Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Partial mediation role of self-efficacy between positive social interaction and mental health in family caregivers for dementia patients in Shanghai

We explored the mediation effect of caregiver self-efficacy on the influences of behavioral and psychological symptoms (BPSD) of dementia care recipients (CRs) or family caregivers’ (CGs) social supports (informational, tangible and affectionate support and positive social interaction) on CGs’ mental health. We interviewed 196 CGs, using a battery of measures including demographic data of the dyads, CRs’ dementia-related impairments, and CGs’ social support, self-efficacy and the Medical Outcome Study (MOS) Short-Form (SF-36) Health Survey. Multiple regression analyses showed that gathering information on self-efficacy and managing CG distress self-efficacy were the partial mediators of the relationship between positive social interaction and CG mental health. Managing caregiving distress self-efficacy also partial mediated the impact of BPSD on CG mental health. We discuss implications of the results for improving mental health of the target population in mainland China.

Partial rectification of the plasmon-induced electrical tunnel current in discontinuous thin gold film at optical frequency

The effect of plasmonoscillations, induced by pulsed laserirradiation, on the DC tunnel current between islands in a discontinuous thin goldfilm is studied. The tunnel current is found to be strongly enhanced by partial rectification of the plasmon-induced AC tunnel currents flowing between adjacent gold islands. The DC tunnel current enhancement is found to increase approximately linearly with the laser intensity and the applied DC bias voltage. The experimental data can be well described by an electron tunnelling model which takes the plasmon-induced AC voltage into account. Thermal heating seems not to contribute to the tunnel current enhancement.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

A methodological exploration to determine transportation disadvantage variables: the partial least square approach

Determining the key variables of transportation disadvantage remains a great challenge as the variables are commonly selected using ad-hoc techniques. In order to identify the variables, this research develops a transportation disadvantage framework by manipulating the capability approach. Developed framework is statistically analysed using partial least square-based software to determine the framework fitness. The statistical analysis identifies mobility and socioeconomic variables that significantly influence transportation disadvantage. The research reveals the key socioeconomic variables for transportation disadvantage in the case of Brisbane, Australia as household structure, presence of dependent family member, vehicle ownership, and driving licence possession.

Effect of partial H2O-D2O replacement on the anisotropy of transverse proton spin relaxation in bovine articular cartilage

Anisotropy of transverse proton spin relaxation in collagen-rich tissues like cartilage and tendon is a well-known phenomenon that manifests itself as the "magic-angle" effect in magnetic resonance images of these tissues. It is usually attributed to the non-zero averaging of intra-molecular dipolar interactions in water molecules bound to oriented collagen fibers. One way to manipulate the contributions of these interactions to spin relaxation is by partially replacing the water in the cartilage sample with deuterium oxide. It is known that dipolar interactions in deuterated solutions are weaker, resulting in a decrease in proton relaxation rates. In this work, we investigate the effects of deuteration on the longitudinal and the isotropic and anisotropic contributions to transverse relaxation of water protons in bovine articular cartilage. We demonstrate that the anisotropy of transverse proton spin relaxation in articular cartilage is independent of the degree of deuteration, bringing into question some of the assumptions currently held over the origins of relaxation anisotropy in oriented tissues.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Basic personal values underlie and give coherence to political values: A cross national study in 15 countries

Do the political values of the general public form a coherent system? What might be the source of coherence? We view political values as expressions, in the political domain, of more basic personal values. Basic personal values (e.g., security, achievement, benevolence, hedonism) are organized on a circular continuum that reflects their conflicting and compatible motivations. We theorize that this circular motivational structure also gives coherence to political values. We assess this theorizing with data from 15 countries, using eight core political values (e.g., free enterprise, law and order) and ten basic personal values. We specify the underlying basic values expected to promote or oppose each political value. We offer different hypotheses for the 12 non-communist and three post-communist countries studied, where the political context suggests different meanings of a basic or political value. Correlation and regression analyses support almost all hypotheses. Moreover, basic values account for substantially more variance in political values than age, gender, education, and income. Multidimensional scaling analyses demonstrate graphically how the circular motivational continuum of basic personal values structures relations among core political values. This study strengthens the assumption that individual differences in basic personal values play a critical role in political thought.

Novel window coupler for the detection of partial discharge activity in GIS

This work investigates the feasibly in using a low noise “C” Band block down-converter as a Ultra High Frequency window coupler for the detection of partial discharge activity from free conducting practices and a protrusion on the high voltage conductor in Gas Insulated Switchgear. The investigated window coupler has a better sensitivity than the internal Ultra High Frequency couplers fitted to the system. The investigated window couplers however are sensitive to changes in the frequency content of the discharge signals and appear to be less sensitive to negative discharges signals produced by a protrusion than the positive discharge signals.

Preliminary work on the detection of partial discharges in SF6 under impulse voltages

This paper presents preliminary results of an investigation into the detection of partial discharges on the rise of impulse voltages from a point-to-plane gap in SF6. A parallel RC detection impedance is placed in the earth path of a point. Computer simulations are done to determine the values of R and C that will result in the smallest impulse voltage signal and the largest discharge signal across the detection impedance. These simulations and the experimental work show that the impulse voltage signal can not be sufficiently attenuated during the rise time of the applied voltage impulse using the RC detection impedance alone. An alternative discharge detection method is proposed in which a resonant partial discharge coupler is used. Elimination of noise and the impulse voltage signal can be achieved by shorting the coupler plate to the ground plane in the middle of the disk. However, due to the bandwidth of the measuring equipment and noise from the impulse generator it was not possible to detect discharges on the rising edge of a 1.5s voltage impulse using a coupler shorted in the middle. It was found that for this particular coupler, with no shorting points, and if the rising edge of the voltage impulse is longer than 5us, (10us) PD activity can be detected on the rising edge.

Partial epilepsy syndrome in a Gypsy family linked to 5q31.3-q32

PURPOSE The restricted genetic diversity and homogeneous molecular basis of Mendelian disorders in isolated founder populations have rarely been explored in epilepsy research. Our long-term goal is to explore the genetic basis of epilepsies in one such population, the Gypsies. The aim of this report is the clinical and genetic characterization of a Gypsy family with a partial epilepsy syndrome. METHODS Clinical information was collected using semistructured interviews with affected subjects and informants. At least one interictal electroencephalography (EEG) recording was performed for each patient and previous data obtained from records. Neuroimaging included structural magnetic resonance imaging (MRI). Linkage and haplotype analysis was performed using the Illumina IVb Linkage Panel, supplemented with highly informative microsatellites in linked regions and Affymetrix SNP 5.0 array data. RESULTS We observed an early-onset partial epilepsy syndrome with seizure semiology strongly suggestive of temporal lobe epilepsy (TLE), with mild intellectual deficit co-occurring in a large proportion of the patients. Psychiatric morbidity was common in the extended pedigree but did not cosegregate with epilepsy. Linkage analysis definitively excluded previously reported loci, and identified a novel locus on 5q31.3-q32 with an logarithm of the odds (LOD) score of 3 corresponding to the expected maximum in this family. DISCUSSION The syndrome can be classified as familial temporal lobe epilepsy (FTLE) or possibly a new syndrome with mild intellectual deficit. The linked 5q region does not contain any ion channel-encoding genes and is thus likely to contribute new knowledge about epilepsy pathogenesis. Identification of the mutation in this family and in additional patients will define the full phenotypic spectrum.