bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Scoping Review of the Prevalence and Correlates of Sexual Dysfunction in Adults with Substance use Disorders
Authors: Ghosh Abhishek , Kathiravan Sanjana , Sharma Kshitiz , Mattoo Surendra Kumar 
Published: December 2021

ABSTRACTBackgroundSubstance use may affect sexual functioning in both men and women. Comorbid sexual dysfunction adds to the clinical burden of substance use disorders (SUD).AimsThe broad aims were to identify research conduct, types of the available evidence, and research gaps in (i) estimating the incidence, prevalence, type, and severity of sexual dysfunction in adults with SUD; (ii) exploring correlates of sexual dysfunction in SUD.MethodsWe conducted systematic searches on PubMed, Google Scholar, and Embase for studies published in the English language between August 1954 and November 2020. We included prospective and cross-sectional observational studies that had examined the prevalence or incidence of any sexual dysfunction in adults of either gender with substance use disorders. Review articles and those with an exclusive focus on tobacco use disorders were excluded. The review was registered in PROSPERO.ResultsOur search identified 65 relevant articles, including five prospective studies. All the prospective studies and most of the cross-sectional studies (n = 40) were done among men and subjects with alcohol (n = 20) and opioid (n = 23) use disorders in clinical populations. Substance use and sexual dysfunction were assessed by a wide range of instruments. Prospective studies reported a prevalence of sexual dysfunction at 75% and 61% for alcohol and opioid use disorders, respectively. The prevalence of any sexual dysfunction in cross-sectional studies ranged between 15 and 100 percent. Erectile dysfunction was the most commonly studied and observed sexual dysfunction. Comorbidity and socioeconomic deprivation were consistently associated with a higher occurrence of sexual dysfunctions.StrengthsWe did not limit our review by the type of substances and year of publication. We adhered to the standards of conducting and reporting scoping reviews; hence, our review results should be replicable, transparent, and reliable.LimitationsThe wide clinical and methodological heterogeneity precluded a systematic review.ConclusionResearch gaps exist in women, non-clinical population, stimulants, and cannabis use disorders, and effect of treatment of SUD in sexual functioning. The quality of evidence is poor.
Decadal Variability of Winter Warm Arctic‐Cold Eurasia Dipole Patterns Modulated by Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation
Authors: Luo Binhe , Luo Dehai , Dai Aiguo , Simmonds Ian , Wu Lixin 
Published: December 2021

AbstractIn recent decades, the winter surface air temperature (SAT) anomaly in the Northern Hemisphere has exhibited a warm Arctic‐cold Eurasia (WACE) dipole pattern and this has undergone significant decadal variation. In this paper, the physical cause of the decadal variability of the WACE pattern is explored, and it is shown to be mediated by the phases of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Although the negative PDO (PDO−) or positive AMO (AMO+) favors the WACE pattern, the meridional structure of the pattern is significantly influenced by whether PDO− or AMO+ dominates. During PDO− (AMO+) phase, the winter‐mean WACE pattern shows an asymmetric dipole with weak (strong) warm anomaly over the Barents‐Kara Seas or BKS and strong (weak) cold anomaly over central Eurasia or Siberia, which corresponds to Ural blocking (UB) concurring with the negative (positive) phase of North Atlantic Oscillation in a winter‐mean field. The winter asymmetric WACE pattern is more strongly related to PDO− than AMO+. It is further found that an asymmetric sub‐seasonal WACE dipole pattern with strong (weak) warm anomaly over BKS and weak (strong) cold anomaly over Siberia is usually formed during the UB episode due to favored (suppressed) sub‐seasonal downward infrared radiation and turbulent heat flux over BKS during AMO+ (PDO−), which leads to a strong asymmetric dipole of the winter WACE pattern.
Using Timescales of Deficit and Residence to Evaluate Near‐Bottom Dissolved Oxygen Variation in Coastal Seas
Authors: Zhang Wenxia , Dunne John P. , Wu Hui , Zhou Feng , Huang Daji 
Published: December 2021

AbstractWe identify the local, vertical and lateral processes that cause bottom oxygen variation, and characterize timescales for each process using oxygen budget analysis based on a coupled physical‐biogeochemical model for the coastal seas in east China. Local oxygen deficit often occurs in the summer season due to the faster local consumption than the vertical replenishment in seasonal timescale. Lateral transport of oxygen‐rich ambient water replenishes local deficit of bottom dissolved oxygen. Competition between local deficit and lateral exchange determines seasonal hypoxia formation and sustainment. Short local consumption timescale is favorable for hypoxia formation, and transient hypoxia often forms when the local deficit and lateral exchange processes act on comparable timescales, such as the East China Sea in which the bottom hypoxia usually lasts for days. Extremely long lateral exchange timescale suggests that dissolved oxygen variation is predominantly controlled by local processes, and short local consumption timescale often causes increasingly severe seasonal hypoxia until the onset of the relaxation of local deficit, such as the bottom hypoxia in the Bohai Sea. Using these timescales to evaluate local deficit relative to vertical and lateral residence time and their variability is a convenient and potentially powerful general mechanistic framework to evaluate strategies to mitigate coastal hypoxia worldwide.
Impacts of Extreme Weather on Mercury Uptake and Storage in Subtropical Forest Ecosystems
Authors: Yuan Wei , Wang Xun , Lin Che‐Jen , Zhang Hui , Feng Xinbin , Lu Zhiyun 
Published: December 2021

AbstractAs climate change accelerates, extreme weather events become more severe and frequent. We analyzed the datasets of decade‐long observation (2005–2020) of mercury (Hg) stored in two subtropical evergreen forests to understand the impacts of extreme weather on the sequestration of atmospheric Hg in forest ecosystems. Results show a weak correlation between litterfall Hg and atmospheric Hg0 concentration. Droughts and snowstorms significantly disturb Hg accumulation in litterfall and soils. Litterfall Hg concentration and deposition both display an increasing trend during the period of extended droughts in 2011–2014, but a decreasing trend after droughts. This is caused by the water stress that influences the change of tree physiology and processes of foliage Hg0 uptake. Snowstorm damages large areas of canopy, which leads to substantial canopy epiphyte cover mixed into the forest floor, thus considerably increasing soil Hg concentrations. Over a decadal timescale, soil Hg variabilities are shaped by the combined effects of atmospheric Hg inputs and processes of organic soil mineralization mediated climatic factors. Our study highlights that the accelerated climate change increases the unpredictability of Hg accumulation in terrestrial ecosystems. Future studies are needed for better understanding the response of Hg biogeochemical cycling to climate change among different terrestrial biomes.
DNN‐aided read‐voltage threshold optimization for MLC flash memory with finite block length
Authors: Wang Cheng , Wei Kang , Kong Lingjun , Shi Long , Mei Zhen , Li Jun , Cai Kui 
Published: December 2021

AbstractThe error‐correcting performance of multi‐level‐cell (MLC) NAND flash memory is closely related to the block length of error‐correcting codes (ECCs) and log‐likelihood‐ratios of the read‐voltage thresholds. Driven by this issue, this paper optimizes the read‐voltage thresholds for MLC flash memory to improve the decoding performance of ECCs with finite block length. First, through the analysis of channel coding rate and decoding error probability under finite block length, the optimization problem of read‐voltage thresholds to minimize the maximum decoding error probability is formulated. Second, a cross‐iterative search algorithm to optimize read‐voltage thresholds under the perfect knowledge of flash memory channel is developed. However, it is challenging to analytically characterize the voltage distribution under the effect of data retention noise. To address this problem, a deep neural network (DNN)‐aided optimization strategy to optimize the read‐voltage thresholds is developed, where a multi‐layer perception network is employed to learn the relationship between voltage distribution and read‐voltage thresholds. Simulation results show that, compared with the existing schemes, the proposed DNN‐aided read‐voltage threshold optimization strategy with a well‐designed Low Density Parity Check (LDPC) code can not only improve the program‐and‐erase endurance but also reduce the read latency.
Research on driving behaviour assessment based on evidence theory in 5G‐VANET
Authors: Zhang Yang , Tie Ying , Liu Yun 
Published: December 2021

AbstractWith the rapid development of 5G and vehicular ad hoc network (VANET), the data fusion plays an increasingly important role in the driving behaviour assessment. However, the unreasonable distribution of conflicting evidence remains a significant issue for decision fusion based on evidence theory. By analysing the parameter information of driving behaviour recognition, this paper proposed a new weighted evidence combination approach to fuse the highly conflicting information. In short, the proposed combination method not only retains the excellent mathematical characteristics of Dempster's combination rule, but also fully considers the mutual relations between evidences and the influence of the characteristics of evidence body. Firstly, a new dissimilarity measure is put forward to quantify the conflict degree between the evidences. Furthermore, the uncertainty measure and internal conflict are adopted to determine the weight of each evidence. Based on the weighted averaging combination method, the reasonable combined results are obtained. According to the experimental results, the proposed method has better performance than the existing methods, and provides an effective solution for driving behaviour assessment.
Codesign of communication scheduling and controller of networked control systems
Authors: Zanma Tadanao , Kuribayashi Toru , Koiwa Kenta , Liu Kang‐Zhi 
Published: December 2021

AbstractNetworked control systems have received increasing attention from many researchers because of their vast potential. The insertion of communication networks in a controlled system brings network‐induced defects, which are mainly caused by limited network resources. This paper proposes a codesign of periodic communication scheduling and a controller using sparsity for efficient use of the network while improving initial control performance. The effectiveness of the proposed method is verified through two numerical simulations.
An adaptive two‐dimensional orthogonalization scheme for non‐linear digital canceller in full‐duplex radios
Authors: Cui Zhongpu , Ge Songhu , Li Yaxing , Guo Yu , Xing Jinling , Meng Jin 
Published: December 2021

AbstractIn this letter, an adaptive two‐dimensional orthogonalization (ATDO) scheme for non‐linear digital canceller is proposed to realize self‐interference (SI) suppression in full‐duplex radios. The proposed scheme consists of three parts. First, an adaptive lattice predictor is adopted to orthogonalize the input data over sample delay dimension. Then, a gradient‐based adaptive orthogonalizer is developed to further orthogonalize the basis functions established with predictor output over non‐linear order, and a new set of two‐dimension orthogonal basis functions is constructed consequently. Finally, a least mean square (LMS) model‐based parameter learning approach is utilized to implement the coefficients estimation with the newly established two‐dimension orthogonal basis functions. The proposed ATDO scheme provides an effective solution to track quickly time‐varying interference with high accuracy for real‐time communication system. Experimental results illustrate that the proposed scheme can efficiently improve the cancellation performance of non‐linear digital canceller, especially for higher order non‐linear distortion model compared to other algorithms in previous literatures.
Improving the energy efficiency of slightly inductive three‐phase three‐wire linear systems through single‐phase capacitors banks
Authors: Blasco Pedro A. , Montoya‐Mira Rafael , Diez José M. , Montoya Rafael , Garcerá Gabriel , Figueres Emilio 
Published: December 2021

AbstractRecent low‐voltage, three‐phase distribution networks carry inefficient power, which can be attributed to the reactive power, imbalance of linear loads, and increase in non‐linear loads. Researchers have mainly focused on developing active filters to improve the quality of electrical energy. However, in most cases, compensating for the reactive power is sufficient, considering cost and quality. Active filters are expensive, thus, passive compensators are more appealing. These devices are composed of single‐phase or three‐phase capacitor banks that act on the reactive power consumed by the load. The operation of these devices has been sufficiently validated owing to their long‐term use. For unbalanced power, compensators that contain coils are used. A methodology to obtain compensators comprising only single‐phase capacitors for the inductive reactive power consumed by the load is presented here; if designed appropriately, these compensators can compensate for a part of or the entire unbalanced power, resulting in greater efficiency in the transfer of electrical energy.
Fast outdoor hazy image dehazing based on saturation and brightness
Authors: Hu Daosong , Yang Yang , Li Bo , Tang Huiming , Xu Yu 
Published: December 2021

AbstractHaze usually limits the visibility and reduces the contrast of outdoor images. The removal of haze in a single image has always been a challenging problem. Recently, many methods have been proposed to effectively remove haze in harsh conditions. However, these methods fail to balance the dehazing effect and time consumption. This paper proposes a method based on HSV colour space to restore the visibility of uniform scattering medium. It can prevent the atmospheric light and transmission from being miscalculated. This method uses the brightness component of haze image to estimate the global atmospheric light, which reduces the influence of luminescent objects on atmospheric light estimation. Then, this paper deduces the estimation model of the saturation of scene radiance based on the atmospheric scattering model. In the meantime, according to the advantages and problems of the model, the fast estimation of the transmission is realized by using the stretching function. Finally, this paper solves the parameters in the model by iterative method. Since this method can estimate different media transmission for each pixel, better results can be obtained. The simulation results show that the algorithm is superior to the existing algorithms in terms of dehazing effect and time consumption.
Quaternion‐based improved cuckoo algorithm for colour UAV image edge detection
Authors: Liu Dujin , Pu Guolin , Wu Xiaoyan 
Published: December 2021

AbstractWith the extensive application of unmanned aerial vehicles (UAVs), there is an increasing demand for fast processing of coloured UAV images. The coloured UAV image pixels are usually represented by quaternion vectors with three bands of visible light corresponding to the three imaginary parts of the pure imaginary quaternion. Accordingly, the colour image edge points can be determined based on the quaternion polar coordinating the rotation principle. Here, a quaternion‐based improved cuckoo algorithm is proposed to perform fast processing for UAVs images. In particular, a novel guiding equation is used to optimize the positions of the improved cuckoo algorithm before the Levi flight. Furthermore, a novel disturbance equation is used to obtain a varied location for the next location after the Levi flight. Comprehensive experiments are conducted to evaluate the performance of the proposed solution. The experimental results showed that the proposed method significantly reduces the image processing time and remarkably improves the quality.
Heuristic approach for the multiobjective optimization of the customized bus scheduling problem
Authors: Liu Kaijun , Liu Jianming , Zhang Jingwei 
Published: December 2021

AbstractCustomized bus is a typical demand‐responsive transit (DRT) service that allows passengers to customize their bus route on demand and be picked up and dropped off at their desired location. A set of ride requests sent at various times by geographically dispersed passengers are operated in real time by the controller and then assigned to the shared bus with the assurance of maintaining the minimum vehicle and driver costs, which introduces a new challenge to scheduling. In this paper, a mixed integer linear programming (MILP) model is presented to solve the customized bus scheduling problem. To quickly generate satisfactory scheduling solutions in the case of single‐ and multi‐depots, a heuristic multi‐objective optimization algorithm based on preemptive scheduling is proposed, which can converge to the optimal solution among a set of vehicle blocks (consecutive trips by one bus). A real‐world customized bus scheduling problem from the public transport company of Chengdu, China that contains 2,000‐trip instances operated on a day is used to demonstrate that the proposed approach reduces total operating costs by 30.51% and 30.71%, compared with the simulated annealing algorithm and genetic algorithm, respectively.
Dynamic driving intention recognition of vehicles with different driving styles of surrounding vehicles
Authors: Zhang Hua , Zhang Zhiyuan , Liang Jun 
Published: December 2021

AbstractDriving behaviour of surrounding vehicles have impacts on the security of ego vehicle. However, many vehicles do not use the turn signal in advance as a warning when changing lanes, which often leads to traffic accidents. Therefore, in the case of Internet of Vehicles (IoV) technology has not been popularized, recognizing the driving intention of surrounding vehicles timely and accurately through effective method is of great significance to ego vehicle. In this paper, a dynamic driving intention recognition method for surrounding vehicles based on adaptive multi‐dimension continuous Gaussian mixture‐HMM (AMCGM‐HMM) is proposed. Considering that driving styles of surrounding vehicles are different, a feature‐based multi‐dimensional time series clustering algorithm is adopted to cluster the lane changing data samples and the results are used as the input of AMCGM‐HMM. Parameters that may affect the recognition accuracy are optimized by multi‐objective particle swarm optimization (MOPSO) algorithm to realize the adaptive of the method. The proposed method is verified on NGSIM dataset, and the application of this model is tested on the PreScan simulation platform combined with adaptive cruise control (ACC) system. Experimental results show that the proposed method can identify the driving intention of surrounding vehicles in advance and has high accuracy.
Research on power system transient stability with wind generation integration under fault condition to achieve economic benefits
Authors: Mastoi Muhammad Shahid , Tahir M. J. , Usman Muhammad , Wang Delin , Zhuang Shenxian , Hassan Mannan 
Published: December 2021

AbstractFor a few decades, electric power growth and demand have increased globally. To fulfil this demand, distribution generators (DGs) have been installed in the power system. To get numerous benefits such as comprising reduction of power losses, improvement of (voltage, current, rpm) transient stability, leads to economic benefits. DGs integration in the distribution power system (DPS) was reported as an optimal generator placement (OGP) problem to maximize these benefits. This paper performs wind turbine (WT) integration while considering the internal generator's (rpm) transient stability under fault conditions. A power loss index (PLI) method is implemented to select potential candidate buses for generator placement. A self‐sorting analytical approach (SSA) is also used to determine the optimal bus and WT size. The IEEE 14‐bus DPS is used as the OGP test system to demonstrate the proposed method's effectiveness in terms of power losses reduction, system transient stability, and economic benefits. The IEEE 14 Bus system was considered using MATLAB with a 3.2 GHz processor to perform the said approach. WT integration suggested in case‐2 results in a 65.80% power losses reduction, which leads to a 60.88% enhancement of economic benefits of the DPS.
Adaptive control strategy of solid state transformer with fast dynamic response and enhanced balance performance
Authors: Liu Zhi , Li Shuaihu , Xiao Fan , Wang Tingting , Cao Yijia , Li Yong , Zhang Xizhuo 
Published: December 2021

AbstractSolid state transformer (SST) is designed as a power transmission device between AC grids and DC grids. However, the power fluctuation causes unbalanced power sharing among dual active bridge (DAB) converters and large voltage fluctuations on dc buses. Here, an adaptive virtual impedance control (AVIC) strategy is proposed to improve the balance performance of SST. Adaptive virtual impedance controller gets the same dynamic response for DAB converters, which matches dynamic impedance of DAB converters. Thereby the power balance can be achieved even the load changes. Meanwhile, an adaptive feedforward control scheme is proposed to reduce the influence of load fluctuation on DC bus voltage. The adaptive feedforward scheme also considers the parameter mismatch, thereby the balance of SST will not be destroyed. Moreover, the balanced power sharing achieved by adaptive controller eliminates the difference between actual transmission power and compensation power in each rectifier, which further suppresses the intermediate capacitor voltage fluctuations. Finally, simulation and StarSim experimental results verified the correctness and effectiveness of the proposed control strategy.
Power system inertia estimation method based on maximum frequency deviation
Authors: Wang Baocai , Sun Huadong , Li Wenfeng , Yang Chao , Wei Wei , Zhao Bing , Xu Shiyun 
Published: December 2021

AbstractIn order to solve the problem that the inertia estimation method based on the rate of change of frequency (RoCoF) is only applicable to the centre of inertia (COI) frequency, a novel inertia estimation method is proposed based on the maximum frequency deviation. This method utilizes the property that the maximum frequency deviation of each generator is basically consistent and easy to obtain. Firstly, the inertia support power of the system is quantified according to the disturbance power and frequency, and then the inertia support energy of the disturbance process is obtained. Finally, the system inertia is estimated by the ratio of the inertia support energy to the maximum frequency deviation. The proposed estimation method is suitable for non‐COI frequency, which makes it unnecessary to obtain the COI frequency and RoCoF. On this basis, a simplified estimation method is proposed based on the linearization of regulation power, which improves the estimation accuracy and simplifies the estimation process. According to the proposed method, the governor test data is used to estimate, which increases the estimation times and provides more information for system stable operation. The effectiveness and accuracy of the proposed method are validated by some cases.