Simple Combination Research Articles

Source–Sink Structural Coupling Within Forest-Clustered Landscapes Drives Headstream Quality Dynamics in Mountainous Sub-Watersheds: A Case Study in Chongqing, China

Water environment quality is profoundly driven by a series of landscape characteristics. However, current knowledge is limited to the independent response of water quality to single landscape elements; this has led to poor knowledge of the potential role of structural coupling within landscapes in driving water quality changes, especially in those agroforestry-mixed mountainous watersheds with highly embedded forest-clustered landscapes and abundant headstreams. Given this fact, this study aims to evaluate whether and how the source–sink coupling structure of forest-clustered landscapes systematically drives headstream quality dynamics. We first systematically assessed the association pattern of source and sink structures within forest-clustered landscapes, and then innovatively proposed and constructed a functional framework of source–sink coupling structure of landscapes across 112 agroforestry-mixed mountainous sub-watersheds in Chongqing, China. On this basis, we further evaluated the driving pattern and predictive performance of the source–sink coupling structure of landscapes behind headstream quality dynamics. We report three findings: (1) headstream quality varied across agroforestry-mixed sub-watersheds, mapping out the source–sink structures and functions of landscapes; (2) there was significant functional coordination between source–sink structures of the forest-clustered landscapes, which significantly drove headstream quality dynamics; (3) the structural positioning and differences of the forest-clustered landscapes along the multivariate functional axes directly corresponded to and predicted headstream quality status. These findings together highlight a key logic that the response of water quality dynamics to landscapes is essentially that to the functional coupling between the source–sink structures of landscapes, rather than the simple combination of a single landscape contribution. This is the first study on the landscape–runoff association from the perspective of source–sink structural coupling, which helps to deepen understanding of the correlation mechanism between water dynamics and landscape systems, and provides a new functional dimension to the development of future landscape ecological management strategies from a local to a global scale.

An Empirical Study of Self-Supervised Learning with Wasserstein Distance

In this study, we consider the problem of self-supervised learning (SSL) utilizing the 1-Wasserstein distance on a tree structure (a.k.a., Tree-Wasserstein distance (TWD)), where TWD is defined as the L1 distance between two tree-embedded vectors. In SSL methods, the cosine similarity is often utilized as an objective function; however, it has not been well studied when utilizing the Wasserstein distance. Training the Wasserstein distance is numerically challenging. Thus, this study empirically investigates a strategy for optimizing the SSL with the Wasserstein distance and finds a stable training procedure. More specifically, we evaluate the combination of two types of TWD (total variation and ClusterTree) and several probability models, including the softmax function, the ArcFace probability model, and simplicial embedding. We propose a simple yet effective Jeffrey divergence-based regularization method to stabilize optimization. Through empirical experiments on STL10, CIFAR10, CIFAR100, and SVHN, we find that a simple combination of the softmax function and TWD can obtain significantly lower results than the standard SimCLR. Moreover, a simple combination of TWD and SimSiam fails to train the model. We find that the model performance depends on the combination of TWD and probability model, and that the Jeffrey divergence regularization helps in model training. Finally, we show that the appropriate combination of the TWD and probability model outperforms cosine similarity-based representation learning.

Identification of multimodal brain imaging biomarkers in first-episode drugs-naive major depressive disorder through a multi-site large-scale MRI consortium data

BackgroundMajor depressive disorder (MDD) is a severe and common mental illness. The first-episode drugs-naive MDD (FEDN-MDD) patients, who have not undergone medication intervention, contribute to understanding the biological basis of MDD. Multimodal Magnetic Resonance Imaging can provide a comprehensive understanding of brain functional and structural abnormalities in MDD. However, most MDD studies use single-modal, small-scale MRI data. And several multimodal studies of MDD are limited to simple linear combinations of functional and structural features. MethodsWe screened a large sample of FEDN-MDD patients and healthy controlsmultimodal MRI data. Extracting the fractional amplitude of low-frequency fluctuations (fALFF) feature from functional magnetic resonance imaging and the gray matter volume (GMV) feature from structural magnetic resonance imaging. The mCCA-jICA method was used to integrate these two modal features to investigate the functional-structural co-variation abnormalities in MDD. To validate the stability of the extracted functional-structural covariant abnormalities features, we apply them to identify FEDN-MDD patients. ResultsThe results show that compared to healthy controls, FEDN-MDD patients exhibit joint group-discriminative independent component and modality-specific group-discriminative independent component, suggesting functional-structural covariant abnormalities in MDD patients. Using lightGBM classifier, we achieve a classification accuracy of 99.84 %. LimitationWe use GMV and fALFF for multimodal fusion shows promise, but requires further validation with other datasets and exploration of additional multimodal features. ConclusionsThis may indicate that multimodal fusion features can effectively explore information between different modalities and can accurately identify FEDN-MDD patients, suggesting their potential as multimodal brain imaging biomarkers for MDD.

CLASSIFICATION OF SIMPLE AND COMPLEX PAREMIOLOGICAL UNITS

In this article, simple and complex paremiological phraseological combinations, concepts of nationality, culture, mentality are inextricably linked with language, and they are analyzed in different genres of paremiological language.

Simultaneous Optimization of Discrete and Continuous Parameters Defining a Robot Morphology and Controller.

The morphology and controller design of robots is often a labor-intensive task performed by experienced and intuitive engineers. Automatic robot design using machine learning is attracting increasing attention in the hope that it will reduce the design workload and result in better-performing robots. Most robots are created by joining several rigid parts and then mounting actuators and their controllers. Many studies limit the possible types of rigid parts to a finite set to reduce the computational burden. However, this not only limits the search space, but also prohibits the use of powerful optimization techniques. To find a robot closer to the global optimal design, a method that explores a richer set of robots is desirable. In this article, we propose a novel method to efficiently search for various robot designs. The method combines three different optimization methods with different characteristics. We apply proximal policy optimization (PPO) or soft actor-critic (SAC) as the controller, the REINFORCE algorithm to determine the lengths and other numerical parameters of the rigid parts, and a newly proposed method to determine the number and layout of the rigid parts and joints. Experiments with physical simulations confirm that when this method is used to handle two types of tasks-walking and manipulation-it performs better than simple combinations of existing methods. The source code and videos of our experiments are available online (https://github.com/r-koike/eagent).

Facile self-assembled monolayer deposition on copper foil for high-performance lithium-metal batteries

Li metal is widely acknowledged as the optimal negative electrode material for high-energy-density Li rechargeable batteries. However, challenges arise owing to the formation of Li dendrites and poor surface stability, leading to reduced cycle life and energy efficiency, thereby limiting widespread application. In this study, we introduced a novel approach of a molecular single-layer surface modification onto a Cu foil using a self-assembled monolayer with hexamethyldisilane (HMDS) to enhance the performance of Li-metal electrodes. The deposition of a single molecular layer at the Å-level was achieved by a simple combination of precursor casting and heat treatment without greatly affecting the energy and power density. Furthermore, this process was both scalable and cost-effective, making it highly suitable for large-scale battery manufacturing. The molecular deposition of HMDS effectively mitigated electrolyte decomposition and promoted uniform Li deposition by enhancing the surface stability under repeated Li plating–stripping processes. Optical microscopy revealed the homogeneous Li plating even after extended cycling; the first cycle on the modified surface depicted uniform plating without blank spots owing to the reduced gas-phase by-products from electrolyte decomposition. Thus, HMDS modification greatly improved the cycle stability of Li-metal batteries by successfully mitigating polarization due to electrolyte decomposition. Such improvement improved the Coulombic efficiencies and enhanced the energy efficiency, especially over a wide current density range of 1–5 mA cm−2. Furthermore, full cells with LiFePO4 cathodes and HMDS-modified Cu foils exhibited extended cyclability with increased energy efficiencies.

Using SAR imagery to extract flash flood sediment deposition area in the northern Loess Plateau

The lack of hydrology data brings challenges to the accurate simulation of the inundation range of flash floods using hydrodynamic models. In addition, the water bodies of flash floods often disappear quickly, which makes it difficult for remote sensing satellites to extract flash flood inundated areas without standing water. There is currently no research using flood sediment deposition areas to characterize flash floods in areas without water accumulation. To address this research gap, we developed a method based on Google Earth Engine (GEE) that uses Sentinel-1 SAR imagery to automatically extract flash flood sediment deposition areas. This method, termed Power Operation of Different Polarization Combination (PODPC), differs from other feature extraction methods in that it utilizes not only the original Vertical-Vertical (VV) and Vertical-Horizontal (VH) polarizations and their simple combinations but also employs power operations and threshold techniques to extrac t sediment deposition areas. We explored the advanced features of PODPC in terms of extraction accuracy, threshold segmentation effect, and sediment deposition area distribution. The results demonstrate that the histograms generated by PODPC exhibit clearer bimodal characteristics, facilitating better threshold selection. VV3, (VV + VH)6, and (VV × VH)3 produced fewer false deposition areas, achieving an overall accuracy of 92 % ∼ 93 %. Compared to commonly used methods such as VV, VH, and VV + VH, PODPC increased the overall accuracy by an average of 23 %. (VV-VH)n and (VV/VH)n are are considered unsuitable for the extraction of sediment deposition areas. The extracted sediment deposition area can serve as indicator of flash flood severity and as validation and input data for flash flood models, enhancing the scientific assessment of flash flood disasters.

A novel asymmetric superwetting filter prepared by easily mass-produced strategy for high-efficient and switchable water/oil filtration

All-purpose materials with on-demand oil/water separation property have received broad attention recently. Herein, a filter paper (FP)-based filter with asymmetric wettability was designed and fabricated via simple combination of liquid phase reduction route with symmetry adhesion method. The fabricated filter exhibits underoil superhydrophobic (UOSHP) and underwater superoleophobic (UWSOP) property. Especially, the good underliquids lyophobicity is still maintained after tape peeling and corrosive, organic solvents treatments. By fixing the hydrophobic (HO) side of filter facing up, the water/light oil mixtures and oil-in-water (O-in-W) emulsions can be highly efficient separated, and the water/heavy oil mixtures and water-in-oil (W-in-O) emulsions are able to be separated with the HI side facing up. The separation efficiencies for water/oil mixtures and oil/water emulsions are higher than 98% and 99.1%, respectively. The study offers a new idea for the preparation of asymmetric superwetting materials with good stability and on-demand water/oil separation capability.

Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation

BackgroundIt remains unclear which early gestational biomarkers can be used in predicting later development of gestational diabetes mellitus (GDM). We sought to identify the optimal combination of early gestational biomarkers in predicting GDM in machine learning (ML) models.MethodsThis was a nested case-control study including 100 pairs of GDM and euglycemic (control) pregnancies in the Early Life Plan cohort in Shanghai, China. High sensitivity C reactive protein, sex hormone binding globulin, insulin-like growth factor I, IGF binding protein 2 (IGFBP-2), total and high molecular weight adiponectin and glycosylated fibronectin concentrations were measured in serum samples at 11–14 weeks of gestation. Routine first-trimester blood test biomarkers included fasting plasma glucose (FPG), serum lipids and thyroid hormones. Five ML models [stepwise logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, support vector machine and k-nearest neighbor] were employed to predict GDM. The study subjects were randomly split into two sets for model development (training set, n = 70 GDM/control pairs) and validation (testing set: n = 30 GDM/control pairs). Model performance was evaluated by the area under the curve (AUC) in receiver operating characteristics.ResultsFPG and IGFBP-2 were consistently selected as predictors of GDM in all ML models. The random forest model including FPG and IGFBP-2 performed the best (AUC 0.80, accuracy 0.72, sensitivity 0.87, specificity 0.57). Adding more predictors did not improve the discriminant power.ConclusionThe combination of FPG and IGFBP-2 at early gestation (11–14 weeks) could predict later development of GDM with moderate discriminant power. Further validation studies are warranted to assess the utility of this simple combination model in other independent cohorts.

Electro-sustainable Synthesis: Rapid and Efficient Production of Benzothiazole Derivatives through Electrochemical Means for Sustainable Chemistry

Abstract: Electro-organic synthesis suggested a mild, environmentally benign, and atom-efficient pathway to interesting and useful organic compounds. Organic electrochemistry offers an excellent alternative to conventional methods of organic synthesis, avoiding harsh, oxidizing and reducing agents, etc. In our reported work, electro-organic synthesis was carried out in an undivided cell at room temperature in the presence of lithium perchlorate as a supporting electrolyte. Electricity is utilized here instead of a chemical substance with a simple graphite-iron electrode combination. The generation of 2-substituted benzothiazoles was achieved through the amalgamation of bis(2- aminophenyl)disulfides with aromatic aldehydes under the influence of the electrodes. This synthetic process yielded a diverse array of 2-substituted benzothiazoles with satisfactory to excellent yields (64-91%). This is a gentle, sustainable, and metal-free condition for the synthesis of 2-substituted benzothiazoles. In this procedure, subsequent procedural steps encompassed the introduction of distilled water followed by filtration and drying processes to ensure the refinement of the final products.

A Microrobotic Design for the Spontaneous Tracing of Isochemical Contours in the Environment

Microrobotic platforms hold significant potential to advance a variety of fields, from medicine to environmental sensing. Herein, minimally functional robotic entities modeled on readily achievable state‐of‐the‐art features in a modern lab or cleanroom are computationally simulated. Inspired by Dou and Bishop (Phys Rev Res. 2019;1(3):1–5), it is shown that the simple combination of unidirectional steering connected to a single environmental (chemical) sensor along with constant propulsion gives rise to highly complex functions of significant utility. Such systems can trace the contours orthogonal to arbitrary chemical gradients in the environment. Also, pairs of such robots that are additionally capable of emitting the same chemical signal are shown to exhibit coupled relative motion. When the pair has unidirectional steering in opposite directions within the 2D plane (i.e., counter‐rotating), they move in parallel trajectories to each other. Alternatively, when steering is in the same direction (corotation), the two move in the same epicyclical trajectory. In this way, the chirality of the unidirectional steering produces two distinct emergent phenomena. The behavior is understood as a ratchet mechanism that exploits the differential in the radii of curvature corresponding to different spatial locations. Applications to environmental detection, remediation, and monitoring are discussed.

A facile preparation of durable superhydrophobic PFA coatings with superior anti-icing, anti-corrosion and self-cleaning performance

The potential of superhydrophobic coatings for various applications has been widely recognized. However, preparing durable superhydrophobic coatings on metal surfaces remains a significant challenge. Perfluoroalkoxy Alkane (PFA), a fluorine-rich material, has recently emerged as a promising candidate for constructing superhydrophobic coatings. In this study, a mechanically stable superhydrophobic PFA coating was prepared using a simple combination of electrodeposition and annealing. The prepared PFA coating displays excellent water repellency, as evidenced by a water contact angle of 171 ± 0.3° and a sliding angle of 1.0 ± 0.4° The water contact angle of the coating only decreases by 0.6°after undergoing 400 tape stripping tests, indicating the remarkable stability. The PFA coating significantly prolongs the freezing time of water droplets on a cool surface at temperatures of -6 °C, -8 °C, and -10 °C, with improvements of 19.4, 72.5, and 47.8 times respectively. The corrosion current density on the coated surface is reduced by four orders of magnitude compared to bare aluminum alloy, and the PFA coating exhibits a high inhibition corrosion efficiency of 99.995 %. Furthermore, the coating possesses exceptional self-cleaning performance by repelling dirt particles and maintaining a clean surface. Consequently, the developed superhydrophobic PFA coating holds significant promise for long-lasting anti-icing, anti-corrosion and self-cleaning applications.

Fabrication of positively charged composite nanofiltration membranes with “multilayer interlocking” structure based on ZIF-8 layer anchored constrained growth strategy for Mg2+/Li+ separation

In recent years, with the rapid development of new energy vehicles, the demand for lithium resources has been increasing sharply. Positively charged nanofiltration (NF) membranes can accurately separate magnesium ions (Mg2+) and lithium ions (Li+), which have become an important technology for extracting lithium resources from salt lakes. The introduction of intermediate layer in thin-film composite (TFC) NF membranes could improve the permeability and selectivity for Mg2+/Li+ separation. However, there is a problem of poor bonding between the intermediate layer and the supporting membranes through the simple physical combination on the membrane surface. Inspired by the controlled growth of succulent plants, the positively charged PA/ZIF-8/PSF composite NF membranes with “multilayer interlocking” structure were prepared successfully based on ZIF-8 layer anchored constrained growth and further interfacial polymerization. The zinc ion ligands of ZIF-8 were pre-anchored on the PSFsolution to provide reaction sites, and the grown ZIF-8 nanoparticles were embedded in the PSFsupporting membrane surface layer. The embedded ZIF-8 nanoparticles can enhance the interface bonding between the PSFsupporting membranes and the ZIF-8 layer. Additionally, the confined growth method can solve the problems of ZIF-8 particle aggregation and poor dispersion. Compared with membranes without ZIF-8 layer, the prepared PA/M − 6 membrane had a high flux of 47.2 L m−2h−1, which was 1.82 times that of PA/M-0. Meanwhile, the Mg2+/Li+ separation factor of the PA/ZIF-8/PSF composite NF membranes could reach 47.6. In particular, the prepared NF membranes exhibited good long-term stability for Mg2+/Li+ separation.

Efficient separation of Chromium(III) from Lanthanide(III) via reductive boronization in molten chloride

It is an easy way to recover metals in molten salt by the precipitation-based method, but the selectivity yet remains challenging. Herein, a new separation method employing reductive boronization is proposed, and it is validated by the separation of trivalent chromium and lanthanide ions in molten LiCl-KCl. Although no Cr(III) and La(III) separation was achieved by using NaBH4, Cr(III) was successfully removed via the formation of insoluble CrB2 when B powder was used as the boronization reagent with La(III) remaining entirely in the melt. More than 97% Cr(III) can be removed from the CrCl3-LaCl3-LiCl-KCl melt after a reaction time of 300 min, and the removal rate was retained when the La/Cr ratio varied from 0.1:1 to 10:1. Such reductive boronization method is also valid in other Ln(III)/Cr(III) systems. The boronization process involves the reduction of Cr(III) and the reaction between zero valent metal and boron rather than the simple combination of anions and cations to give precipitates as evidenced by the XPS analyses. The difference in reactivity between Cr(III) and La(III) toward B can be rationalized in terms of their significant difference in the ΔG values of the boronization reactions that mainly correlates with the much lower reduction potential of La(III)/La(0), which makes B an ideal boronization reagent for the separation of trivalent chromium and lanthanide ions in molten chloride.

Investigation of Key Electronic States in Layered Mixed Chalcogenides With a d0 Transition Metal as Li‐Ion Cathodes

AbstractLithium‐rich transition metal chalcogenides are witnessing a revival as candidates for Li‐ion cathode materials, spurred by the boost in their capacities from transcending conventional redox processes based on cationic states and tapping into additional chalcogenide states. A particularly striking case is Li2TiS3‐ySey, which features a d0 metal. While the end members are expectedly inactive, substantial capacities are measured when both Se and S are present. Using X‐ray absorption spectroscopy, it is shown that the electronic structure of Li2TiS3‐ySey is not a simple combination of the end members. The data confirm previous hypotheses that, in Li2TiS2.4Se0.6, this behavior is underpinned by concurrent and reversible redox of only S and Se, and identify key electronic states. Moreover, wavelet transforms of the extended X‐ray absorption fine structure provide direct evidence of the formation of short Se–Se units upon charging. The study uncovers the underpinnings of this intriguing reactivity and highlights the richness of redox chemistry in complex solids.

Preparation and characterization of novel polyols-based DESs and their use in efficient sequestration of radioactive iodine

The utilization of Novel DESs can be greener alternative to traditional organic solvents. In present study, four polyols-based DESs are synthesized and characterized by several techniques. The prepared DESs are used for the efficient capture of hazardous iodine. In present study by simple combination of two readily accessible, economical, and biodegradable components four polyols-based DESs have been prepared. For the creation of these DESs, a hydrogen bond donors (HBDs) (polyols) and hydrogen bond acceptors (HBAs) (BTEAC) are used, which havemelting points far lower than their respective melting points. The developed DESs were investigated for their physicochemical properties such as density, dynamic viscosity. Our results revealed distinct trends in these properties across different DES compositions, highlighting unique molecular interactions and solvation capabilities. The FTIR and NMR characterization study indicated considerable intermolecular interaction between the various component of the DES system. Further, Kamlet-Taft solvatochromic parameters were determined using Nile red dye, and other solvatochromic dyes. For synthesized DESs, the solvatochromic parameters ENT, normalized polarity parameter, π*, polarity / polarizability; β, hydrogen-bond acceptor basicity and α, hydrogen-bond donor acidity, have been determined. The ENT parameters demonstrate that both non-specific and specific interactions play a significant role in solute–solvent interactions. The synthesized DESs have been utilized for the efficient capture of the iodine. The removal efficiency of DES depends upon the mass of the DESs taken and time duration. These findings deepen our understanding of DES behavior and underscore their versatility in diverse industrial and scientific applications.

Eye-Tracking and Psychological Analysis: The Impact of Building Shape on Visitor Visual Preference

Garden buildings not only enhance the aesthetics of gardens but also affect the visual and psychological experience of visitors. However, existing studies lack a systematic analysis of the shape types and combination patterns of buildings, which indirectly affects the overall experience of visitors. This study explores the attractiveness of different forms, styles, and combinations of buildings to visitors through oculometry and psychological analysis. The results of the study show that buildings are always the main focus of visitors’ sight in the garden, and traditional buildings can stimulate visitors’ excitement and curiosity. When observed at close range, visitors’ attention to simple-shaped buildings was mainly focused on the overall shape, while details of complex-shaped buildings, such as decorations, doors, windows, and columns, can significantly attract the eye. In contrast, when viewed from a distance, simple and regular combinations of building shapes were more effective in attracting visitors’ attention, while the appeal of the historic features of complex buildings declined, possibly due to reduced clarity of detail. Visually striking elements such as buildings with acute angles or curved eaves attracted more visual attention when viewed from a distance. This study not only provides a scientific basis for the design of shapes and historical characteristics of garden buildings but also provides practical guidance for the layout and spatial remodeling of garden buildings.

Improved conditions for the synthesis of tertiary fluorides using a KF/H2SO4 combination

In this paper, we report the deoxyfluorination of tertiary alcohol using a simple combination of potassium fluoride and sulfuric acid. These cheap and widely available reagents allow for the synthesis of tertiary fluorides in good to excellent yields. Extension of the reaction to other functional groups such as alkenes, acetates and ethers have also been studied.

Polyolefin waste to light olefins with ethylene and base-metal heterogeneous catalysts.

The selective conversion of polyethylene, polypropylene, and mixtures of the two polymers to form products with high volume demand is urgently needed because current methods suffer from low selectivity, produce large quantities of greenhouse gases, or rely on expensive, single-use catalysts. The isomerizing ethenolysis of unsaturated polyolefins could be an energetically and environmentally viable route to propylene and isobutylene, but noble-metal homogeneous catalysts and an unsaturated polyolefin are currently required, and the process has been limited to polyethylene. We show that the simple combination of tungsten oxide on silica and sodium on gamma-alumina transforms polyethylene, polypropylene, or a mixture of the two, including post-consumer forms of these materials, to propylene or a mixture of propylene and isobutylene in greater than 90% yield at 320°C without the need for dehydrogenation of the starting polyolefins.

Enhancing Agricultural Commodity Forecasting: A Median-Based Combination of Time Series Models

This study explores the efficacy of combining forecasts using the median operator to enhance forecasting performance. The traditional approach of assigning equal weights to individual models often struggles with extreme forecasts. A new method Simple Combination of Univariate Models (SCUM) is utilized, which uses the median operator to combine forecasts from four distinct time series models: Exponential Smoothing (ETS), Auto Regressive Integrated Moving Average (ARIMA), Dynamically Optimised Theta Model (DOTM), and Complex Exponential Smoothing (CES). This approach aims to mitigate the influence of extreme forecasts and improve overall accuracy. Our empirical analysis investigates the use of the SCUM approach for the agricultural commodity data. Yearly production of Rice is used, sourced from the Ministry of Agriculture & Farmers Welfare, Government of India. The forecasting performance of the SCUM approach is compared against individual models and a mean-based combined forecast using key performance metrics such as Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and Relative Efficiency. The results show that SCUM outperforms all other models, achieving the lowest RMSE (51.89) and a MAPE of 6.90, indicating superior in-sample forecasting accuracy. ARIMA was the least efficient with a 22.11% relative efficiency, while the Mean combination method (3.33%) was closest to SCUM in performance. The findings suggest that SCUM is not only a viable alternative to traditional methods but also offers significant advantages in improving forecasting accuracy. This research underscores the potential for median-based forecast combinations to achieve superior predictive accuracy and reliability, making it a valuable tool for scholars and practitioners in time series forecasting.