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Leaf area index (LAI) assessment methods relying on physical and empirical models are considered to be the most commonly used method at present, but their estimation efficiency and accuracy are deficient. Although the hybrid model of these two methods can address these issues, a poor coupling mechanism can easily occur. Given that, a PROSAIL model coupling particle swarm optimization (PSO) neural network (NN) algorithm (PSO-NN-PROSAIL model) was introduced to invert the winter wheat LAI (WWLAI) at five distinct growth stages. The Xiangfu District in the east of Kaifeng City, Henan Province was served as the study region. Based on the measured WWLAI data at varying stages and GF-1 WFV satellite images, the initial analysis focused on assessing the PROSAIL model's sensitivity in simulating vegetation canopy reflectance. It then calculated six vegetation index models according to the wavelength reflectance of GF-1 WFV and analysed their correlation with LAI to select the input parameters that could be used in the model. Normalized differential vegetation Index (NDVI) and ratio vegetation Index (RVI) as well as vegetation canopy reflectance were employed as input parameters to invert the WWLAI by adopting the PSO-NN-PROSAIL model. The experimental results showed the following: (1) In the vegetation index model, the determination coefficient (R2) of NDVI and RVI was greater than 0.68, implying that NDVI and RVI might serve as input factors for the proposed model in this paper; (2) LAI and chlorophyll a + b content (Cab) were most sensitive to the PROSAIL model in near-infrared and visible light bands; and (3) the PSO-NN-PROSAIL model possessed better LAI inversion accuracy. In summary, the model proposed in this paper provided a technical reference for rapid and accurate remote sensing monitoring of WWLAI. The optimization technology of particle swarm optimization algorithm is integrated into the neural network, and the weight of the neural network is adjusted by its fitness function transformation and inertia weight. By integrating prior knowledge into the inversion of crop leaf area index constructed by machine learning and radiative transfer model, the ill-posed problem of physical model inversion has been improved. [ABSTRACT FROM AUTHOR]

To address the problems of slow detection speed and low accuracy commonly found in cigarette factory warehouse workshops when detecting tobacco moth, a visual detection method for tobacco moth in cigarette factories based on improved lightweight YOLOv5s was developed. The method utilizes the correlation and redundancy between feature maps to design the EESP-Ghost module, and uses this module as the basis for designing a double-attention Ghost-bneck block incorporating an efficient spatial pyramid, which is introduced into the YOLOv5s model to achieve lightweighting of the deep neural network model while improving the detection accuracy. The method is used for validation experiments on the tobacco moth dataset. The results showed that the method improved the average accuracy by 4.37% with only 49.88% of the original YOLOv5s parameter count. When the tobacco moth adhering to the sticky board was detected in a real detection scenario, the method has high detection confidence and correct detection number, which could realize the high-precision real-time detection of the tobacco moth in the cigarette factory, and provide a guarantee for the effective control of the tobacco moth. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) has attracted strong interest since AlphaGo beat human professionals, and its applications in stock trading are widespread. In this paper, an enhanced stock trading strategy called Dual Action and Dual Environment Deep Q-Network (DADE-DQN) for profit and risk reduction is proposed. Our approach incorporates several key highlights. First, to achieve a better balance between exploration and exploitation, a dual-action selection and dual-environment mechanism are incorporated into our DQN framework. Second, our approach optimizes the utilization of storage transitions by utilizing independent replay memories and performing dual mini-batch updates, leading to faster convergence and more efficient learning. Third, a novel deep network structure that incorporates Long Short-Term Memory (LSTM) and attention mechanisms is introduced, thereby improving the network's ability to capture essential features and patterns. In addition, an innovative feature selection method is presented to efficiently enhance the input data by utilizing mutual information to identify and eliminate irrelevant features. Evaluation on six datasets shows that our DADE-DQN algorithm outperforms multiple DRL-based strategies (TDQN, DQN-Pattern, DQN-Vanilla) and traditional strategies (B&H, S&H, MR, TF). For example, on the KS11 dataset, the DADE-DQN strategy has achieved an impressive cumulative return of 79.43% and a Sharpe ratio of 2.21, outperforming all other methods. These experimental results demonstrate the performance of our approach in enhancing stock trading strategies. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) inversion accuracy of the water cloud model (WCM) based on the SAR images is low. The main reason is that the WCM model assumes two independent contributions from plant and soil surfaces, without taking into account their interactions. Based on this, this study proposes an efficient LAI estimation method that combines the advanced integral equation model (AIEM) and modified water cloud model (MWCM). Images collected by GaoFen-3 synthetic aperture radar (GF-3 SAR) in the Xiangfu area in the east of Kaifeng City, Henan Province, are processed with a modified SAR-BM3D method and used as test data of the proposed method. The proposed AIEM-MWCM method that combines the AIEM and MWCM models is employed to perform the remote sensing inversion of winter wheat LAI throughout the growth cycle. The results show that the fitting accuracy of winter wheat LAI in the five growth stages achieved by the proposed AIEM-MWCM method inversion is better than that of the Dubois-MWCM model. The R2 value of the proposed method is higher than 0.8, and its root mean squared error (RMSE) is lower than 0.3. [ABSTRACT FROM AUTHOR]

Annual monitoring of the spatial distribution of cultivated land is important for maintaining the ecological environment, achieving a status quo of land resource management, and guaranteeing agricultural production. With the gradual development of remote sensing technology, it has become a common practice to obtain cultivated land boundary information on a large scale with the help of satellite Earth observation images. Traditional land use classification methods are affected by multiple types of land cover, which leads to a decrease in the accuracy of cultivated land mapping. In contrast, although the current advanced methods (such as deep learning) can obtain more accurate cultivated land mapping results than traditional methods, such methods often require the use of a massive amount of training samples, large computing power, and highly complex model tuning processes, increasing the cost of mapping and requiring the involvement of more professionals. This has hindered the promotion of related methods in mapping institutions. This paper proposes a method based on time series vector features (MTVF), which uses vector thinking to establish the features. The advantage of this method is that the introduction of vector features enlarges the differences between the different land cover types, which overcomes the loss of mapping accuracy caused by the influences of the spectra of different ground objects and ensures the calculation efficiency. Moreover, the MTVF uses a traditional method (random forest) as the classification core, which makes the MTVF less demanding than advanced methods in terms of the number of training samples. Sentinel-2 satellite images were used to carry out cultivated land mapping for 2020 in northern Henan Province, China. The results show that the MTVF has the potential to accurately identify cultivated land. Furthermore, the overall accuracy, producer accuracy, and user accuracy of the overall study area and four sub-study areas were all greater than 90%. In addition, the cultivated land mapping accuracy of the MTVF is significantly better than that of the maximum likelihood, support vector machine, and artificial neural network methods. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop stable microsatellite markers and evaluate the genetic background of cultivated Sargassum fusiforme. Based on the transcriptome data obtained by high-throughput sequencing, eleven polymorphic microsatellite markers were developed using four S. fusiforme populations from China. One cultivated population was from Dongtou (DT) and three wild populations were from Muye Island (MY), Pingyu Island (PY) and Nanji Island (NJ). The cultivated S. fusiforme had the highest genetic diversity, with 90.91% polymorphic loci and Shannon's information index (I) of 0.606, which were much higher than those of the wild populations (I = 0.425). The four populations were divided into two groups through a structure analysis. DT, PY and NJ were clustered into a group, and MY was an almost completely separate group. Both the structure and principal coordinates analysis showed that DT and PY had the lowest genetic differentiation, suggesting that the parents of the breeding population in Dongtou partly come from Pingyu Island. The observed heterozygosity of NJ was much higher than expected, indicating that the NJ wild resource was greatly affected by the environment. These eleven microsatellite markers could provide additional markers for germplasm resource evaluations and facilitate genetic analyses of the S. fusiforme population. [ABSTRACT FROM AUTHOR]

Background: Dulong (Drung people) are one of the ethnic minorities of China, consisting of a small population living in remote and mountainous regions with limited facilities. Over the years, the Dulong have maintained their livelihood by collecting wild medicinal and edible plants. Therefore, through their experience and understanding, they had accumulated sufficient traditional knowledge about local plant resources. Since ancient times, wild edible plants have been essential to the food security of the Dulong people. However, there is almost no comprehensive report available on WEPs consumed by the Dulong people. The objectives of this study were to: (1) make a systematic study of WEPs used by Dulong people, (2) record traditional knowledge related to WEPs, (3) analyze multiple uses of WEPs, and (4) evaluate species with significant cultural significance to Dulong people. Methods: Ethnobotanical survey including free listing, semi-structured interviews, key informant interviews and participatory observations was conducted in Dulongjiang Township, Gongshan County, Yunnan Province, Southwest China. A total of 127 informants were selected using the snowball method and information about WEPs, including vernacular name, food categories, parts used, mode of consumption, collection season, and other local uses were collected. The RFC and CFSI were calculated to identify the most culturally significant WEPs. One-way analysis of variance was performed to evaluate whether the four reference variables (gender, age, occupation, and education) significantly influenced the number of plant species mentioned by the respondents. Results and discussion: A total of 148 species of WEPs consumed by the Dulong people belonging to 58 families were collected, including wild vegetables (71), wild fruits (52), staple food substitutes (15), spices (7), nuts (4), tea substitute (2), liquor making materials (3) oils and fats (3), and culinary coagulants (1). WEPs are used in a number of different ways, including as fuelwood, feed, and medicine. Food substitute plants accounted for the majority of the top 27 wild food plants identified by RFC and CFSI. It was observed that farmers have more knowledge of WEPs, and moderate education level informants reported less WEPs used. Conclusion: The WEPs used by the Dulong people are diverse and abundant in the Dulongjiang region. In the future, WEPs such as Maianthemum atropurpureum, Caryota obtusa, Cardiocrinum giganteum, and Angiopteris esculenta with economic potential can be developed to provide a source of income for the residents. More studies of the nutritional value, chemical composition, and biological activities of WEPs are needed. The demands and development of local communities can be realized under the premise of protecting WEPs and the associated traditional knowledge. More attention should be paid to the value of WEP and underutilized plants during future rural development. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is an important agroecological physiological parameter affecting vegetation growth. To apply the genetic algorithms neural network model (GANNM) to the remote sensing inversion of winter wheat LAI throughout the growth cycle and based on GaoFen-3 Synthetic aperture radar (GF-3 SAR) images and GaoFen-1 Wide Field of View (GF-1 WFV) images, the Xiangfu District in the east of Kaifeng City, Henan Province, was selected as the testing region. Winter wheat LAI data from five growth stages were combined, and optical and microwave polarization decomposition vegetation index models were used. The backscattering coefficient was extracted by modified water cloud model (MWCM), and the LAI was obtained by MWCM inversion as input factors to construct GANNM to invert LAI. The root mean square error (RMSE) and determination coefficient (R2) were used as evaluation indicators of the model. The fitting accuracy of winter wheat LAI in five growth stages by GANNM inversion was better than that of the BP neural network model; the R2 was higher than 0.8, and RMSE was lower than 0.3, indicating that the model could accurately invert the growth status of winter wheat in five growth stages. [ABSTRACT FROM AUTHOR]

We study finite maturity American-style stock loans under a two-state regime-switching economy. We present a thorough semi-analytic discussion of the optimal redeeming prices, the values and the fair service fees of the stock loans, under the assumption that the volatility of the underlying is in a state of uncertainty. Numerical experiments are carried out to show the effects of the volatility regimes and other loan parameters. [ABSTRACT FROM AUTHOR]

This paper studies a robust portfolio optimization problem under a multi-factor volatility model. We derive optimal strategies analytically under the worst-case scenario with or without derivative trading in complete and incomplete markets and for assets with jump risk. We extend our study to the case with correlated volatility factors and propose an analytical approximation for the robust optimal strategy. To illustrate the effects of ambiguity, we compare our optimal robust strategy with the strategies that ignore the information of uncertainty, and provide the welfare analysis. We also discuss how derivative trading affects the optimal strategies. Finally, numerical experiments are provided to demonstrate the behavior of the optimal strategy and the utility loss. [ABSTRACT FROM AUTHOR]

In this paper, a PDE (partial differential equation) based approach is presented to price weather derivatives with the market price of risk extracted from the utility indifference valuation. Assuming that the underlying temperature follows an Ornstein–Uhlenbeck process, the PDEs associated with the utility indifference valuation are established and then solved numerically using a one-sided finite difference scheme. The solution procedure is validated through numerical experiments for the utility indifference futures prices, and then applied to price more complicated weather derivatives such as options. [ABSTRACT FROM AUTHOR]

One of the prominent alternating direction implicit (ADI) schemes for numerically pricing financial options, the modified Craig–Sneyd scheme, is put to test for its reliability and efficiency for solving non-trivial problems with empirical market data. The Heston equation for pricing foreign exchange options of European style, a two-dimensional convection–diffusion–reaction equation with a mixed derivative term, is numerically solved for various parameter values observed in the market by employing the said scheme. Numerical stability and convergence issues of this scheme is compared with another popular Hundsdorfer–Verwer ADI scheme. From among a total of 56 options on 8 currency pairs, it is observed that some interesting ones for which the so-called Feller condition is strongly violated, create additional computational challenges. Suggestions on successful implementation of the MCS scheme are made in order to tackle these challenging test cases. [ABSTRACT FROM AUTHOR]

The influences of stocking density on stereotypic behavior, fecal cortisol and the musk secretion of captive Alpine musk deer (Moschus chrysogaster) were studied in the Xinglongshan Musk Deer Farm (XMDF) of Xinglongshan National Nature Reserve in Gansu Province of Northwest China from the 1st November to the 30th December 2020. The behavior of 26 captive male musk deer was recorded using focal animal sampling and all-occurrence recording, while radioimmunoassay was used to determine fecal cortisol and testosterone levels, and the muscone content was determined by gas chromatography-flame ionization detection (GC-FID). The results showed that the stereotypy behavior of individuals in high stocking density group (HDG) was more frequent (88.89%) and lasted longer (8.4 ± 1.0%) than of individuals in low density group (LDG) (50% and 4.2 ± 1.7%, respectively) (p < 0.05). The fecal cortisol level of HDG individuals (60.19 ± 5.83 ng g− 1) was significantly higher than that of LDG musk deer (36.34 ± 4.77 ng g− 1) (p < 0.05). There was no difference in muscone content, musk secretion and testosterone level between HDG and LDG individuals (p > 0.05). In musk deer farming of XMDF, the stocking density significantly influenced the health of captive Alpine musk deer, but had no significant impact on the musk secretion. [ABSTRACT FROM AUTHOR]

In this paper, we propose an integral equation approach for pricing an American-style Parisian up-and-out call option under the Black–Scholes framework. The main difficulty of pricing this option lies in the determination of its optimal exercise price, which is a three-dimensional surface, instead of a two-dimensional (2-D) curve as is the case for a “one-touch” barrier option. In our approach, we first reduce the 3-D pricing problem to a 2-D one by using the “moving window” technique developed by Zhu and Chen (2013, Pricing Parisian and Parasian options analytically. Journal of Economic Dynamics and Control, 37(4): 875-896), then apply the Fourier sine transform to the 2-D problem to obtain two coupled integral equations in terms of two unknown quantities: the option price at the asset barrier and the optimal exercise price. Once the integral equations are solved numerically by using an iterative procedure, the calculation of the option price and the hedging parameters is straightforward from their integral representations. Our approach is validated by a comparison between our results and those of the trusted finite difference method. Numerical results are also provided to show some interesting features of the prices of American-style Parisian up-and-out call options and the behaviour of the associated optimal exercise boundaries. [ABSTRACT FROM AUTHOR]

The valuation of perpetual timer options under the Hull–White stochastic volatility model is discussed here. By exploring the connection between the Hull–White model and the Bessel process and using time-change techniques, the triple joint distribution for the instantaneous volatility, the cumulative reciprocal volatility and the cumulative realized variance is obtained. An explicit analytical solution for the price of perpetual timer call options is derived as a Black–Scholes–Merton-type formula. [ABSTRACT FROM AUTHOR]

We derive an analytical solution for the value of Parisian up-and-in calls by using the “moving window” technique for pricing European-style Parisian up-and-out calls. Our pricing formula can be applied to both European-style and American-style Parisian up-and-in calls, due to the fact that with an “in” barrier, the option holder cannot do or decide on anything before the option is activated, and once the option is activated it is just a plain vanilla call, which could be of American style or European style. [ABSTRACT FROM PUBLISHER]

A pot culture experiment was conducted in soils with a 3-, 5-, or 10-year history of continuous cropping. Results showed that with increasing years of continuous cropping, biomass, soil and plant analyzer development (SPAD) readings, root activity, superoxide dismutase (SOD) activity, and malondialdehyde (MDA) content gradually decreased. After bio-organic fertilizer (BOF) application, biomass, SPAD readings and root activity, SOD activity, and MDA content gradually increased compared to controls. Similarly, catalase (CAT) and guaiacol peroxidase (POD) activity decreased with increasing years of continuous cropping, and increased substantially in BOF-treated soil compared to the control soil. The diversity and richness of soil bacterial community declined, while those of fungal community increased as continuous cropping increased. BOF application led to substantial increases in quantities of soil rhizosphere bacteria and actinomycetes and significant decreases in quantities of soil fungi. The soil bacterial community showed the greatest changes, whereas the fungal community showed the fewest changes. [ABSTRACT FROM AUTHOR]

In this paper, for solving large sparse vertical linear complementarity problems, the modulus-based synchronous multisplitting iteration method is established. Convergence theorems of the proposed method are given, which are shown to generalize and improve the existing results of the serial method. Numerical tests by OpenACC technique are given to show the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The ellipsoid shape model plays an important role in physical research on asteroids. However, its symmetric structure cannot practically simulate real asteroids. This article applies a general shape model, named the cellinoid, instead of the ellipsoid model to simulate the asymmetric shape of asteroids. The cellinoid shape model consists of eight octants of ellipsoids having different semi-axes, with the constraint that adjacent octants must have two equal semi-axes in common. Totally, the shape of the cellinoid model is controlled by six parameters, not three as in the case of the shape of the ellipsoid. Using this shape model, the brightness of asteroids observed from the Earth can be fitted numerically by the surface triangularization of the cellinoid. The Levenberg-Marquardt algorithm is also employed here to solve a nonlinear minimization problem. Owing to the asymmetric shape of the cellinoid, the physical parameters of asteroids, such as the rotation period and pole orientation, can be fitted more accurately than in the case of the ellipsoid model. Finally, this is confirmed numerically by applying the shape to both synthetic light curves and real light curves of asteroids. Additionally, the center of mass and moment of inertia of the cellinoid are analyzed explicitly. [ABSTRACT FROM AUTHOR]

• American option with transaction costs analysed through utility maximization. • Effect of transaction costs on the option price and optimal exercise boundary. • A comprehensive study of American option writing price with transaction costs. • Sensitivity analysis of optimal exercise boundary to option parameters. American option pricing plays an essential role in quantitative finance and has been extensively studied in the past. However, how transaction costs affect the American option price, particularly the most important feature of American options, the optimal exercise price, is much less investigated. It is primarily because such a study must be conducted under an incomplete market, which presents additional difficulties on top of an already difficult nonlinear mathematical problem. This paper attempts to provide a supplement study in this area by analyzing the optimal exercise price of an American option in addition to the option price itself in the presence of transaction costs through a utility-based approach. With a computationally efficient numerical scheme, we are able to demonstrate clearly how the optimal exercise price should be calculated and consequently how the option prices for the buyer and writer as well as the early exercise decision are affected by the inclusion of transaction cost. [ABSTRACT FROM AUTHOR]

Pricing options in a market with transaction costs is an important research topic in quantitative finance. There are basically two categories of approaches to deal with transaction costs. One is discrete hedging strategies under the Black–Scholes framework, another is utility indifference approaches. Hedging approaches are easy to implement, but preference-independent, whereas utility indifference approaches incorporate risk preferences, in general involving lengthy calculations. In a market with transaction costs, trading stocks involves risk so investors' risk preferences must be taken into consideration. In this paper, we price European options with proportional transaction costs using a utility indifference approach which updates the fraction of one's total wealth in the risky asset at regular intervals. Our HJB equation for the portfolio without option is two-dimensional instead of three-dimensional as in standard utility indifference approaches. Since the HJB equations could only be solved by a numerical method, our approach provides saving of computing time. Results from our numerical experiments via the finite difference method are presented to illustrate the effects of key option parameters on option prices. [ABSTRACT FROM AUTHOR]

As the number of observatories located on the surface of Earth is increasing largely in decades more and more photometric data of asteroids is observed to make the research about their various physical and chemical characteristics. Compared with hundreds of thousands of asteroids found up to now, rare hundreds of three-dimensional shape models of asteroids have been built from the tremendous photometric data with incessant observations, i.e. lightcurves. For some specific asteroid already with many observed lightcurves, the unceasing observation is not too much valuable, nevertheless an additional lightcurve observed in a request viewing aspect can refine the shape model and other related parameters. This article taking the asteroid (6) HEBE for example, attempts to introduce a method to make the observation plan by combining the request of the shape model and the orbital limitation of asteroids. Through analyzing the distribution of lightcurves of (6) HEBE, small cabins without any lightcurve data are found, which can be filled by new observations at some specified dates when the positions of Asteroid, Sun, Earth are limited as the request geometry. [ABSTRACT FROM AUTHOR]

Abstract: A standing wave field of ultrasound was established in the designed standing wave tube. The enhancement of ultrasound irradiation on desalting and dewatering process of LU-NING pipeline oil was studied. The results showed that the best conditions of the oil pretreatment was: adding 30mg/L demulsifier, injecting 5% (v.) wash water, irradiating the crude oil 5min by 10kHz ultrasound (intensity 0.38W/cm2, standing wave field), settling for 90min. The final results of salt and water contents were 3.851mg/L and 0.37%, respectively. The effect of standing wave field combined with demulsifier was better than that of the demulsifier only. High temperature (80°C) in the process was better than low temperature. Salt balance study showed that the key of desalting was: the wash water and the oil should be mixed sufficiently to extract the salts into the water as more as possible, the water added in should be provided to be separated out. If one stage of desalting process could not achieve the norm, two stages of desalting process should be considered. [Copyright &y& Elsevier]

Abstract: The ultrasonic irradiation for crude oil pretreatment to enhance desalting process was investigated. The intensity and irradiation time of ultrasound were studied. The settling time and the temperature of treatment for crude oil were also studied. Micrographs in this paper showed that the sizes of water drops were enlarged by more than 30% after the proper ultrasonic irradiation. The crude oil was pretreated for 5min at 80°C in the standing-wave field with frequency of 10kHz and with ultrasonic intensity of 0.38Wcm−2. After the pretreatment, the dewatering rate and desalting rate were up to 92.6% and 87.9%, respectively in 90min of settling time. The resulting final salt content of 3.85mgL−1 is acceptable for refinery. [Copyright &y& Elsevier]

Abstract: In this paper, a simple dogleg algorithm for solving new conic model subproblems is proposed, and a quasi-Newton method based on the simple dogleg algorithm is developed. Then the global convergence of the method under some reasonable conditions is established. Numerical experiment shows that this method may be superior to the corresponding method with a quadratic model. [Copyright &y& Elsevier]

Abstract: The dual reciprocity boundary element method employing the step by step time integration technique is developed to analyse two-dimensional dynamic crack problems. In this method the equation of motion is expressed in boundary integral form using elastostatic fundamental solutions. In order to transform the domain integral into an equivalent boundary integral, a general radial basis function is used for the derivation of the particular solutions. The dual reciprocity boundary element method is combined with an efficient subregion boundary element method to overcome the difficulty of a singular system of algebraic equations in crack problems. Dynamic stress intensity factors are calculated using the discontinuous quarter-point elements. Several examples are presented to show the formulation details and to demonstrate the computational efficiency of the method. [Copyright &y& Elsevier]

Discusses the emplacement timing of granitic plutons at Chaxinzi, Xiaoweishahe and Longfou in the Tonghua area, south of Jilin Province. The results of single-grain zircon U-Pb dating, which show these plutons formed in the Triassic period with ages of 203–217 Ma; Geological and geochemical characteristics of the plutons, which consist of quartz diorite and granite; Evidence of partial melting in the mafic lower crust and thickened crust with garnet as the residue in the source; How the protoliths are different despite having the same emplacement age; Indication that these plutons are petrologically different from the coeval granites in the Xingmeng (Xing’an–Mongolian) to Jihei (Jilin–Heilongjiang) orogenic belt in the north; Suggestion that their formation was related to theDabie–Sule ultrahigh-pressure collisional orogenesis; Association with the first rapid exhumation of the ultrahigh-pressure metamorphic rocks and emplacement of the post-collisional granites.

In this paper, a two-step iteration method was established which can be viewed as a generalisation of the existing modulus-based methods for vertical linear complementarity problems. The convergence analysis of the proposed method is presented, which can enlarge the convergence domain of the parameter matrix compared to the recent results. Numerical examples show that the proposed method is efficient with the two-step technique and confirm the improvement of the theoretical results. [ABSTRACT FROM AUTHOR]

Algorithmic trading is playing an increasingly important role in the financial market, achieving more efficient trading strategies by replacing human decision-making. Among numerous trading algorithms, deep reinforcement learning is gradually replacing traditional high-frequency trading strategies and has become a mainstream research direction in the field of algorithmic trading. This paper introduces a novel approach that leverages reinforcement learning with human feedback (RLHF) within the double DQN algorithm. Traditional reward functions in algorithmic trading heavily rely on expert knowledge, posing challenges in their design and implementation. To tackle this, the reward-driven double DQN (R-DDQN) algorithm is proposed, integrating human feedback via a reward function network trained on expert demonstrations. Additionally, a classification-based training method is employed for optimizing the reward function network. The experiments, conducted on datasets including HSI, IXIC, SP500, GOOGL, MSFT, and INTC, show that the proposed method outperforms all baselines across six datasets and achieves a maximum cumulative return of 1502% within 24 months. [ABSTRACT FROM AUTHOR]

Ma and Xu (2016) proposed a Hawkes jump–diffusion model for the firm's value to describe the unexpectedness of default and default clustering in the framework of Merton's structural default. However, the authors resorted to Monte-Carlo simulations for the calculation of the default probability and the default correlation, as no other solution method was available in the literature. In this note, we present a closed-form solution for the probability of default and the default correlation using the characteristic function. Our new solution can substantially improve the computational efficiency for the problem. [ABSTRACT FROM AUTHOR]

In this work, the two-stage multisplitting iteration methods based on the equivalent modulus equations are analyzed for solving linear complementarity problems. New convergence results are presented where the convergence domains of the parameter matrices are enlarged compared the existing literatures. Furthermore, the improved domains are validated by numerical examples with parallel computations using OpenACC. • Propose two convergence theorems of the two-stage multisplitting iteration methods for LCPs with new proof techniques. • The given results can improve the domain of the parameter matrices in the existing literatures. • Design an OpenACC framework where the efficiency of the proposed methods is shown to be improved with good speedups. [ABSTRACT FROM AUTHOR]

Illegal open-pit mining causes environmental harm and undermines sustainable development. Conventional monitoring approaches such as field research and unmanned aerial vehicle (UAV) imagery are time-consuming and labor-intensive, making large-scale monitoring difficult. In comparison, optical remote sensing imagery can cover large areas but is vulnerable to adverse weather conditions and is not sensitive to vertical ground changes. As open-pit excavation causes sudden changes in the scattering properties of ground objects along with dramatic vertical deformation, we evaluated the feasibility of using interferometric synthetic aperture radar (InSAR) coherence to identify illegal mining activities. Our method extracts the coherence coefficient from two SAR images taken on different dates, applies thresholding and filtering to extract a decorrelation map, and then overlays this with legal mining boundaries and optical satellite images to identify illegal mining activities. For three test cases in southwestern Inner Mongolia, China, 49 legal mining sites were correctly detected (with an accuracy of 90.74%) as well as six illegal mining sites. Ground truthing confirmed the presence of ongoing activity at one of these sites. Our study shows that InSAR coherence is suitable for the identification of mining activities, and our method provides a new approach for the detection and monitoring of illegal open-pit mining. [ABSTRACT FROM AUTHOR]

In this study, we develop a semi-analytic method to evaluate American options under a two-state regime-switching economy. The two free boundaries corresponding to the states divide the pricing domain into two regions: a common continuation region and a transition region. Non-linear partial differential equation (PDE) systems are derived under the Black–Scholes framework for each region. The Laplace transform method is used to solve the PDE systems. Equations for determining the optimal exercise prices are obtained analytically and solved numerically in the Laplace space. A numerical inversion technique is then used to obtain the free boundaries and the option prices in the original time space. The results of various examples show that our technique is efficient and accurate. • Semi-analytic pricing of American options under a regime-switching economy. • Volatility regimes governed by two-state Markov chains. • Derivation of coupled nonlinear equations for the moving (optimal exercise) boundaries. • Easy to implement procedure for the computation of optimal prices and option values. • Efficient and accurate method extendable to pricing of other financial derivatives. [ABSTRACT FROM AUTHOR]

In this work, for solving large sparse vertical linear complementarity problems, a relaxation two-step modulus-based synchronous multisplitting method without auxiliary variable is constructed. The convergence conditions are presented for the proposed method, where the range of the relaxation parameters is obtained. By OpenACC framework, the proposed method is shown to be more efficient than the existing method with high speedups with numerical tests. [ABSTRACT FROM AUTHOR]

Potato is the world's largest non-cereal crop, occupying a position critical for global food security. In China, potato is the fourth largest crop adding to food security and incomes. The large population and unremitting reductions in arable land are the most critical root causes of China's food security problems. Hence, crop yield improvements and strategies to improve land use are at the forefront of solutions to increase China's food security. Maintenance of existing land resources while increasing crop yields, avoiding soil quality degradation and wastage of water are enduring problems that have long attracted widespread attention in many research fields. This article, analyzes and discusses the status and challenges to sustainable intensification of rice-potato rotation in southern China. Three significant findings were obtained in this paper, viz. availability of about 16 million hectares of suitable land for rice-potato intensification in southern China in 2016 are reported, several conservation agricultural practices with varying intensity and higher economic benefits in rice-potato rotation than rice-fallow, which may positively effects the environment. It was concluded that agricultural intensification with potato was an economically viable avenue along with good agricultural practices that minimize adverse environmental effects. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to compare the outcomes of different mapping procedures based on anatomic or default frequency distribution in postlingual deafness adults who underwent cochlear implantation (CI). Methods: Forty-eight adults with postlingual deafness who underwent CI (MED-EL) from January 2021 to May 2022 in our hospital were prospectively recruited. The participants were randomly assigned to two groups (the anatomic group and the default group). Postoperative computerized tomography (CT) scans were evaluated with Otoplan® to determine the angular insertion depth (AID) and the specific locations of the intracochlear electrodes. Anatomic maps were imported into MAESTRO 9.0 software (MED-EL) for anatomy-based fitting for anatomic group, while default mapping program was set up for the default group. Hearing thresholds, Speech Recognition Scores (SRS), and subjects' auditory and musical abilities were evaluated 1 year after using the CI. Differences were determined in two groups using Stata statistical software, with significance defined as p < 0.05. Results: SRS under noisy conditions was significantly greater for anatomic group than the default group (p = 0.02). Under quiet conditions, however, mean hearing thresholds (0.5, 1, 2, and 4 kHz) and SRS did not differ significantly between the two groups (p = 0.07). Modified questionnaires showed that auditory (p = 0.02) and musical (p = 0.01) quality were significantly better following the anatomic mapping than the default procedure. Conclusion: CI program based on the anatomic distribution may bring better SRS under noise conditions as well as better auditory and musical qualities than based on the default frequency distribution. [ABSTRACT FROM AUTHOR]

Objectives: To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image quality and assessment of lung parenchyma. Methods: Sixty patients underwent chest regular-dose CT (RDCT) followed by LDCT during the same examination. RDCT images were reconstructed with hybrid iterative reconstruction (HIR) and LDCT images were reconstructed with HIR and DLR, both using lung algorithm. Radiation exposure was recorded. Image noise, signal-to-noise ratio, and subjective image quality of normal and abnormal CT features were evaluated and compared using the Kruskal–Wallis test with Bonferroni correction. Results: The effective radiation dose of LDCT was significantly lower than that of RDCT (0.29 ± 0.03 vs 2.05 ± 0.65 mSv, p < 0.001). The mean image noise ± standard deviation was 33.9 ± 4.7, 39.6 ± 4.3, and 31.1 ± 3.2 HU in RDCT, LDCT HIR-Strong, and LDCT DLR-Strong, respectively (p < 0.001). The overall image quality of LDCT DLR-Strong was significantly better than that of LDCT HIR-Strong (p < 0.001) and comparable to that of RDCT (p > 0.05). LDCT DLR-Strong was comparable to RDCT in evaluating solid nodules, increased attenuation, linear opacity, and airway lesions (all p > 0.05). The visualization of subsolid nodules and decreased attenuation was better with DLR than with HIR in LDCT but inferior to RDCT (all p < 0.05). Conclusion: LDCT DLR can effectively reduce image noise and improve image quality. LDCT DLR provides good performance for evaluating pulmonary lesions, except for subsolid nodules and decreased lung attenuation, compared to RDCT-HIR. Clinical relevance statement: The study prospectively evaluated the contribution of DLR applied to chest low-dose CT for image quality improvement and lung parenchyma assessment. DLR can be used to reduce radiation dose and keep image quality for several indications. Key Points: • DLR enables LDCT maintaining image quality even with very low radiation doses. • Chest LDCT with DLR can be used to evaluate lung parenchymal lesions except for subsolid nodules and decreased lung attenuation. • Diagnosis of pulmonary emphysema or subsolid nodules may require higher radiation doses. [ABSTRACT FROM AUTHOR]

Soil salinity is among the crucial factors that impact on crop productivity, including oat (Avena sativa L.). Herein, we used two distinct oat cultivars with varied salt tolerance levels to unravel adaptive responses to salt stress by metabolomic and transcriptomic characterization. Metabolomic profiling revealed 201 metabolites, including saccharides, amino acids, organic acids, and secondary metabolites. The levels of most saccharides and amino acids were elevated in Baiyan 2 (BY2) as well as in Baiyan 5 (BY5) exposed to salt stress. In the tolerant cultivar BY2 exposed to 150 mM NaCl, concentrations of most of the metabolites increased significantly, with sucrose increased by 38.34-fold, Sophorose increased by 314.15-fold and Isomaltose 2 increased by 25.76-fold. In the sensitive cultivar BY5, the concentrations of most metabolites increased after the plant was exposed to 150 mM NaCl but decreased after the plant was exposed to 300 mM NaCl. Transcriptomic analysis revealed that gene expressions in BY5 were significantly affected under exposure to 300 mM NaCl (34040 genes up-regulated and 14757 genes down-regulated). Assessment of metabolic pathways as well as KEGG enrichment revealed that salt stress interferes with the biosynthesis of two oat cultivars, including capacity expenditure and sugar metabolism. Most of the BY2 genes enhanced energy consumption (for example, glycolysis) and biosynthesis (for instance, starch and sugar metabolism) under salt stress. In contrast, genes in BY5 were found to be down-regulated, leading to the inhibition of energy consumption and biosynthesis, which may also be attributed to salt sensitivity in BY5. In addition, the modified Na+/K+ transporter genes expression is associated with the predominant ionic responses in BY2, which leads low concentration of Na+ and high K+ when exposed to high salt situations. These findings suggest that the varied defensive capacities of these two oat cultivars in response to salt stress are due to their variations in energy-expenditure strategy, synthesis of energy substances and ion transport in roots. Our present study offers a crucial reference for oat cultivation under saline soil. • Response to salt stress is regulated by expression levels of genes associated with Na+/K+ transporter in BY2 (salt-tolerant cultivar). • Genes associated with sugars and energy metabolism were upregulated under salt stress. • Glycolysis and other metabolic pathways were enhanced under salt stress to generate energy for oats growth. [ABSTRACT FROM AUTHOR]

In this work, by applying the synchronous multisplitting technique to the non-auxiliary variable modulus equation of the vertical linear complementarity problems, a new parallel method is constructed, which can generalize the existing modulus-based matrix splitting iteration method. The convergence conditions of the proposed method are discussed in the cases of more than two system matrices, and the existing results are improved. Numerical examples under OpenACC framework show that the proposed method can solve the large sparse vertical linear complementarity problems efficiently with high parallel efficiency. • A new parallel modulus-based method without auxiliary variable is proposed, which generalizes the existing serial method. • The complete convergence proof is given, which can improve the domain of the parameter matrix in the existing literatures. • An OpenACC framework is designed in the numerical examples with effective parallel speedup. [ABSTRACT FROM AUTHOR]

Utility-indifference approach is a useful approach to be adopted for pricing financial derivatives in an incomplete market and is an ongoing hot research topic in quantitative finance. One interesting question associated with this approach is whether or not it renders to the same option prices, degenerately, when the market becomes infinitesimally close to a complete market. The answer for such a question has been provided for European-style options as there is a well-documented theoretical proof in Davis et al. (1993). However, a theoretical proof for the case of pricing American-style options is unavailable at this stage and the answer for this question must be at least numerically confirmed before it can be comfortably used to price American-style options in incomplete markets. The contribution of this paper is to provide such a numerical verification. [ABSTRACT FROM AUTHOR]

Coeval shoshonitic and calc-alkaline to high-K calc-alkaline rock series were discovered in the eastern North China Craton (NCC). Here, we report zircon and titanite U Pb dating, zircon oxygen isotopic, whole-rock major and trace element and Sm Nd isotopic data for these rocks. Zircon and titanite U Pb geochronology suggests that the coeval shoshonitic to calc-alkaline mantle-derived magmas from the Jinan terrane were emplaced at ∼2.5 Ga and recorded multi-phases of metamorphic imprints. The shoshonitic series in Group I show higher K 2 O, but in contrast, the calc-alkaline to high-K calc-alkaline series (Group II) are characterized by higher Na 2 O. The two groups have enriched light rare earth elements (LREE) and depleted/nearly flat heavy rare earth elements (HREE). They also show negative anomalies in some HFSE and positive anomalies in LILE. Therefore, the geochemical data, Sm Nd and O isotopes included, show that the Jinan shoshonitic to calc-alkaline magmas were generated by melting of the metasomatized mantle at an ancient continental arc. Distinct geochemical features possibly suggest different mantle source features (metasomatic agents). The elevated zircon δ18O values imply that the weathering was significant during the end of Archean. In addition, the crustal reworking or intra-crustal recycling process played an important role in the continental crust evolution. The low-δ18O magmas documented here possibly indicate high-temperature water-rock interaction that occurs between continental crust and meteoric water. This study represents an example of co-existed shoshonitic and calc-alkaline mantle-derived magma derived from the melting of metasomatized mantle above an ancient subduction zone. Similar coeval associations of shoshonitic to calc-alkaline mantle-derived rocks, in combination with high-P granulites and crust-derived granites, may be used to constrain the ancient subduction-collisional belts. • Coeval shoshonitic to calc-alkaline intrusions from Jinan formed at ∼2.5 Ga. • They were formed by melting of metasomatized mantle at an ancient continental arc. • O isotopes imply significant weathering during the end of Archean. • The low zircon δ18O result from hydrothermal alteration by meteoric water. [ABSTRACT FROM AUTHOR]

Haze appearing in natural scene images generally contains nonhomogeneous characteristics such as filaments, masses, and mist. The high-frequency part of hazy images contains variable background textures and haze shapes, whereas regions with mostly uniform distribution are dominated by low-frequency information. Although existing methods based on convolutional neural networks have achieved remarkable progress in single image dehazing, the intrinsic hazy image patterns have been neglected in most models. We propose a frequency division dehazing network to leverage prior knowledge characterizing hazy images. The proposed network processes shallow feature maps through high-, medium-, and low-frequency branches. This separation facilitates a flexible architecture, whose branch handling lower-frequency components is less redundant given its relatively simpler background and haze shapes. Then, by integrating knowledge extracted from all the network branches using feature fusion, the proposed network fully exploits the variety of frequency characteristics in hazy images and achieves 39.51 PSNR and 0.9931 SSIM on the RESIDE dataset. Experiments on both synthetic and real hazy images demonstrate the superiority of the proposed network over several existing state-of-the-art methods, demonstrating the effectiveness of exploiting prior knowledge in hazy images. [ABSTRACT FROM AUTHOR]

Background: Pu'er Traditional Tea Agroecosystem is one of the projects included in the United Nations' Globally Important Agricultural Heritage Systems (GIAHS) since 2012. Against the background of having rich biodiversity and a long history of tea culture, the ancient tea trees in Pu'er have experienced from wild–transition–cultivation for thousands of years, and the local people's knowledge about the management of ancient teagardens has not been rigorously recorded. For this reason, it is important to study and record the traditional management knowledge of Pu'er ancient teagardens and the influence on the formation of tea trees and communities. This study focuses on the traditional management knowledge of ancient teagardens in Jingmai Mountains, Pu'er, and monoculture teagardens (monoculture and intensively managed planting base for tea cultivation) were used as the control, through the community structure, composition and biodiversity of ancient teagardens to respond to the influence of traditional management, and this work with a view to providing a reference for further research on the stability and sustainable development of tea agroecosystem. Methods: From 2021 to 2022, information on traditional management of ancient teagardens was obtained through semi-structured interviews with 93 local people in the Jingmai Mountains area of Pu'er. Informed consent was obtained from each participant before conducting the interview process. The communities, tea trees and biodiversity of Jingmai Mountains ancient teagardens (JMATGs) and monoculture teagardens (MTGs) were examined through field surveys, measurements and biodiversity survey methods. The Shannon-Weiner (H), Pielou (E) and Margalef (M) indices were calculated for the biodiversity of the teagardens within the unit sample, using monoculture teagardens as a control. Results: The tea tree morphology, community structure and composition of Pu'er ancient teagardens are significantly different from those of monoculture teagardens, and the biodiversity is significantly higher than that of monoculture teagardens. The local people mainly manage the ancient tea trees mainly using several methods, including weeding (96.8%), pruning (48.4%) and pest control (33.3%). The pest control mainly relies on the removal of diseased branches. JMATGs annual gross output is approximately 6.5 times that of MTGs. The traditional management of ancient teagardens is through setting up forest isolation zones as protected areas, planting tea trees in the understory on the sunny side, keeping tea trees 1.5–7 m apart, as well as consciously protecting forest animals such as spiders, birds and bees, and reasonably rearing livestock in the teagardens. Conclusions: This study shows that local people have rich traditional knowledge and experience in the management of ancient teagardens in Pu'er, and that this traditional management knowledge has impacted the growth of ancient tea trees, enriched the structure and composition of tea plantation communities and actively protected the biodiversity within ancient teagardens. [ABSTRACT FROM AUTHOR]

American-style puttable convertible bonds are often priced with various numerical solutions because the predominant complexity arises from the determination of the two free boundaries together with the bond price. In this paper, two forms of integral equations are derived to price a puttable convertible bond on a single underlying asset. The first form is obtained under the Black–Scholes framework by using an incomplete Fourier transform. However, this integral equation formulation possesses a discontinuity along both free boundaries. An even worse problem is that this representation contains two first-order derivatives of the unknown exercise prices, which demands a higher smoothness of the interpolation functions used in the numerical solution procedure. Thus, a second integral equation formulation is developed based on the first form to overcome those problems. Numerical experiments are conducted to show several interesting properties of puttable convertible bonds. [ABSTRACT FROM AUTHOR]