Serum neuronal pentraxin 2 is related to cognitive dysfunction and electroencephalogram slow wave/fast wave frequency ratio in epilepsy

BACKGROUND Cognitive dysfunction in epileptic patients is a high-incidence complication.Its mechanism is related to nervous system damage during seizures,but there is no effective diagnostic biomarker.Neuronal pentraxin 2(NPTX2)is thought to play a vital role in neurotransmission and the maintenance of synaptic plasticity.This study explored how serum NPTX2 and electroencephalogram(EEG)slow wave/fast wave frequency ratio relate to cognitive dysfunction in patients with epilepsy.AIM To determine if serum NPTX2 could serve as a potential biomarker for diagnosing cognitive impairment in epilepsy patients.METHODS The participants of this study,conducted from January 2020 to December 2021,comprised 74 epilepsy patients with normal cognitive function(normal group),37 epilepsy patients with cognitive dysfunction[epilepsy patients with cognitive dysfunction(ECD)group]and 30 healthy people(control group).The minimental state examination(MMSE)scale was used to evaluate cognitive function.We determined serum NPTX2 levels using an enzyme-linked immunosorbent kit and calculated the signal value of EEG regions according to the EEG recording.Pearson correlation coefficient was used to analyze the correlation between serum NPTX2 and the MMSE score.RESULTS The serum NPTX2 level in the control group,normal group and ECD group were 240.00±35.06 pg/mL,235.80±38.01 pg/mL and 193.80±42.72 pg/mL,respectively.The MMSE score was lowest in the ECD group among the three,while no significant difference was observed between the control and normal groups.In epilepsy patients with cognitive dysfunction,NPTX2 level had a positive correlation with the MMSE score(r=0.367,P=0.0253)and a negative correlation with epilepsy duration(r=−0.443,P=0.0061)and the EEG slow wave/fast wave frequency ratio value in the temporal region(r=−0.339,P=0.039).CONCLUSION Serum NPTX2 was found to be related to cognitive dysfunction and the EEG slow wave/fast wave frequency ratio in patients with epilepsy.It is thus a potential biomarker for the diagnosis of cognitive impairment in patients with epilepsy.

Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China

Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.

Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model:A case study from an agro-urban region of Pakistan

In Punjab(Pakistan),the increasing population and expansion of land use for agriculture have severely exploited the regional groundwater resources.Intensive pumping has resulted in a rapid decline in the level of the water table as well as its quality.Better management practices and artificial recharge are needed for the development of sustainable groundwater resources.This study proposes a methodology to delineate favorable groundwater potential recharge zones(FPRI)by integrating maps of groundwater potential recharge index(PRI)with the DRASTIC-based groundwater vulnerability index(VI).In order to evaluate both indexes,different thematic layers corresponding to each index were overlaid in ArcGIS.In the overlay analysis,the weights(for various thematic layers)and rating values(for sub-classes)were allocated based on a review of published literature.Both were then normalized and modified using the analytical hierarchical process(AHP)and a frequency ratio model respectively.After evaluating PRI and FPRI,these maps were validated using the area under the curve(AUC)method.The PRI map indicates that 53%of the area assessed exists in very low to low recharge zones,22%in moderate,and 25%in high to excellent potential recharge zones.The VI map indicates that 38%of the area assessed exists in very low to low vulnerability,33%in moderate,and 29%in high to very high vulnerability zones.The FPRI map shows that the central region of Punjab is moderately-to-highly favorable for recharge due to its low vulnerability and high recharge potential.During the validation process,it was found that the AUC estimated with modified weights and rating values was 79%and 67%,for PRI and VI indexes,respectively.The AUC was less when evaluated using original weights and rating values taken from published literature.Maps of favorable groundwater potential recharge zones are helpful for planning and implementation of wells and hydraulic structures in this region.

GIS-based Frequency Ratio and Logistic Regression Modelling for Landslide Susceptibility Mapping of Debre Sina Area in Central Ethiopia

Ethiopia has a mountainous landscape which can be divided into the Northwestern and Southeastern plateaus by the Main Ethiopian Rift and Afar Depression. Debre Sina area is located in Central Ethiopia along the escarpment where landslide problem is frequent due to steep slope, complex geology, rift tectonics, heavy rainfall and seismicity. In order to tackle this problem, preparing a landslide susceptibility map is very important. For this, GISbased frequency ratio(FR) and logistic regression(LR) models have been applied using landslide inventory and the nine landslide factors(i.e. lithology, land use, distance from river & fault, slope, aspect, elevation, curvature and annual rainfall). Database construction, weighting each factor classes or factors, preparing susceptibility map and validation were the major steps to be undertaken. Both models require a rasterized landslide inventory and landslide factor maps. The former was classified into training and validation landslides. Using FR model, weights for each factor classes were calculated and assigned so that all the weighted factor maps can be added to produce a landslide susceptibility map. In the case of LR model, the entire study area is firstly divided into landslide and non-landslide areas using the training landslides. Then, these areas are changed into landslide and non-landslide points so as to extract the FR maps of the nine landslide factors. Then a linear relationship is established between training landslides and landslide factors in SPSS. Based on this relationship, the final landslide susceptibility map is prepared using LR equation. The success-rate and prediction-rate of FR model were 74.8% and 73.5%, while in case of LR model these were 75.7% and 74.5% respectively. A close similarity in the prediction and validation rates showed that the model is acceptable. Accuracy of LR model is slightly better in predicting the landslide susceptibility of the area compared to FR model.

Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.

Frequency Ratio Analysis of Mass Movements in the Xiangxi Catchment, Three Gorges Reservoir Area, China

In 2003, the Three Gorges Project （TGP, China）, currently the world＇s largest hydroelectric power plant by total capacity, went into operation. Due to large-scale impoundment of the Yangtze River and its tributaries and also due to resettlement, extensive environmental impacts like land use change and increase of geohazards are associated with the TGP. Within the Yangtze Project, we investigate these effects for the Xiangxi （香溪） catchment which is part of the Three Gorges Reservoir. The aim of this study is to evaluate the susceptibility for mass movement within the Xiangxi River backwater area using geographic information system （GIS）. We used existing mass movements and the conditioning factors （geology, elevation, slope, curvature, land use, and land use change） for analyzing mass movement susceptibility. Mass movements and geology were mapped in the field to establish a mass movement inventory and a geological map. Land use and digital elevation model （DEM） were obtained from remote-sensing data. We determined the relation between mass movements and the conditioning factors by using the frequency ratio method and found strong relation between mass movements and both natural and human-influenced conditioning factors.

Fuzzy–frequency ratio model for avalanche susceptibility mapping

Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the property.Avalanche susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche risk.In the present study,a probabilistic data-driven geospatial fuzzy–frequency ratio(fuzzy–FR)model is proposed and developed for avalanche susceptibility mapping,especially for the large undocumented region.The fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti region.The fuzzy–FR model utilized the six avalanche occurrence factors(i.e.slope,aspect,curvature,elevation,terrain roughness and vegetation cover)and one referent avalanche inventory map to generate the avalanche susceptibility map.Amongst 292 documented avalanche locations from the avalanche inventory map,233(80%)were used for training the model and remaining 59(20%)were used for validation of the map.The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve(ROC-AUC)technique.For validation of the results using ROC-AUC technique,the success rate and prediction rate were calculated.The values of success rate and prediction rate were 94.07%and 91.76%,respectively.The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping.

Influence of porosity distribution on nonlinear free vibration and transient responses of porous functionally graded skew plates

This article deals with the investigation of the effects of porosity distributions on nonlinear free vibration and transient analysis of porous functionally graded skew(PFGS)plates.The effective material properties of the PFGS plates are obtained from the modified power-law equations in which gradation varies through the thickness of the PFGS plate.A nonlinear finite element(FE)formulation for the overall PFGS plate is derived by adopting first-order shear deformation theory(FSDT)in conjunction with von Karman’s nonlinear strain displacement relations.The governing equations of the PFGS plate are derived using the principle of virtual work.The direct iterative method and Newmark’s integration technique are espoused to solve nonlinear mathematical relations.The influences of the porosity distributions and porosity parameter indices on the nonlinear frequency responses of the PFGS plate for different skew angles are studied in various parameters.The effects of volume fraction grading index and skew angle on the plate’s nonlinear dynamic responses for various porosity distributions are illustrated in detail.

Analysis and Optimum Design of Differential Inductors Using Distributed Capacitance Model

A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven symmetric inductor to the f SR of the single-ended driven inductor is firstly predicted and explained.Compared with a single-ended configuration,experimental data demonstrate that the differential inductor offers a 127% greater maximum quality factor and a broader range of operating frequencies.Two differential inductors with low parasitical capacitance are developed and validated.

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data(70% landslide pixels) and validation data(30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC) curve) of the proposed model was the highest, reaching 0.88,compared with traditional models(support vector machine(SVM) = 0.85, Bayesian network(BN) = 0.81,frequency ratio(FR) = 0.75, weight of evidence(WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km^(2) and 0.88/km^(2), respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without containing more " stable" pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.

Uncertainty pattern in landslide susceptibility prediction modelling:Effects of different landslide boundaries and spatial shape expressions

In some studies on landslide susceptibility mapping(LSM),landslide boundary and spatial shape characteristics have been expressed in the form of points or circles in the landslide inventory instead of the accurate polygon form.Different expressions of landslide boundaries and spatial shapes may lead to substantial differences in the distribution of predicted landslide susceptibility indexes(LSIs);moreover,the presence of irregular landslide boundaries and spatial shapes introduces uncertainties into the LSM.To address this issue by accurately drawing polygonal boundaries based on LSM,the uncertainty patterns of LSM modelling under two different landslide boundaries and spatial shapes,such as landslide points and circles,are compared.Within the research area of Ruijin City in China,a total of 370 landslides with accurate boundary information are obtained,and 10 environmental factors,such as slope and lithology,are selected.Then,correlation analyses between the landslide boundary shapes and selected environmental factors are performed via the frequency ratio(FR)method.Next,a support vector machine(SVM)and random forest(RF)based on landslide points,circles and accurate landslide polygons are constructed as point-,circle-and polygon-based SVM and RF models,respectively,to address LSM.Finally,the prediction capabilities of the above models are compared by computing their statistical accuracy using receiver operating characteristic analysis,and the uncertainties of the predicted LSIs under the above models are discussed.The results show that using polygonal surfaces with a higher reliability and accuracy to express the landslide boundary and spatial shape can provide a markedly improved LSM accuracy,compared to those based on the points and circles.Moreover,a higher degree of uncertainty of LSM modelling is present in the expression of points because there are too few grid units acting as model input variables.Additionally,the expression of the landslide boundary as circles introduces errors in measurement and is not as accurate as the polygonal boundary in most LSM modelling cases.In addition,the results under different conditions show that the polygon-based models have a higher LSM accuracy,with lower mean values and larger standard deviations compared with the point-and circle-based models.Finally,the overall LSM accuracy of the RF is superior to that of the SVM,and similar patterns of landslide boundary and spatial shape affecting the LSM modelling are reflected in the SVM and RF models.

Enhancement and modulation of terahertz radiation by multi-color laser pulses

We study theoretically intense terahertz radiation from multi-color laser pulse with uncommon frequency ratios. Com- paring the two-color laser scheme, of which the uncommon frequency ratio should be set to be a specific value, we show that by using multi-color harmonic laser pulses as the first pump component, the lasers as the second pump component can be adjusted in a continuous frequency range. Moreover, these multi-color laser pulses can effectively modulate and enhance the terahertz radiation, and the terahertz yield increases with the increase of the wavelength of the uncommon pump com- ponent and is stable to the laser relative phase. Finally, we utilize the electron densities and velocities of ionization events to illustrate the physical mechanism of the intense terahertz generation.

An experimental investigation of one-and two-degree of freedom VIV of cylinders

In the paper,an experiment investigation was conducted for one-and two-degree of freedom vortex-induced vibration（VIV） of a horizontally-oriented cylinder with diameter of 11 cm and length of 120 cm.In the experiment,the spring constants in the cross-flow and in-line flow directions were regulated to change the natural vibration frequency of the model system.It was found that,in the one-degree of freedom VIV experiment,a ＂double peak＂ phenomenon was observed in its amplitude within the range of the reduced velocities tested,moreover,a ＂2T＂ wake appeared in the vicinity of the second peak.In the two-degree of freedom VIV experiment,the trajectory of cylinder exhibited a reverse ＂C＂ shape,i.e.,a ＂new moon＂ shape.Through analysis of these data,it appears that,besides the non-dimensional in-line and cross-flow natural vibration frequency ratios,the absolute value of the natural vibration frequency of cylinder is also one of the important parameters affecting its VIV behavior.

Predicting of dust storm source by combining remote sensing, statistic-based predictive models and game theory in the Sistan watershed, southwestern Asia

Dust storms in arid and desert areas affect radiation budget,air quality,visibility,enzymatic activities,agricultural products and human health.Due to increased drought and land use changes in recent years,the frequency of dust storms occurrence in Iran has been increased.This study aims to identify dust source areas in the Sistan watershed(Iran-Afghanistan borders)-an important regional source for dust storms in southwestern Asia,using remote sensing(RS)and bivariate statistical models.Furthermore,this study determines the relative importance of factors controlling dust emissions using frequency ratio(FR)and weights of evidence(WOE)models and interpretability of predictive models using game theory.For this purpose,we identified 211 dust sources in the study area and generated a dust source distribution map-inventory map-by dust source potential index based on RS data.In addition,spatial maps of topographic factors affecting dust source areas including soil,lithology,slope,Normalized difference vegetation index(NDVI),geomorphology and land use were prepared.The performance of two models(WOE and FR)was evaluated using the area under curve(AUC)of the receiver operating characteristic curve.The results showed that soil,geomorphology and slope exhibited the greatest influence in the dust source areas.The 55.3%(according to FR)and 62.6%(according to WOE)of the total area were classified as high and very high potential dust sources,while both models displayed acceptable accuracy with subsurface levels of 0.704 for FR and 0.751 for WOE,although they predict different fractions of dust potential classes.Based on Shapley additive explanations(SHAP),three factors,i.e.,soil,slope and NDVI have the highest impact on the model's output.Overall,combination of statistic-based predictive models(or data mining models),RS and game theory techniques can provide accurate maps of dust source areas in arid and semi-arid regions,which can be helpful for mitigation of negative effects of dust storms.

Experimental Study on Flow past A Rotationally Oscillating Cylinder

A series of experiments was carried out to study the flow behaviour behind a rotationally oscillating cylinder at a low Reynolds number （Re=300） placed in a recirculation water channel. A stepper motor was used to rotate the cylinder clockwise- and- counterclockwise about its longitudinal axis at selected frequencies. The particle image velocimetry （PIV） technique was used to capture the flow field behind a rotationally oscillating cylinder. Instantaneous and time-averaged flow fields such as the vorticity contours, streamline topologies and velocity distributions were analyzed. The effects of four rotation angle and frequency ratios Fr （Fr=fn/fv, the ratio of the forcing frequency fn to the natural vortex shedding frequency fv） on the wake in the lee of a rotationally oscillating cylinder were also examined. The significant wake modification was observed when the cylinder undergoes clockwise-and-counterclockwise motion with amplitude of π, especially in the range of 0.6≤Fr≤1.0.

Analyses of Characteristics of Long-Term Monitoring of Arterial Pressure and Pulse

Long-term observations of pulse and arterial blood pressure taken from a patient＇s daily self-control diary have been analyzed in the paper. The diary was kept in the morning and in the evening. It contains regular observational data collected during over 13 years. Statistical estimates of series and their spectral responses were obtained. A difference between the morning and evening series was noted. Spectral harmonics with the period of 7 days was typical of the evening series. The morning series are characterized by a ＂lunar＂ component with the -27.35-day period. The examined series were also compared with the daily series of atmospheric pressure and daily Wolf numbers. Seasonal pulse and arterial pressure pattern and average monthly self-control tabulated data obtained during 13 years are presented in the paper.

Compromises in Vehicle Suspension Design

When designing vehicle suspension systems, compromises are usually made when setting the range of values for spring stiffness and damping constant. Suspension parameters are set depending on the operational requirements of the market. Passenger car for example, would require high quality damping while off road vehicle requires high spring stiffness setting. A quarter vehicle suspension model has been used to study the suspension transmissibility in handling and ride at various frequency ratios. The results obtained show that as the frequency ratio increases, transmissibility for handling reduces with increasing suspension stiffness and increases as the damping constant is increased. On the other hand, transmissibility for ride deteriorate as the spring constant is increased but approaches the ideal as the damping constant is increased. The dynamic magnification of the sprung masses reduces while that of the unsprung masses improves as the frequency ratio is increased.

Evaluation of the Collapse Susceptibility of the Northern Foot of the Tianshan Mountains

Collapse is a geological disaster second only to landslides and occurs in large numbers every year in the northern foothills of the Tianshan Mountains in Xinjiang, China. We collected a variety of data such as topography, geological vegetation coverage, and human activities, and used spatial correlation analysis to eliminate factors with strong correlations. The frequency of collapse was calculated by the frequency ratio method and a hierarchical map was made. The result shows, in low susceptibility zone (LSI = 0 - 4), only 3 collapses happened, and 0.39% of total collapses. In middle susceptibility zone (LSI = 4 - 7.5), 35 collapses happened, and 5.66% of total collapses. In high susceptibility zone (LSI = 7.5 - 10), 64 collapses happened, and 10.36% of total collapses. In extremely high susceptibility zone (LSI = 10 - 14), 516 collapses happened, and 83.5% of total collapses. Using the GIS-based frequency method, the susceptibility to collapse was calculated and mapped, which was in good agreement with the actual landslide data. Collapse susceptibility results provide guidance for engineering construction.

Landslide Hazard Assessment in the Northern Mountainous Areas of Tianshan Mountains Based on GIS

China is a country prone to geological disasters, especially in the northern mountainous areas of the Tianshan Mountains in Xinjiang, where the surface vegetation is sparse and the rainfall is concentrated, which is prone to landslides and brings a lot of losses to the local people. Based on the field investigation, this paper evaluates the landslide susceptibility in the northern mountainous area of Tianshan Mountains. The frequency ratio method is used to calculate the landslide probability, and the landslide index (LSI) is formed to represent the landslide susceptibility. The slope unit method is used to determine the landslide units, which values were calculated by the average of the landslide index. According to the calculated LSI range of 4.53 - 20.60. It is divided into 4 grades, LSI = 4.53 - 9, which is an area that is not prone to landslides, with an area of 891.69 km2. LSI = 9 - 11 indicates an area where landslides are more likely to occur, with an area of 1252.31 km2. LSI = 11 - 13 indicates the area is more prone to landslides, with an area of 714.86 km2. LSI > 13 indicates the most prone area for landslides, with an area of 924.60 km2.

Normalization method for asphalt mixture fatigue equation under different loading frequencies

In order to analyze the effect of different loading frequencies on the fatigue performance for asphalt mixture,the changing law of asphalt mixture strengths with loading speed was revealed by strength tests under different loading speeds.Fatigue equations of asphalt mixtures based on the nominal stress ratio and real stress ratio were established using fatigue tests under different loading frequencies.It was revealed that the strength of the asphalt mixture is affected by the loading speed greatly.It was also discovered that the fatigue equation based on the nominal stress ratio will change with the change of the fatigue loading speed.There is no uniqueness.But the fatigue equation based on the real stress ratio doesn't change with the loading frequency.It has the uniqueness.The results indicate the fatigue equation based on the real stress ratio can realize the normalization of the asphalt mixture fatigue equation under different loading frequencies.It can greatly benefit the analysis of the fatigue characteristics under different vehicle speeds for asphalt pavement.