Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Complexity Model Predictive Torque Control Method Without Weighting Factor for Five-Phase PMSM Based on Hysteresis Comparators

An improved model predictive torque control (MPTC) method without weighting factors is proposed for five-phase permanent magnet synchronous machine (PMSM) drives, which aims to reduce heavy computation complexity, and the low-order current harmonics existing in harmonic subspace in the traditional finite-control-set (FCS) MPTC. In the proposed MPTC scheme, a modified control set consisting of virtual voltage vectors has been defined and adopted with two hysteresis comparators. Duty ratio optimization is also introduced to reduce torque ripples and eliminate weighting factors in the predefined cost function. In addition, a digital delay compensation solution of the proposed MPTC scheme is adopted to improve the control precision. Finally, a series of hardware-in-loop real-time simulation and experimental tests is achieved to compare the performances of the proposed and traditional FCS-MPTC schemes. Simulation and experimental results have verified the effectiveness of the proposed MPTC scheme.
BRAIN LEVELS OF CHLORDIAZEPOXIDE IN RATS

Sununary: The timeand dose-dependent uptake of chlordiazepoxide by the brain of rats was investigated and correlated with the blood levels of the drug. Peak concentration in the brain was reached in 10 min after i.p. injection of25 mg/kg, and in 5 min with a dose of 50 mglkg of the drug. Retention of chlordiazepoxide by the brain showed different characteristics depending on the size of the dose used.
Oblivious Chase Termination: The Sticky Case

The chase procedure is one of the most fundamental algorithmic tools in database theory. A key algorithmic task is uniform chase termination, i.e., given a set of tuple-generating dependencies (tgds), is it the case that the chase under this set of tgds terminates, for every input database? In view of the fact that this problem is undecidable, no matter which version of the chase we consider, it is natural to ask whether well-behaved classes of tgds, introduced in different contexts such as ontological reasoning, make our problem decidable. In this work, we consider a prominent decidability paradigm for tgds, called stick-iness. We show that for sticky sets of tgds, uniform chase termination is decidable if we focus on the (semi-)oblivious chase, and we pinpoint its exact complexity: PS PACE -complete in general, and NL OG - S PACE -complete for predicates of bounded arity. These complexity results are obtained via graph-based syntactic characterizations of chase termination that are of independent interest.
Advanced diffusion weighted imaging techniques Aims: 1) The basic principle of how magnetic resonance imaging is sensitized to free diffusion or Browinan motion of water protons

1) The basic principle of how magnetic resonance imaging is sensitized to free diffusion or Browinan motion of water protons 2) The introduction of the commonly used apparent diffusion coefficient (ADC) based on an increasing, mono-exponential signal decay when diffusion weighting is augmented 3) The perfusion induced deviation from monoexponential signal decay when weak diffusion sensitizing is applied, as introduced in the intravoxel-incoherent motion (IVIM) theory (1). 4) The restriction induced deviation from monoexponential signal when strong diffusion sensitizing is applied as captures using diffusion kurtosis imaging (2) 5) To show clinical examples of the application of advanced diffusion techniques
Strategies for Glucose Control in People with Type 1 Diabetes

Abstract In this paper we apply a robust feedforward-feedback control strategy to people with type 1 diabetes. The feedforward controller consists of a bolus calculator which compensates the disturbance coming from meals. The feedback controller is based on a linearized description of the model describing the patient. We minimize the risk of hypoglycemia by introducing a time-varying glucose setpoint based on the announced meal size and the physiological model of the patient. The simulation results are based on a virtual patient simulated by the Hovorka model. They include the cases where the insulin sensitivity changes, and mismatches in meal estimation. They demonstrate that the designed controller is able to achieve offset-free control when the insulin sensitivity change, and that having a time-varying reference signal enables more robust control of blood glucose in the cases where the meal size is known, but also when the ingested meal does not match the announced one.
AN ESTIMATION OF TECHNICAL EFFICIENCY OF GARLIC PRODUCTION IN KHYBER PAKHTUNKHWA PAKISTAN

This study was conducted to estimate the technical efficiency of farmers in garlic production in Khyber Pakhtunkhwa province, Pakistan. Data was randomly collected from 110 farmers using multistage sampling technique. Maximum likelihood estimation technique was used to estimate Cob-Douglas frontier production function. The analysis revealed that the estimated mean technical efficiency was 77 percent indicating that total output can be further increased with efficient use of resources and technology. The estimated gamma value was found to be 0.93 which shows 93% variation in garlic output due to inefficiency factors. The analysis further revealed that seed rate, tractor hours, fertilizer, FYM and weedicides were positive and statistically significant production factors. The results also show that age and education were statistically significant inefficiency factors, age having positive and education having negative relationship with the output of garlic. This study suggests that in order to increase the production of garlic by taking advantage of their high efficiency level, the government should invest in the research and development aspects for introducing good quality seeds to increase garlic productivity and should organize training programs to educate farmers about garlic production.
Casitas: A Location-Dependent Ecological Trap for Juvenile Caribbean Spiny Lobsters, Panulirus argus

This Article is brought to you for free and open access by the Biological Sciences at ODU Digital Commons. It has been accepted for inclusion in Biological Sciences Faculty Publications by an authorized administrator of ODU Digital Commons. For more information, please contact digitalcommons@odu.edu. Repository Citation Gutzler, Benjamin C. ; Butler, Mark J. IV; and Behringer, Donald C. , "Casitas: A Location-Dependent Ecological Trap for Juvenile Caribbean Spiny Lobsters, Panulirus argus" (2015). Biological Sciences Faculty Publications. 310. https://digitalcommons.odu.edu/biology_fac_pubs/310
Integrating diverse calibration products to improve seismic location

The monitoring of nuclear explosions on a global basis requires accurate event locations. As an example, under the Comprehensive Test Ban Treaty, the size of an on-site inspection search area is 1,000 square kilometers or approximately 17 km accuracy assuming a circular area. This level of accuracy is a significant challenge for small events that are recorded using a sparse regional network. In such cases, the travel-time of seismic energy is strongly affected by crustal and upper mantle heterogeneity and large biases can result. This can lead to large systematic errors in location and, more importantly, to invalid error bounds associated with location estimates. Corrections can be developed and integrated to correct for these biases. These path corrections take the form of both three-dimensional model corrections along with three-dimensional empirically based travel time corrections. LLNL is currently working to integrate a diverse set of three-dimensional velocity model and empirical based travel-time products into one consistent and validated calibration set. To perform this task, we have developed a hybrid approach that uses three-dimensional model corrections for a region and then uses reference events when available to improve the path correction. This Bayesian kriging approach uses the best apriori three-dimensional velocity modelmore » that is produced for a local region and uses this as a baseline correction. When multiple models are produced for a local region, uncertainties in the models are compared against each other using ground truth data and an optimal model is chosen. We . are in the process of combining three-dimensional models on a region-by-region basis and integrating the uncertainties to form a global correction set. The Bayesian kriging prediction combines this a priori model and its statistics with the empirical calibrations to give an optimal aposteriori calibration estimate. In regions where there is limited or no coverage by reference events the corrections will be based primarily on the model. The integrated a priori model is particularly important in these areas. In regions with adequate calibration events, we are demonstrating improvement in event location through the reduction of regional bias. In regions with sparse or no ground truth, the a priori model will need to be spot-validated with the use of dedicated calibration experiments or through the use of mining explosions, where available. « less
What Do Grades and Achievement Tests Measure ? ∗

Grades and achievement tests are widely used as measures of cognition. This paper shows that they are stronger predictors of many important life outcomes than IQ. We examine a variety of sources of evidence on what these measures capture and find that personality contributes substantially to the predictive performance of these measures. This result has important implications for the interpretation of studies using cognition to explain differences in outcomes and for the use of cognitive measures to evaluate the effectiveness of public policies.
A Reinforcement Learning Framework for Explainable Recommendation

Explainable recommendation, which provides explanations about why an item is recommended, has attracted increasing attention due to its ability in helping users make better decisions and increasing users' trust in the system. Existing explainable recommendation methods either ignore the working mechanism of the recommendation model or are designed for a specific recommendation model. Moreover, it is difficult for existing methods to ensure the presentation quality of the explanations (e.g., consistency). To solve these problems, we design a reinforcement learning framework for explainable recommendation. Our framework can explain any recommendation model (model-agnostic) and can flexibly control the explanation quality based on the application scenario. To demonstrate the effectiveness of our framework, we show how it can be used for generating sentence-level explanations. Specifically, we instantiate the explanation generator in the framework with a personalized-attention-based neural network. Offline experiments demonstrate that our method can well explain both collaborative filtering methods and deep-learning-based models. Evaluation with human subjects shows that the explanations generated by our method are significantly more useful than the explanations generated by the baselines.
The Effect of Kuwaiti Online Readers’ Comments on Sectarian and Tribal Issues: A Case Study of the Online Newspaper Alaan

One of the dilemmas faced by online newspapers is how to handle readers’ comments. The interactive nature of the Internet encourages online readers to express their ideas, feelings and opinions freely without fear of negative outcomes resulting from crossing the restrictions of freedom expression that have been set by the government or by online editors. Arab online editors encourage their readers to comment on news stories but censor what they consider to be offensive, anti-nationalist or blasphemous against Islam. An attitudinal study involving online content analysis found those readers’ comments in the first Kuwaiti online newspaper, Alaan, encourage enmity among its readers and lead to increased religious and ethnic bigotry among Kuwaiti students.
The Promises and Perils of Multinational Corporations: the Nigerian Experience

This article explores the concept of multinational corporations, their evolution and impact on the developing economies with Nigeria in focus. Several theories of multinational enterprises were reviewed and how these theories, as well as the activities of the multinational firms, relate to the development of the Nigerian economy. Arguments put forward by different scholars were also discussed. Finally, it was recommended that for the Nigerian economy to develop, conscious actions have to be taken to move the economy from an import dependent to an exporting economy.
Chemically Sensitive Polymer Coatings For SH-Surface Acoustic Wave Sensors for the Detection of Benzene in Water

CHEMICALLY SENSITIVE POLYMER COATINGS FOR SH-SURFACE ACOUSTIC WAVE SENSORS FOR THE DETECTION OF BENZENE IN WATER Robert Lenisa, B.S. Marquette University, 2013 Polymer-coated shear horizontal surface acoustic wave (SH-SAW) sensors are investigated for the detection of benzene in aqueous samples. The SH-SAW sensors using three-layer geometry have a single polymer sensing layer which absorbs the analyte and interacts with the surface wave. Several polymers are identified as potential improvements over current sensing films based on glass transition temperature and Hildebrand solubility parameter. The polymers investigated in this work include poly (methyl acrylate) (PMA), poly (butyl acrylate) (PBA), poly (ethylene co-vinyl acetate) (PEVA), bisphenol-A poly (dimethylsiloxane) (BPA PDMS), and bisphenol-A poly (hexamethyltrisiloxane) (BPA HMTS). The polymers are spin coated on a lithium tantalate (LiTaO3) SHSAW dual delay-line device at thicknesses between 0.3 μm and 1.0 μm. Each film’s thickness is measured and the film is exposed to multiple concentrations of the aromatic hydrocarbons benzene, ethylbenzene, toluene, and xylenes (BTEX). The added mass and viscoelastic changes in the sensing layer result in a change in center frequency and acoustic loss of the device. The frequency change is measured and used to determine sensitivity of the coated sensor to each analyte. BPA PDMS and BPA HMTS show larger sensitivities to each of the BTEX analytes than PBA, PMA, or PEVA. However, both BPA PDMS and BPA HMTS were observed to lose sensitivity during the aging process. It is shown that the aging effect on BPA HMTS can be mitigated by baking the film after it is applied to the device.
FPGA-BASED DIGITAL CONTROLLER FOR DC-DC CONVERTER DIYYA HIDAYAH BT ABD. RAHMAN A thesis submitted in fulfillment of the requirement for the award of the Degree of Master of Electrical Engineering Faculty of Electrical and Electronic Engineering UniversitiTun

This thesis presents a FPGA-based digital controller for a DC-DC converter. The converter topologies chosen in this project is Non-Inverting Buck-Boost converter. The main difference from DSP-based solution is that FPGA allows simultaneous execution of all control procedures. The control algorithm has been developed using Verilog language based on the voltage control loop. The FPGA switching controller has been designed as simple as possible while maintaining the accuracy and dynamic response. The DE1 board is used to control the main circuit. Simulations and experimental results show the feasibility of the proposed method, opening interesting possibilities in motion and power electronics converter control.
A Contrastive Analysis of Machine Translation (Google Translate) and Human Translation: Efficacy in Translating Verb Tense from English to Persian

This study aims to examine the efficiency of Google translation in translating verb tense from English to Persian, the acceptable translation of Google translation, and the areas of possible errors in the Google translation. To this end, Google translated four passages of Oliver Twist. The Google translations were compared with the translation of Gharib based on the selected codes for the domain and extent of errors. The results were analyzed and evaluated in terms of accuracy and appropriateness. The findings of the study showed that Google Translate is not able to translate verb tense from English to Persian and the translated passages are not acceptable. Also, most of the grammatical errors occurred in translation of aspects, passives, and compounds, respectively. DOI: 10.5901/mjss.2016. v7n4S2p40
The Effects of European Austerity Programmes on Social Security Systems

The recent financial and economic crisis is intensifying the pressure for budget consolidation,increasing the likelihood of cuts in social services throughout Europe. One government after another is bringing forward a budget consolidation programme. Cuts are envisaged above all in social services and so the question arises of what effects this will have on welfare states in EU member countries and on Social Europe in general. In this study cuts in social systems are analysed and compared, both planned and already undertaken. Regardless of the different magnitudes of the austerity efforts and the policy fields concerned there can be no doubt that all austerity programmes are regressive in nature and that the option of raising incomes is being exercised far less frequently than spending cuts and this applies especially in the social realm.
Economic and Environmental Impacts of LSNT and Cover Crops for Nitrate-Nitrogen Reduction in Walnut Creek Watershed, Iowa, Using FEM and Enhanced SWAT Models

Nitrate nitrogen (NO 3 -N) enriched water originates from subsurface drains or "tiles" that underlay many fields in the Corn Belt and is the primary source of NO 3 -N to surface waters in this region. To better assess the fate and transport of nutrients, such as NO 3 -N, the tile drain and pothole components of SWAT (Soil and Water Assessment Tool) were enhanced and modified in the previous component of this study. In this study, the environmental and economic impacts of various best management practice (BMP) scenarios often adopted by local farmers to reduce sediment and nutrient loadings (in particular NO 3 -N) were evaluated using the modified SWAT (SWAT-M) and FEM (Farm-level Economic Model) models. Measured values of water quality indicators from the Walnut Creek watershed (WCW) located in central Iowa were used to verify the capability of SWAT-M to predict the impact of late-spring nitrate test (LSNT) and rye cover crop management on NO 3 -N reduction at the subbasin level. The results obtained from SWAT-M simulation results, similar to field measurement data, indicated a 25% reduction in NO 3 -N under the LSNT scenario. FEM results indicated a corresponding increased annual cost of $6/ha across all farms in the watershed. Simulation of other scenarios, including winter cover cropping and a combination of LSNT and cover cropping at different adoption rates within WCW, resulted in a progressive reduction in sediment and nutrient losses as adoption rates increased. Use of the rye cover crop added about $25/ha to $35/ha to the annual cost of the average farm, indicating that some cost-share support may be necessary to encourage farmers to use winter cover crops.
A Combined Probabilistic/Nonprobabilistic Decision Analysis for Contaminant Remediation

Groundwater contaminant remediation poses a significant challenge due in large part to ubiquitous uncertainties and unknowns. A number of remedial options are typically available at a given contamination site. However, choosing the best option is challenging, because it is not typically known beforehand how effective each remediation will be. Nonetheless, choices must be made. We present an approach to decision support consisting of three coupled layers accounting for model/parametric uncertainties and unknowns. The inner and outer layers employ an information-gap approach to uncertainty quantification, while the middle layer employs Bayes' theorem. Two synthetic remedial scenarios are explored to demonstrate the efficacy of the approach. Considered remedial actions are natural attenuation (NA) and an enhanced attenuation (EA).
Forest structure determines the abundance and distribution of large lianas in Gabon

Aim Lianas are an important component of forest structure in the tropics, accounting for up to 45% of total stems. Mounting evidence that tropical forests are undergoing structural changes, with a growing abundance of lianas reducing forest carbon storage potential, imparts a sense of urgency to study the drivers that control liana abundance and biomass, particularly in Africa where data come from a few, small-scale studies.
Temperature dependence of the paramagnetic spin excitations in BaFe$_2$As$_2$

We use inelastic neutron scattering to study temperature dependence of the paramagnetic spin excitations in iron pnictide BaFe$_2$As$_2$ throughout the Brillouin zone. In contrast to a conventional local moment Heisenberg system, where paramagnetic spin excitations are expected to have a Lorentzian function centered at zero energy transfer, the high-energy ($\hbar\omega>100$ meV) paramagnetic spin excitations in BaFe$_2$As$_2$ exhibit spin-wave-like features up to at least 290 K ($T= 2.1T_N$). Furthermore, we find that the sizes of the fluctuating magnetic moments $\approx 3.6\ \mu^2_B$ per Fe are essentially temperature independent from the AF ordered state at $0. 05T_N$ to $2. 1T_N$, which differs considerably from the temperature dependent fluctuating moment observed in the iron chalcogenide Fe$_{1.1}$Te [I. A. Zaliznyak {\it et al.}, Phys. Rev. Lett. {\bf 107}, 216403 (2011). ]. These results suggest unconventional magnetism and strong electron correlation effects in BaFe$_2$As$_2$.
Modeling Non-Compositional Expressions using a Search Engine

Non-compositional multi-word expressions present great challenges to natural language processing applications. In this paper, we present a method for modeling non-compositional expressions based on the assumption that the meaning of expressions depends on context. Therefore, context words can be used to select documents and separate documents where the expression has different meanings. Deviation from a baseline is measured using serendipity (i.e. the pointwise effect size). We used this statistical measure to mark which patterns are over-and under-represented and to take a decision if the pattern under scrutiny belongs to the meaning selected by the context words or not. We used the Google search engine to find document frequency estimates. When used with Google document frequency estimates, the serendipity measure closely mirrors some human intuitions on the preferred alternative.