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Introduction: Subthalamic nucleus deep brain stimulation (STN-DBS) is a proven treatment modality for Parkinson’s disease (PD), reducing dyskinesia and time spent in the “OFF” state. This study evaluates the long-term outcomes of STN-DBS in PD patients up to 10 years post-surgery in Singapore. Method: We conducted a retrospective review of Movement Disorders Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) scores, activities of daily living (ADLs), disease milestones, dopaminergic drug prescriptions, and adverse events in patients before and after STN-DBS surgery. Results: A total of 94 PD patients who underwent bilateral STN-DBS were included. STN-DBS reduced time in the “OFF” state by 36.9% at 1 year (P=0.034) and 40.9% at 5 years (P=0.006). Time with dyskinesia did not significantly change. Levodopa equivalent daily dose was reduced by 35.1% by 5 years (P less than 0.001). MDS-UPDRS-II and III scores increased from 5 years post-DBS by 40.5% and 35.4%, respectively. Independence in ADLs decreased, though not significantly. The prevalence of frequent falls increased at 5 years. Surgery- and device-related adverse events were uncommon and generally mild. Conclusion: STN-DBS provides sustained relief from motor complications and reduced medication requirements in PD patients in Singapore. This study highlights STN-DBS as an effective treatment option, significantly enhancing the quality of life for those with PD.

The inter-system-like bias between the regional (BDS-2) and global (BDS-3) constellation of the BeiDou Navigation Satellite System (BDS) has been identified on common B1I pseudo-range observations. In this study, its characteristics are investigated with tracking data from the International GNSS Service (IGS) and International GNSS Monitoring and Assessment System (iGMAS) network. Firstly, the satellite-specific inter-system-like bias is calculated and the dependency on satellite is observed. Clearly noticeable discrepancies on BDS-2 and BDS-3 can be identified. Hence, the constellation-specific inter-system-like bias is estimated. Biases for all receivers are quite stable, with standard derivation (STDev) less than 0.2 m in average. The bias shows clear dependence on the receiver, while the firmware and antenna have limited but not negligible impacts, particularly for Trimble NetR9 and Alloy receivers. The Trimble NetR9 with TRM59800.00 antenna shows noticeable discrepancy up to about 1.5 m with different antenna, and the bias of the Trimble Alloy 5.37 jumps about 2.4 m with respect to later firmware. In addition, clear annual variations are observed for stations ABPO and MIZU with Septentrio POLARX5 5.3.2 and ASTERX4 4.4.2 receivers, respectively. Furthermore, the impacts of the biases on the BDS orbit and clock solutions are analyzed. Once BDS-2 and BDS-3 are treated as two independent systems, the root mean square (RMS) of code and carrier phase residuals can be reduced by around 9.3 cm and 0.23 mm, respectively, while the three-dimensional orbit consistency is improved by 6.8%, mainly in the tracking direction. Satellite laser ranging (SLR) shows marginal impacts on IGSO and MEO satellites. However, the SLR residual of C01 shifts −13.2 cm, resulting in a smaller RMS value. In addition, the RMS of linear clock fitting is reduced from 0.050 ns to 0.038 ns for BDS-3 MEO satellites in average.

This review summarizes the progress in the research on polyoxometalate (POM)-decorated gold (Au) and silver (Ag) core–shell structures (Au/Ag@POMs), emphasizing their substantial application potential in catalysis, medicine, and biology. It outlines the central strategies for fabricating Au/Ag@POMs with diverse morphologies and dimensions, leveraging POMs as protective ligands and reducing agents as well as for ligand exchange. Of particular note is the focus on the analysis of the nanoparticle size, shape, and intricate architecture of POM shells using cryo-electron microscopy techniques. By integrating recent findings on atomically precise POM-stabilized nanoclusters, this review delves deeper into understanding surface interface structures, intrinsic atomic architectures, and electronic interactions between POM shells and metallic cores. Collectively, advancements in this field underscore significant strides in the controllable synthesis and precise structural manipulation of Au/Ag@POM architectures, thus paving the way for engineering high-performance metal catalysts. [ABSTRACT FROM AUTHOR]

Airborne LiDAR (Light Detection and Ranging) is an active Earth observing system, which can directly acquire high-accuracy and dense building roof data. Thus, airborne LiDAR has become one of the mainstream source data for building detection and reconstruction. The emphasis for building reconstruction focuses on the accurate extraction of feature lines. Building roof feature lines generally include the internal and external feature lines. Efficient extraction of these feature lines can provide reliable and accurate information for constructing three-dimensional building models. Most related algorithms adopt intersecting the extracted planes fitted by the corresponding points. However, in these methods, the accuracy of feature lines mostly depends on the results of plane extraction. With the development of airborne LiDAR hardware, the point density is enough for accurate extraction of roof feature lines. Thus, after acquiring the results of building detection, this paper proposed a feature lines extraction strategy based on the geometric characteristics of the original airborne LiDAR data, tracking roof outlines, normal ridge lines, oblique ridge lines and valley lines successively. The final refined feature lines can be obtained by normalization. The experimental results showed that our methods can achieve several promising and reliable results with an accuracy of 0.291 m in the X direction, 0.295 m in the Y direction and 0.091 m in the H direction for outlines extraction. Further, the internal feature lines can be extracted with reliable visual effects using our method.

A method for land-cover classification was proposed based on the fusion of features generated from waveform data and point cloud respectively. It aims to partially overcome the ineffectiveness of many traditional classifiers caused by the fact that point cloud is lacking spectral information. The whole flowchart of the method is as follows: Firstly, Gaussian decomposition was applied to fit an echo full-waveform. The parameters associated with the Gaussian function were optimized by LM (Levenberg-Marquard) algorithm. Six and thirteen features were generated to describe the waveform characteristics and the local geometry of point cloud, respectively. Secondly, a random forest was selected as the classifier to which the generated features were input. Relief-F was used to rank the weights of all the features generated. Finally, features were input to the classifier one by one according to the weights calculated from feature ranking, where classification accuracies were evaluated. The experimental results show that the effectiveness of the fusion of features generated from waveform and point cloud for LiDAR data classification, with 95.4% overall accuracy, 0.90 kappa coefficient, which outperform the results obtained by a single class of features, no matter whether they were generated from point cloud or waveform data.

Airborne light detection and ranging (LiDAR) technology has been widely utilized for collecting three-dimensional (3D) point cloud data on forest scenes, enabling the generation of high-accuracy digital elevation models (DEMs) for the efficient investigation and management of forest resources. Point cloud filtering serves as the crucial initial step in DEM generation, directly influencing the accuracy of the resulting DEM. However, forest filtering presents challenges in dealing with sparse point clouds and selecting appropriate initial ground points. The introduction of full-waveform LiDAR data offers a potential solution to the problem of sparse point clouds. Additionally, advancements in multi-source data integration and machine learning algorithms have created new avenues that can address the issue of initial ground point selection. To tackle these challenges, this paper proposes a novel filtering method for forest scenes utilizing full-waveform LiDAR data and hyperspectral image data. The proposed method consists of two main steps. Firstly, we employ the improved dynamic graph convolutional neural network (IDGCNN) to extract initial ground points. In this step, we utilize three types of low-correlation features: LiDAR features, waveform features, and spectral features. To enhance its accuracy and adaptability, a self-attention module was incorporated into the DGCNN algorithm. Comparative experiments were conducted to evaluate the effectiveness of the algorithm, demonstrating that the IDGCNN algorithm achieves the highest classification accuracy with an overall accuracy (OA) value of 99.38% and a kappa coefficient of 95.95%. The second-best performer was the RandLA-net algorithm, achieving an OA value of 98.73% and a kappa coefficient of 91.68%. The second step involves refining the initial ground points using the cloth simulation filter (CSF) algorithm. By employing the CSF algorithm, non-ground points present in the initial ground points are effectively filtered out. To validate the efficacy of the proposed filtering method, we generated a DEM with a resolution of 0.5 using the ground points extracted in the first step, the refined ground points obtained with the combination of the first and second steps, and the ground points obtained directly using the CSF algorithm. A comparative analysis with 23 reference control points revealed the effectiveness of our proposed method, as evidenced by the median error of 0.41 m, maximum error of 0.75 m, and average error of 0.33 m.

We introduce an approach for the direct measurement of the gravitational potential (GP) along the trajectory of a satellite, with a specific focus on Low-Earth Orbit (LEO) satellites. A LEO satellite communicates with several Geosynchronous Equatorial Orbit (GEO) satellites via frequency signal links. The GP difference can be measured in real-time using the gravitational frequency shift approach by equipping both LEO and GEO satellites with precise atomic clocks. Since the GP at the high orbits of the GEO satellites can be precisely determined by the present gravitational field model EGM2008, the GP along the LEO satellite’s trajectory can be determined. In this study, simulation experiments were conducted, featuring a GRACE-type satellite as the LEO satellite in communication with three equidistant GEO satellites. The results indicated that the accuracy of the GP measurements along the LEO satellite’s trajectory primarily depends on the precision of the onboard atomic clocks. Supposing optical atomic clocks attain an instability level of 1×10−17τ−1/2 (τ in seconds), we determined the GP distribution covered by the LEO satellite’s trajectories with 30-day observations. Then, we determined a gravitational field at the centimeter level based on the GP distribution. The GP data derived from the trajectory of a LEO satellite can be utilized to establish temporal gravitational fields, which have broad applications in different disciplines.

The International Association of Geodesy (IAG) aims to establish the International Height Reference System (IHRS) as one of its primary scientific objectives. Central to the realization of the IHRS is global vertical datum unification, which requires the connection of existing local vertical height reference systems (VHS) robustly and consistently. However, conventional methods are not suitable for estimating the offsets between two distant local height systems. In this paper, we propose a framework for connecting two local VHSs using ultraprecise clock frequency signal links between satellites and ground stations, referred to as the satellite frequency signal transmission (SFST) approach. The SFST approach allows for the direct determination of the geopotential and height differences between two ground datum stations without any location restrictions between the two VHSs. The simulation results show that the VHSs of China and the US can be unified with an accuracy of several centimeters, provided that the stability of atomic clocks used on-board the satellite and at on-ground datum locations reaches 4.8×10−17τ−1/2 for an averaging time τ (in seconds). We conclude that the SFST approach shows promise for achieving centimeter-level accuracy in unifying the global vertical height datum and represents a new paradigm for the realization of the IHRS.

Stereodivergent synthesis of N -heterocycle frameworks bearing 1,3-nonadjacent stereogenic centers through a single transformation remains a high-priority challenge in organic synthesis. Herein, we highlight our recent discovery of stereodivergent access to such useful structural motifs using Pd-catalyzed [4+2] annulation reactions of vinyl benzoxazinaones and seven-membered cyclic N-sulfonyl aldimines. A wide range of N -heterocycles with 1,3-nonadjacent stereogenic centers were obtained in high efficiency and stereodivergency. Importantly, the polarity of solvents was found to play a key role in switching the diastereoselectivity. Furthermore, good enantioselectivities of these reactions were achieved by the employment of commercially available Wingphos as the chiral ligand. [ABSTRACT FROM AUTHOR]

Filtering is one of the key steps for Digital Elevation Model (DEM) generation from airborne Light Detection and Ranging (LiDAR) data. Machine-learning-based filters have emerged as a class of filtering algorithms in recent years. Most existing studies mainly focus on feature generation due to limited available features a point cloud possesses. More than 30 features have been described in the existing literature. But most generated features are based on geometric information of points. Several redundant and irrelevant features may not necessarily improve the filtering accuracy. Hence, this paper proposes a feature-selection method using minimal-Redundancy-Maximal-Relevance (mRMR) combined with Parzen window optimization to deal with both discrete and continuous features. An optimal/suboptimal feature subset is constructed for machine-learning filters in various landscapes. Experimental results based on AdaBoost show that height-related features, particularly height itself, are of the greatest significance in both urban and rural scenes. Moreover, different subsets can be selected from the datasets of the two landscapes by our feature-selection strategy, which increases the data relevance for describing each geographical landscape. This study provides guidelines for the selection of optimal/suboptimal features for point cloud filtering based on machine-learning algorithms.

Organic macrocyclic complexes composed of polyoxometalates (POMs) and cyclodextrins based on host–guest interactions have garnered significant attention. Herein, we report the assemblies by blending inorganic POMs and a complex macrocycle. Utilizing silver-coordinated bridge connections, four distinct POM-based silver-bisphosphine (Ag2dppp2) (dppp = 1,3-bis(diphenylphosphino)propane) macrocyclic hybrids: [Ag4(dppp)4(Mo8O26)] (1), {[Ag4(dppp)4(PW12O40)]NO3} (2), [Ag3(dppp)3(PMo12O40)] (3), and [Ag2(dppp)2(CH3CN)2(Mo6O19)] (4) have successfully been synthesized. The self-assemblies of hybrids involve sandwich and tubular structures that depend on the size, charge of POMs, anions and coordination solvent. Interactions of the silver-bisphosphine macrocycle and POMs in solution were further examined by 31P nuclear magnetic resonance (NMR) and cyclic voltammetry (CV). Dye adsorption behavior has been investigated for the structure–activity relationship of surface structures of the hybrids. [ABSTRACT FROM AUTHOR]

In order to explore novel antifungal agents, twenty-seven triazole derivatives featuring an alkyne linker in the side chain were designed and synthesized by the Sonogashira reaction. Most of the target compounds exhibited good antifungal activity against eight human pathogenic fungi, especially excellent activity against Candida and Cryptococcus species, comparing with the reference drugs fluconazole, voriconazole and ravuconazole. Compounds A2 and A3 exhibited in vitro activity against all the tested fungi with MIC80 values ranging from 0.0156 μg/mL to 0.5 μg/mL, which are superior to ravuconazole and fluconazole. SAR and molecular docking study give a clear conclusion that para-fluoro, para-chloro, and para-cyano substituted phenylalkynyl or pyridinylalkynyl side chains may promote triazole antifungal activity. Keywords: Triazole, Alkyne, CYP51, Antifungal, Synthesis

Nowadays, Over-The-Top (OTT) voice call service has become more popular than other Voice over Internet Protocol services provided by mobile operators due to cheaper costs. For devices with more than one network interfaces, the OTT software may need to handover between heterogeneous networks during a call. Unnecessary handover may lead to signal overload, especially in a Wi-Fi intensive area where users may handover frequently between Wi-Fi and cellular networks. For example, if the period between when a user handovers from Wi-Fi to Long Term Evolution (LTE) and when the user handovers from LTE back to Wi-Fi is too short to transmit voice data, the handover procedures between Wi-Fi and LTE can be considered unnecessary and power consuming. To tackle this issue, this paper proposes delay handover mechanism (DHM) to avoid the unnecessary handover procedures by postponing the timing to handover from Wi-Fi to LTE. We then propose an analytical model as well as a simulation model to investigate how many handovers can be reduced. The analytical model is validated against the simulation model. With extensive simulation experiments, the performance evaluation of DHM offers a guideline to configure parameters based on the trade-off between reduced handover ratio and packet loss rate. As a whole, DHM is an application-based mechanism for avoiding unnecessary handovers as well as cutting down LTE usages.

This article discusses the development of a cobalt-catalyzed enantioselective alkynylation reaction for oxabicyclic alkenes. The researchers optimized the reaction conditions and found that chlorobenzene as a solvent and CoBr2 as a catalyst resulted in the highest yield and enantioselectivity. The method was successfully used to produce a variety of chiral cyclic homopropargylic alcohols. The document provides detailed information about the experimental procedures, results, and characterization of the synthesized compounds using various analytical techniques. The absolute configurations of the compounds were determined by reference to previous literature. The supporting information for the article is available online. [Extracted from the article]

In this paper, we report the successful assembly of achiral {Ln6M} ([Ln6M(μ3-OH)8(acac)12(CH3O)x(CH3OH)y], Ln = La, M = Mn, Co, Fe) and chiral {Nd9Fe2} ([Nd9Fe2(μ4-O)(μ3-OH)14(acac)16(NO3)(CH3OH)2(H2O)3]) rare earth clusters using achiral rigid ligands and a transition metal doping strategy. {Ln6M} can be viewed as the fusion of two {Ln3M} tetrahedrons by sharing vertices. {Nd9Fe2} results from the fusion of four {Ln3M} tetrahedrons by vertice and edge sharing. The substitution of Ln with transition metal leads to changes in the coordination pattern around neighboring Ln, which triggers the switch of metal center chirality. This study demonstrates the potentiality of utilizing transition metal doping and rigid ligand to control the chirality of rare earth clusters. In addition, the photocatalytic CO2 activity of these transition metal-doped rare earth clusters has been studied. [ABSTRACT FROM AUTHOR]

Biochar has been recognized as a new exogenous organic substrate and is often used as an important organic resource for carbon reduction because of its stability, adsorption and carbon nutrient richness. The study was conducted in a typical indica rice area of Nanning from 2021 to 2022, against the background of having high early indica rice yields, simultaneous rain and heat, and unique cropping system. In this paper, authors set three treatments: Control treatment (CK): no fertilizer. Inorganic N input (T1, chemical fertilizer) treatment: chemical fertilizer application at conventional fertilizer level, compound fertilizer 800kgha-1, urea 260.87kgha-1, potassium 193.55kgha-1. Inorganic N with organic N (T2, biochar + chemical fertilizer) treatment: biochar 4000kgha-1, compound fertilizer 738.67kgha-1, urea 146.09kgha-1, potassium 34.19kgha-1. The cumulative greenhouse gas emissions, emission equivalents, rice yield traits and the effect of isonitrogen substitution of biochar application on greenhouse gas emissions and rice yield in early southern rice fields were analyzed by regular monitoring of soil greenhouse gas emissions in rice fields during the rice reproductive period using a split static box-meteorological chromatography method 5d after rice transplanting, this study provide a basis for optimizing intensive early rice low-carbon cultivation and reduce fertilizer and increase efficiency. The results showed that: (1) biochar can reduce CH4 and CO2 emissions from paddy soils, and reduce the combined emission equivalent by slowing down CH4 emissions. The application of fertilizer with biochar can mitigate the increase of greenhouse gas carbon emissions caused by fertilizer application alone, and its delayed effect of mitigating CO2 emissions is more obvious. In biochar treatment (T2), compared with the chemical fertilizer treatment (T1), the maximum CH4 emission flux in 2021 was reduced by 41.38% and the cumulative emission was reduced by 31.25%, and the maximum emission flux in 2022 was reduced by 50.50% and the cumulative emission was significantly reduced by 50%, and the combined emission equivalents of 2 years were significantly lower than those of the T1 treatment. The maximum CO2 emission flux and cumulative emission in 2021 were reduced by 57.38% and 37.68%, respectively, compared with the T1 treatment, and the corresponding reduction in 2022 was 16.06% and 35.52% compared to the T1 treatment. (2) Biochar can suppress N2O emissions, significantly reduce cumulative emissions, and reduce nitrogen source emission equivalents. Compared to the T1 treatment, the maximum N2O emission flux was reduced by 5.43% and the cumulative emission was significantly reduced by 33.53% in 2021 in T2 treatment; the maximum emission flux was reduced by 73.75% and the cumulative emission was significantly reduced by 54.33% in 2022, and there was no significant change with the CK treatment. (3) Biochar facilitates the optimization of intensive early indica rice cultivation structure and enhances the productivity of early indica rice. After biochar was put into the paddy field for 2 years, the effect of increasing yield became more and more obvious, and the theoretical yield of T2 treatment was 1.02-1.33 times that of T1 treatment, while the actual yield was 1.06-1.32 times that of T1 treatment. Fertilizer with biochar reduced greenhouse gas emissions and increased rice yield in early indica rice fields, which can be used as an optimization model for low-carbon production of intensive early indica rice in the south. [ABSTRACT FROM AUTHOR]

Halide ions have emerged as important surface active species that regulate the growth of nanomaterials and concomitant physicochemical properties. However, there are very few reports concerning anion exchange of halide ions for the growth and conversion of nanocrystals or nanoclusters. Herein, we present the transformations of silver(I) chalcogenide clusters induced by doping halide ions, which are particularly of interest because of individual pathways controlled by ion species and amounts. Based on the cluster transformation, we further developed a luminescence turn-on sensor with high selectivity, detecting Cl− and Br−. This work opens a new way of understanding the growth of clusters and developing their luminescence sensing applications. [ABSTRACT FROM AUTHOR]