is a need for an improved h-index by a new approach which includes important citations received by a paper instead of the whole list of citations. Citation classification is an emerging area of research that categorizes citations based on the purpose behind the citation. To perform citation classification there is need of a standard set of classes called as classification scheme. Such standard scheme is not available so we aim to generate a citation classification scheme automatically i.e. by using hierarchical clustering. The clustering is performed by using similarity vectors. The main contribution of this research is to generate similarity distance matrix of keywords and verbs extracted from the citation sentences with the help of WordNet.
Returns to education in the Philippines

The paper estimated the marginal private and social rates of return for education investments over time (1988, 1990, and 1995) using the “elaborate method” and Mincer equation. Rates of return estimates in general were relatively stable, mostly increasing between 1988 and 1990, but fell in 1995. The unlikely trend of high or stable returns when educational attainment was increasing suggests that demand for educated workers somewhat kept pace with supply, due perhaps to technological expansion which favors skilled workers. Private and social rates of return consistently exceeded benchmarks used to judge the profitability of investment except for dropouts, possibly indicating the “sheepskin” effects and validating the private incentive for completion. As non-completion can be involuntary, government intervention is necessary—it should provide financial support to poor families to keep their children in school or implement policies to reduce unnecessary attrition in schooling attendance.
Obtaining Estimates for the Standard Errors of Long-Run Parameters

Macro Modelling Notes is a new section of the Review, which we hope will appear on a regular basis. It will contain a small number of very short papers that have arisen from applied macro modelling work at the Institute or elsewhere. In the course of building and operating macro models, a large amount of information is used and produced that may never enter the public domain. This may be because the information is not substantial enough to justify a whole journal article, or because it is specific to the practice of using a macro econometric model. However this information is often of general interest to other economists, and is nearly always helpful to other macro modellers. This section is designed as an outlet for information of this kind, which might otherwise not be published in any readily accessible form. The three notes below provide three different examples of this type of note. The first involves econometric practice, and shows how long-run standard errors can be simply derived using standard regression techniques. The second presents some econometric results on export pricing obtained during normal ‘model maintenance’ of our world model GEM. The third considers the problem of setting terminal dates for a consistent expectations model. This new section of the Review is designed as a vehicle for all UK and overseas macro modellers, and therefore outside submissions are strongly encouraged. Submissions must be of about the length of the notes shown here, and contain relevant material that does not form part of a larger article soon to be published. Unlike Review articles, these notes will not normally be refereed, but the Editorial Board may consult expert advice when necessary.
Mandatory auditor rotation and retention: impact on market share

Purpose – To explore the effects of mandatory auditor rotation and retention on the long‐term market shares of the accounting firms that audit the members of the Standard and Poor's (S&P) 500.Design/methodology/approach – A Markov model is constructed that depicts the movements of S&P 500 firms in the period 1995 to 1999 among Big 5 accounting firms. Auditor rotation and retention are reflected in the transition probabilities. The impacts of mandatory auditor rotation and retention policies are evaluated by examining the state probabilities after two, five, and nine years.Findings – The paper finds that mandatory auditor rotation will have substantial effects on long‐term market shares, whereas mandatory auditor retention will have very small effects. It shows that a firm's ability to attract new clients, as opposed to retaining current clients, will be the primary factor in determining the firm's long‐term market share under mandatory auditor rotation.Research limitations/implications – The paper assumes.
Does financial crisis affect financial reporting of good news and bad news

The objective of this paper is to examine the impact of financial crisis on financial reporting of good news and bad news in the UK annual report narrative sections. We use the manual content analysis to measure levels of good news and bad news information for a sample of 110 chairman statements of financial institutions. Our sample covers a five year period (2006–2010), which represents the global financial crisis year (2008), two years before the crisis and two years after the crisis. Our regression analysis shows that UK financial companies disclose more good news information than bad news information. We also find that the crisis affects the financial reporting of good news and bad news. These results suggest that after controlling for other firm characteristics and corporate governance mechanisms, UK financial companies disclose more bad news information during and after the crisis period, while they disclose less good news during these periods.