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A dual-channel “on–off–on” fluorescent carbon dot was developed for specific detection of Fe3+ and Hg2+, which can be distinguished by F− and Al3+. The probe was practically applied in quantification of Fe3+ and Hg2+ in livestock feed and wastewater.

Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease that leads to progressive motor impairments with no available disease-modifying treatment. Current evidence indicates that exacerbated postsynaptic glutamate signaling in the striatum plays a key role in the pathophysiology of HD. However, it remains unclear whether reducing glutamate release can be an effective approach to slow the progression of HD. Here, we show that the activation of metabotropic glutamate receptors 2 and 3 (mGluR2/3), which inhibit presynaptic glutamate release, improves HD symptoms and pathology in heterozygous zQ175 knockin mice. Treatment of both male and female zQ175 mice with the potent and selective mGluR2/3 agonist LY379268 for either 4 or 8 weeks improves both limb coordination and locomotor function in all mice. LY379268 also reduces mutant huntingtin aggregate formation, neuronal cell death, and microglial activation in the striatum of both male and female zQ175 mice. The reduction in mutant huntingtin aggregates correlates with the activation of a glycogen synthase kinase 3β–dependent autophagy pathway in male, but not female, zQ175 mice. Furthermore, LY379268 reduces both Akt and ERK1/2 phosphorylation in male zQ175 mice but increases both Akt and ERK1/2 phosphorylation in female zQ175 mice. Taken together, our results indicate that mGluR2/3 activation mitigates HD neuropathology in both male and female mice but is associated with the differential activation and inactivation of cell signaling pathways in heterozygous male and female zQ175 mice. This further highlights the need to take sex into consideration when developing future HD therapeutics. SIGNIFICANCE STATEMENT The mGluR2/3 agonist LY379268 improves motor impairments and reduces pathology in male and female zQ175 Huntington’s disease mice. The beneficial outcomes of LY379268 treatment in Huntington’s disease mice were mediated by divergent cell signaling pathways in both sexes. We provide evidence that mGluR2/3 agonists can be repurposed for the treatment of Huntington’s disease, and we emphasize the importance of investigating sex as a biological variable in preclinical disease-modifying studies.

Glutamate is the primary excitatory neurotransmitter in the brain and plays critical roles in all aspects of neuronal function. Disruption of normal glutamate transmission has been implicated in a variety of neurodegenerative and neuropsychiatric diseases. Glutamate exerts its effect through ionotropic and metabotropic glutamate receptors (mGluRs). mGluR2 and mGluR3 are members of the Group II mGluR family and their activation leads to the inhibition of glutamate release from presynaptic nerve terminals and is also poised upstream of a myriad of signaling pathways in postsynaptic nerve terminals and neuroglia. Therefore, mGluR2 and mGluR3 have been considered as potential drug targets for the treatment of many neurological conditions and several compounds targeting these receptors have been developed. In this review, we discuss what is currently known regarding the contribution of mGluR2 and mGluR3 to the pathophysiology of some neurodegenerative and neuropsychiatric diseases including Amyotrophic lateral sclerosis, Alzheimer's disease, Huntington's disease, Parkinson's diseases, schizophrenia and depression as well as drug addiction. We then highlight the evidence supporting the use of various drugs including orthosteric and allosteric ligands acting on either mGluR2, mGluR3 or both for the management of these brain disorders.

A novel dual-emissive Eu

An accurate prediction of design wind speed is critical to the estimation of wind loads on any earth-bound civil engineering structure. Concerns have been raised within the Indian design co...

Huntington’s disease (HD) is an inherited autosomal dominant neurodegenerative disorder that leads to progressive motor and cognitive impairment. There are currently no available disease modifying treatments for HD patients. We have previously shown that pharmacological blockade of metabotropic glutamate receptor 5 (mGluR5) signaling rescues motor deficits, improves cognitive impairments and mitigates HD neuropathology in male zQ175 HD mice. Mounting evidence indicates that sex may influence HD progression and we have recently reported a sex-specific pathological mGluR5 signaling in Alzheimer’s disease (AD) mice. Here, we compared the outcomes of treatment with the mGluR5 negative allosteric modulator CTEP (2-chloro-4-[2-[2,5-dimethyl-1-[4-(trifluoromethoxy)phenyl]imidazol-4-yl]ethynyl]pyridine) in both male and female symptomatic zQ175 mice. We found that female zQ175 mice required a longer treatment duration with CTEP than male mice to show improvement in their rotarod performance. Unlike males, chronic CTEP treatment did not improve the grip strength nor reverse the cognitive decline of female zQ175 mice. However, CTEP reduced the number of huntingtin aggregates, improved neuronal survival and decreased microglia activation in the striatum of both male and female zQ175 mice. Together, our results indicate that mGluR5 antagonism can reduce HD neuropathology in both male and female zQ175 HD mice, but sex has a clear impact on the efficacy of the treatment and must be taken into consideration for future HD drug development.

Electroencephalogram (EEG) emotion recognition based on a hybrid feature extraction method in empirical mode decomposition domain combining with optimal feature selection based on sequence backward selection is proposed, which can reflect subtle information of multiscale components of unstable and nonlinear EEG signals and remove the reductant features to improve the performance of emotion recognition. The proposal is tested on DEAP dataset, in which the emotional states in the Valance dimension and Arousal dimension are classified by both ${K}$ -nearest neighbor and support vector machine, respectively. In the experiments, temporal windows of different length and three kinds of rhythms of EEG signal are taken into account for comparison, from which the results show that EEG signal with 1s temporal window achieves highest recognition accuracy of 86.46% in Valence dimension and 84.90% in Arousal dimension, respectively, which is superior to some state-of-the-art works. The proposed method would be applied to real-time emotion recognition in multimodal emotional communication-based humans–robots interaction system.

Purpose Numerous studies have reported that the long non-coding RNA colorectal neoplasia differentially expressed (CRNDE) plays important roles in the tumorigenesis, progression, and prognosis of various types of cancer. However, thus far, a systematic analysis of CRNDE in cancers of the digestive system has not been conducted. Thus, the aim of this meta-analysis was to explore the relationship between CRNDE expression and survival or the clinicopathological features of gastrointestinal cancer. Methods Eligible studies were collected from nine databases (ie, PubMed, Medline, Embase, Cochrane Library, Ovid, Science Citation Index Expanded, China Biology Medicine, Chinese National Knowledge Infrastructure, and Wanfang). The meta-analysis was conducted using the Stata SE.12 Software. The pooled hazard ratio (HR) or odds ratio (OR) with a 95% confidence interval (Cl) was used to assess the clinical value of CRNDE expression in gastrointestinal cancers. Results A total of 1,053 patients from nine articles were selected. The analysis provided evidence suggesting a significant negative correlation between high CRNDE expression and the rate of overall survival [HR=1.92, 95% CI (1.40-2.64), p 5 cm [OR=2.81, 95% CI (1.62-4.88), p

To ensure that people can replenish the right amount of water when they are short of it, an initiative service method based on the fuzzy analytical hierarchy process (FAHP) and context intention inference for the drinking service robot is proposed, in which the factors that affect people’s drinking demand including individual factors (e.g., physical activity, age, and gender) and environmental factors (e.g., temperature and humidity) are taken into account for drinking service. In addition, a two-level hierarchy structure for human intention together with intention degree is proposed, in which weights between context features and intention are calculated by FAHP, which imitates human’s subjective judgment process mathematically and mentally. Moreover, the relationship between human intention and their demands is established by a demand analysis model for providing satisfactory service of robots. Drinking service experiments are performed in a laboratory scenario using a humans–robots interaction system, from which the experimental results show that the resultant ${p}$ -value in Condition 1 is 0.455, and the resultant ${p}$ -value in Condition 2 is 0.09, and the averaged values of satisfaction feedback are 2.15 and 1.85 (satisfaction from 1 to 5 decreased in turn), respectively, approximately satisfied, which demonstrates the feasibility of the proposal.

The duration of wind storms over a threshold wind speed value is known to be an important parameter in determining damage and losses, with losses tending to increase with the duration. This is because peak pressures tend to increase with longer duration, many building components and cladding systems are vulnerable to different types of fatigue mechanisms, and the yielding of linear elastic materials in the plastic range depends on the number of load cycles. A hurricane model was used to examine the duration of high winds in the United States at Miami, Galveston, and Charleston with the goal of establishing duration statistics for hurricanes as a function of peak wind speed. It was found that the duration of high winds, defined as the time that the 10 min wind speeds are within 30% of the peak 10 min wind speed, had a significant variation with a range from tens of minutes to more than 20 h, depending on location. The median duration ranged from 1.5 to 4 h at the three locations, depending on location and the design wind speed level (i.e., the risk Category of the building). These results were used to establish a simple normalized model for wind speed as a function of time, which could be used together with the design wind speed to establish load cycles for design.

In the field of face recognition and analysis, eye state detection is an essential step, which is the prerequisite and breakthrough of drowsiness estimation and auxiliary driving. This paper presents an eye state detection method based on Weight Binarization Convolution Neural Network (WBCNN). The weight of the network is constrained by binarization, which can limit the weight to 1 or -1, reducing the power dissipation and internal storage considerably. The human eye state features which can be extracted by convolution neural network effectively, and binary network not only contributes to reducing the storage size of the model, but also accelerates the computation. Experiments on eye state detection were conducted on the Closed Eyes in the wild (CEW) and FER2013 Databases, from which the results show that our method achieved average test accuracy of 97.41% on CEW. We used the FER2013 facial expression database for pre-training, which can make up for the lack of CEW training samples. The computational speed of non-binary is slower than binary network. Moreover, less storage capacity is required by our method.

Three main tasks consist of calibrating design wind speed. These include obtaining high quality extreme wind speed records, selecting the most appropriate probabilistic model, and applying the best fitting method to estimate the distribution parameters. The last two aspects have critical impact on the calibrated design wind speeds and have been intensively studied periodically. However, data quality is still the primary factor that affects the reliability of the calibrated design wind speed. The data is typically screened and processed before carrying out extreme value analysis. This includes removing erroneous data and conducting standardization. Besides quality control and standardization, the total number of years of data and the sampling intervals of data in each recording day also need to be considered. The former concern, also known as sample size effect, is well acknowledged and revisited in a recent study. The later concern draws relatively few attentions. One recent study investigated the later concern by using some wind speed observations at ground level. As the sample size is limited, the effect of sample size and disjunct sampling could be mixed in their observation. Moreover, appreciation of the disjunct sampling from sampling theory was not investigated in their study. To better appreciate the impact of disjunct sampling on design wind speed calibration alone, the effect of sample size needs to be eliminated. This requires very long period wind speed records that are not available for historical records. Therefore, this study employs Monte Carlo technique to simulate long term wind speed samples. The simulated wind speeds are used to investigate the impact of disjunct sampling on the design wind speed and the combined effect of disjunct sampling and limited sample size on design wind speed. Effect of disjunct sampling appears in part of the period on the estimated return period wind speeds is also investigated.

Tropical cyclone wind-induced hazards for the eastern coastal built environments of India can be severe. The extreme cyclone winds can cause damage to structures and infrastructures and losses of lives and economies. The current building code of India provides design wind speeds for the eastern coastal cyclone-prone regions. These design wind speeds were determined without considering extreme wind speeds associated with different weather types, such as thunderstorms or cyclones. The cyclone simulation technique has not been considered to update the design wind speeds for India's eastern coastal cyclone-prone regions. Several previous studies used the regional maximum sustained wind speeds to derive the design level cyclone-induced wind speeds. This approach differs from advanced cyclone simulation techniques and provides overly conservatism. The effect of using the regional maximum sustained wind speeds of cyclones in estimating the design wind speeds was investigated quantitatively in this study. A fast-predictive cyclone wind hazard model was proposed to assess the cyclone wind hazards. This model used simple wind field modeling and directly applied the historical best track datasets. The performance of this model was validated by comparing the predicted design level tropical cyclone wind speeds for selected coastal cities in the USA and China to those provided by the local building code or reported in previous studies using advanced tropical cyclone simulation models. This fast-predictive model was used to calculate the peak cyclone wind speeds and predict the 50-year return period cyclone wind speeds for twenty eastern coastal cities in India. The predicted 50-year return period cyclone wind speeds using the fast-predictive model were compared with those predicted using the regional maximum sustained wind speeds and current code design wind speeds.

Wind hazard is one of the most severe natural hazards. Structures and infrastructure can be vulnerable to wind load effects due to extreme wind speeds. Mitigation and the reduction of wind-related risks of structures and infrastructures can be made by considering the wind load effects within the structural design process. Building design codes or standards for some countries in the Arabian Peninsula do not formally define the wind load effects. For countries with wind load provisions in their building codes and standards, the spatial resolution of design wind speeds may not be sufficient to cover many cities or areas. To date, there has not been a comprehensive study on the extreme wind hazards at the design level in the Arabian Peninsula. Extreme wind hazards have been conventionally evaluated by using historical surface observations. However, an investigation showed that many meteorological stations in the Arabian Peninsula cannot be used to evaluate the design wind speeds due to low data quality or insufficient sampling resolution. This study used the Weather Research and Forecasting (WRF) model to obtain data with a high spatial-temporal resolution. The simulated extreme wind speeds across the Arabian Peninsula were characterized statistically. Spatial distributions of the extreme wind speeds and their associated attributes were investigated. The simulated wind speeds were separated into convective event-induced wind speeds and synoptic wind speeds to obtain the design wind speeds. The convective wind events were identified using a statistical algorithm defining the threshold values of the Lifted Index and the Convective Available Potential Energy values. A numerical parametric cyclone model was used to simulate the cyclone-induced extreme wind speeds for the southern coastal regions of the Arabian Peninsula. The design wind speeds were evaluated by using the most appropriate probability distribution and preferred fitting method. Contour maps of various return period wind speeds were developed.

A probabilistic model for simulating tropical cyclone (TC) track from the genesis to lysis is developed based on historical best-track dataset for western North Pacific basin. The spatially varying model coefficients are determined through regression analysis. Tracks are simulated using the developed probabilistic model; statistics of the key parameters defining the TC track: the translation velocity, storm heading and, relative intensity that is a function of central pressure difference, are estimated at sites along the coastline using the simulated tracks. The statistics of the key parameters are compared with those estimated using historical tracks, indicating the adequacy of the developed empirical track model. The developed track model together with a well-established planetary boundary layer wind field model are subsequently used to assess the TC or typhoon wind hazard, in terms of the return period value of the annual maximum TC wind speed, for coastal region of the mainland China. The estimated wind hazard at selected sites is compared to that based on the circular sub-regional method. Comparison is also extended to the values recommended in Chinese design code at many sites, and the results from the surface wind observations at four sites. It is shown that the estimated typhoon wind hazard is consistent with that derived based on surface wind observations, and the mapped typhoon wind hazard near the coastal line is in good agreement with that presented in current design code.

This paper presents a concise method for determining the design wind loads for multi-row ground-mounted solar arrays, including both static and dynamic wind load coefficients compatible with the ASCE 7, based on a compilation of wind tunnel experiments conducted by RWDI using rigid pressure models. The proposed method addresses the well-established shortcomings of the ASCE 7–16 definition of ‘rigid structure’ based on the frequency of 1 ​Hz when applied to such arrays and the need identified in SEAOC PV2 (2017) that ground-mounted arrays with numerous repetitive structures shall consider vortex shedding and consequent dynamic resonant effects. Comparisons to other sources available in the technical literature have been made where possible, which are largely satisfactory, and an illustrative example is provided to assist practitioners in applying the proposed method. It is important to note that the method and data presented in this paper assume that wind-induced deflections are small, and thus, the structure is not flexible; flexible structures such as unrestrained single-axis trackers are also prone to aeroelastic effects and torsional instabilities, which are beyond the scope of this paper. Sources of uncertainty are discussed and, in an effort to minimize these uncertainties when predicting design wind loads, it is the authors’ hope that the dataset presented herein be augmented by other contributors to form the basis for codification.

This study aimed to determine the effect of excessive fluoride (F) on the morphological characteristics of the small intestine and the contents of serum cytokines in rats. A total of 48 3-week-old healthy female Sprague-Dawley rats were randomly divided into four groups (n = 12). The control group was given deionized distilled water, while the F treatment groups were treated with water containing 25, 50, and 100 mg F−/L. After 70 days of treatment, the duodenum, the jejunum, and the ileum were collected to measure the developmental parameters and the distribution of intestinal glycoproteins, goblet cells, and mast cells through Pannoramic Viewer, Periodic Acid-Schiff (PAS) staining, Alcian blue and periodic acid-Schiff (AB-PAS) staining, and toluidine blue staining, respectively. The contents of cytokines, namely, interleukin (IL)-1β, IL-2, IL-6, and tumor necrosis factor (TNF)-α, in serum were detected via enzyme-linked immunosorbent assay (ELISA). Results showed that the villus height, crypt depth, villus height to crypt depth ratio, goblet cells, glycoproteins, and mast cells of the small intestine significantly decreased (P

To ensure the efficiency of people's work while working long hours, an initiative service method with regard to degree of sleepiness for drinking service robot is proposed. It can recognize the degree of sleepiness and provide initiative service to increase the efficiency of people's work. Degree of sleepiness is defined as three levels by observer rating, which is supposed to be associated with human actions, environmental factors, and individual factors. In addition, a model of degree of sleepiness based on Finite State Machines (FSM) is introduced. The relationship between human demands and degree of sleepiness is established through demand analysis model by which the initiative service with regard to degree of sleepiness for drinking service robot is achieved. Experiments on real initiative drinking service are performed in a multimodal emotional communication based on human-robot interaction (MEC-HRI) system, from which the experimental results show that the time of initiative service is 8 minutes earlier than that without initiative service. In prospect, the proposal could be applied to other kinds of services such as health care, safety driving assistance, and other safety work assistance.

The small sample size of the annual maximum wind speed at a wind speed recording site causes uncertainty in the estimated return period of wind speed. The influence of this uncertainty on the estimated return period values of annual maximum wind speed and structural reliability is quantified in this study. The results show that the effect of statistical uncertainty due to limited sample size on the estimated return period value of the wind speed and structural reliability is largely reduced if the sample size is increased from 10 to 20. The implication of the results is discussed in terms of two alternative options to specify the factored design wind load: (i) a low return period for selecting nominal wind speed combined with a large wind load factor and (ii) a high return period for selecting nominal wind speed combined with unity wind load factor. It was concluded that option (i) is preferred to cope with sample size effect if the design in a region with statistically homogeneous wind climate; for code ...

The coastal region in mainland China experiences typhoon wind hazard and risk. Since historical surface observations are scarce and of short period, the hazard assessment is often carried out using the typhoon wind field and track models. For a few major cities in the coastal region, there are differences among the return period values of the annual maximum typhoon wind speed estimated by different studies and by the Chinese design code. The publically availability of the best track dataset released from China Meteorological Administration (CMA) provides an opportunity to potentially assess and validate some of the results. The present study provides probabilistic characterizations of typhoon tracks for a circular subregion around each of the nine considered cities located in the coastal region of mainland China by using the best track data from CMA. It applies the developed probability models for the tracks to estimate the typhoon wind hazard for the nine cities using a subregion approach. The results show that the estimated wind hazard is relatively insensitive to the size of the subregion, but it is strongly influenced by the adopted probability distribution model for the central pressure difference as the return period increases. The results also show that the code recommended return period values for some sites are lower than those obtained in this study by up to 8 % for the return period of 50 and 100 years.

Probability plotting positions are popular and used as the basis for distribution fitting and for inspecting the quality of the fit because of its simplicity. The plotting positions that lead to excellent approximation to the mean of the order statistics should be used if the objective of the fitting is to estimate quantiles. Since the mean depends on the sample size and is not amenable for simple to use closed form solution, many plotting positions have been presented in the literature, including a new plotting position that is derived based on the weighted least-squares method. In this study, the accuracy of using the new plotting position to fit the Gumbel distribution for estimating quantiles is assessed. Also, plotting positions derived by fitting the mean of the order statistics for all ranks is proposed, and an approximation to the covariance of the order statistics for the Gumbel (and Weibull) variate is given. Relative bias and root-mean-square-error of the estimated quantiles by using the proposed plotting position are shown. The use of the proposed plotting position to estimate the quantiles of annual maximum wind speed is illustrated.

The Gumbel model is often used to fit annual maximum wind speed or wind velocity pressure. The commonly used fitting methods include the method of moments, the method of maximum likelihood, the method of L-moments, and the Lieblein BLUE (i.e., generalized least-squares method (GLSM)). Previously, the coefficients of the estimators for the latter method have not been available for large sample size, and the relative performance of the GLSM to other fitting methods such as the method of L-moments is unknown. In this study, we evaluate these coefficients for a sample size up to 100, and identify trends in the calculated coefficients. The relative performance of commonly used fitting methods for the Gumbel distribution, including the GLSM, is evaluated in terms of efficiency, bias, and root-mean square error. We illustrate their application and impact on the estimated return period values of the annual maximum wind speed for 14 locations in Canada.

Relevance vector machine (RVM) is a machine learning algorithm based on a sparse Bayesian framework, which performs well when running classification and regression tasks on small-scale datasets. However, RVM also has certain drawbacks which restricts its practical applications such as (1) slow training process, (2) poor performance on training large-scale datasets. In order to solve these problem, we propose Discrete AdaBoost RVM (DAB-RVM) which incorporate ensemble learning in RVM at first. This method performs well with large-scale low-dimensional datasets. However, as the number of features increases, the training time of DAB-RVM increases as well. To avoid this phenomenon, we utilize the sufficient training samples of large-scale datasets and propose all features boosting RVM (AFB-RVM), which modifies the way of obtaining weak classifiers. In our experiments we study the differences between various boosting techniques with RVM, demonstrating the performance of the proposed approaches on Spark. As a result of this paper, two proposed approaches on Spark for different types of large-scale datasets are available.

Eight or nine tropical cyclones (TC) per year make landfall over mainland China and cause large typhoon wind speeds and economic loss. This study estimates the return period value of the annual maximum typhoon wind speed, vT, for a set of grid points in the coastal region of mainland China. vT can be used to characterize the typhoon’s wind hazard and to assign the wind load in design codes. The estimation uses a typhoon wind hazard model consisting of the TC track and wind field models. For the estimation, the development of track model for a circular subregion centered at each of the grid points is carried out by using the best-track dataset from China Meteorological Administration, and a well-accepted wind field model for simulating the TC is adopted. The spatial trends of the parameters controlling the track model are investigated, and the time histories of the wind speeds estimated by using the adopted wind field model are compared with those observed from two historical typhoon events. The es...

The interdecadal variability of the basic mode of global zonal-mean atmospheric circulation was analyzed with the monthly reanalysis data provided by NCEP/NCAR. The results indicate that the basic mode of global zonal-mean atmospheric circulation has significant interdecadal variability with a period of 20a. On the time scale about 20a, the change of zonal-mean temperature led the zonal-mean geopotential height by about 2 months, and led the zonal-mean flow by about 10 months. Furthermore, the change of zonal-mean geopotential height led the zonal-mean flow by about 8 months. The increase (decrease) of zonal-mean temperature caused the zonal-mean geopotential height descending (ascending) at high latitudes and ascending (descending) at middle and low latitudes; then further caused the zonal-mean westerly accelerating (decelerating) at middle and high latitudes and tropics, and westerly decelerating (accelerating) at polar regions and subtropics. On the 20a time scale, the signals of significant global warming from the end of the 1970s emerged firstly at the tropopause of the South Hemisphere, next at the lower troposphere over the South Hemisphere, and then the lower troposphere and the tropopause of the North Hemisphere.

The hurricane hazard modeling requires a hurricane wind field model and a hurricane track model, that are generally developed based on historical wind speed and track records. Several hurricane hazard models have been proposed for engineering applications; the model used to map the hurricane wind hazard shown in several editions of a U.S. national standard is extensively documented in open literature. A term, which is expressed as the product of the hurricane translation velocity and gradient of the wind velocity relative to the moving center of the vortex in the governing equation (i.e., fluid momentum equation) to model hurricane wind field, is neglected in various publications. However, the effect of using this approximation on the calculated wind field has not been elaborated. In the research reported in this paper, the effect of this approximation on the wind field is investigated through numerical analysis. Also, a possible simplification of the track model used to estimate the extreme hurri...