In situ atomic-scale observation of size-dependent (de) potassiation and reversible phase transformation in tetragonal FeSe anodes

Potassium-ion batteries(PIBs)are considered promising alternatives to lithium-ion batteries owing to cost-effective potassium resources and a suitable redox potential of-2.93 V(vs.-3.04 V for Li+/Li).However,the exploration of appro-priate electrode materials with the correct size for reversibly accommodating large K+ions presents a significant challenge.In addition,the reaction mecha-nisms and origins of enhanced performance remain elusive.Here,tetragonal FeSe nanoflakes of different sizes are designed to serve as an anode for PIBs,and their live and atomic-scale potassiation/depotassiation mechanisms are revealed for the first time through in situ high-resolution transmission electron micros-copy.We found that FeSe undergoes two distinct structural evolutions,sequen-tially characterized by intercalation and conversion reactions,and the initial intercalation behavior is size-dependent.Apparent expansion induced by the intercalation of K+ions is observed in small-sized FeSe nanoflakes,whereas unexpected cracks are formed along the direction of ionic diffusion in large-sized nanoflakes.The significant stress generation and crack extension originating from the combined effect of mechanical and electrochemical interactions are elucidated by geometric phase analysis and finite-element analysis.Despite the different intercalation behaviors,the formed products of Fe and K_(2)Se after full potassiation can be converted back into the original FeSe phase upon depotassiation.In particular,small-sized nanoflakes exhibit better cycling perfor-mance with well-maintained structural integrity.This article presents the first successful demonstration of atomic-scale visualization that can reveal size-dependent potassiation dynamics.Moreover,it provides valuable guidelines for optimizing the dimensions of electrode materials for advanced PIBs.

A Hybrid Spatial Dependence Model Based on Radial Basis Function Neural Networks (RBFNN) and Random Forest (RF)

The majority of spatial data reveal some degree of spatial dependence. The term “spatial dependence” refers to the tendency for phenomena to be more similar when they occur close together than when they occur far apart in space. This property is ignored in machine learning (ML) for spatial domains of application. Most classical machine learning algorithms are generally inappropriate unless modified in some way to account for it. In this study, we proposed an approach that aimed to improve a ML model to detect the dependence without incorporating any spatial features in the learning process. To detect this dependence while also improving performance, a hybrid model was used based on two representative algorithms. In addition, cross-validation method was used to make the model stable. Furthermore, global moran’s I and local moran were used to capture the spatial dependence in the residuals. The results show that the HM has significant with a R2 of 99.91% performance compared to RBFNN and RF that have 74.22% and 82.26% as R2 respectively. With lower errors, the HM was able to achieve an average test error of 0.033% and a positive global moran’s of 0.12. We concluded that as the R2 value increases, the models become weaker in terms of capturing the dependence.

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

Hierarchical microstructures with high spatial frequency laser induced periodic surface structures possessing different orientations created by femtosecond laser ablation of silicon in liquids

High spatial frequency laser induced periodic surface structures(HSFLs)on silicon substrates are often developed on flat surfaces at low fluences near ablation threshold of 0.1 J/cm2,seldom on microstructures or microgrooves at relatively higher fluences above 1 J/cm^2.This work aims to enrich the variety of HSFLs-containing hierarchical microstructures,by femtosecond laser(pulse duration:457 fs,wavelength:1045 nm,and repetition rate:100 kHz)in liquids(water and acetone)at laser fluence of 1.7 J/cm^2.The period of Si-HSFLs in the range of 110–200 nm is independent of the scanning speeds(0.1,0.5,1 and 2 mm/s),line intervals(5,15 and 20μm)of scanning lines and scanning directions(perpendicular or parallel to light polarization direction).It is interestingly found that besides normal HSFLs whose orientations are perpendicular to the direction of light polarization,both clockwise or anticlockwise randomly tilted HSFLs with a maximal deviation angle of 50°as compared to those of normal HSFLSs are found on the microstructures with height gradients.Raman spectra and SEM characterization jointly clarify that surface melting and nanocapillary waves play important roles in the formation of Si-HSFLs.The fact that no HSFLs are produced by laser ablation in air indicates that moderate melting facilitated with ultrafast liquid cooling is beneficial for the formation of HSFLs by LALs.On the basis of our findings and previous reports,a synergistic formation mechanism for HSFLs at high fluence was proposed and discussed,including thermal melting with the concomitance of ultrafast cooling in liquids,transformation of the molten layers into ripples and nanotips by surface plasmon polaritons(SPP)and second-harmonic generation(SHG),and modulation of Si-HSFLs direction by both nanocapillary waves and the localized electric field coming from the excited large Si particles.

Dynamics of Advantageous Mutant Spread in Spatial Death-Birth and Birth-Death Moran Models

The spread of an advantageous mutation through a population is of fundamental interest in population genetics. While the classical Moran model is formulated for a well-mixed population, it has long been recognized that in real-world applications, the population usually has an explicit spatial structure which can significantly influence the dynamics. In the context of cancer initiation in epithelial tissue, several recent works have analyzed the dynamics of advantageous mutant spread on integer lattices, using the biased voter model from particle systems theory. In this spatial version of the Moran model, individuals first reproduce according to their fitness and then replace a neighboring individual. From a biological standpoint, the opposite dynamics, where individuals first die and are then replaced by a neighboring individual according to its fitness, are equally relevant. Here, we investigate this death-birth analogue of the biased voter model. We construct the process mathematically, derive the associated dual process, establish bounds on the survival probability of a single mutant, and prove that the process has an asymptotic shape. We also briefly discuss alternative birth-death and death-birth dynamics, depending on how the mutant fitness advantage affects the dynamics. We show that birth-death and death-birth formulations of the biased voter model are equivalent when fitness affects the former event of each update of the model, whereas the birth-death model is fundamentally different from the death-birth model when fitness affects the latter event.

Dynamic analysis of spatial convergence of green total factor productivity in China's primary provinces along its Belt and Road Initiative

This paper focuses on China's primary provinces along its Belt and Road Initiative,measures and analyses the provincial green total factor productivity (GTFP) development by GML index based on SBM directional distance function,discusses the temporal evolution characteristics of spatial convergence of the provincial GTFP under multiple spatial weight matrices,and estimates the net effect of China's Belt and Road Initiative on the development gap of provincial GTFP by regression discontinuity.The research shows that the provincial GTFP is generally good while the internal gap is relatively large.There is spatial absolute βconvergence and condition βconvergence in provincial GTFP,and the convergence speed has been signifcantly accelerated since the construction of China's Belt and Road Initiative.The current low economy level and infrastructure allocation efficiency of primary provinces restrict the GTFP development,while government expenditure has promoted the GTFP development,trade between provinces and countries along China's Belt and Road Initiative is negative to GTFP.China's Belt and Road Initiative has significantly narrowed the gap of provincial GTFP development with the net effect of-0.016.

Spatial sensitivity to absorption changes for various near-infrared spectroscopy methods:A compendium review

This compendium review focuses on the spatial distribution of sensitivity to localized absorption changes in optically diffuse media,particularly for measurements relevant to near-infrared spectroscopy.The three temporal domains,continuous wave,frequency domain,and time domain,each obtain different optical data types whose changes may be related to effective homogeneous changes in the absorption coefficient.Sensitivity is the relationship between a localized perturbation and the recovered effective homogeneous absorption change.Therefore,spatial sensitivity maps representing the perturbation location can be generated for the numerous optical data types in the three temporal domains.The review first presents a history of the past 30 years of work investigating this sensitivity in optically diffuse media.These works are experimental and theoretical,presenting one-,two-,and three-dimensional sensitivity maps for different Near-Infrared Spectroscopy methods,domains,and data types.Following this history,we present a compendium of sensitivity maps organized by temporal domain and then data type.This compendium provides a valuable tool to compare the spatial sensitivity of various measurement methods and parameters in one document.Methods for one to generate these maps are provided in Appendix A,including the code.This historical review and comprehensive sensitivity map compendium provides a single source researchers may use to visualize,investigate,compare,and generate sensitivity to localized absorption change maps.

Distributed Air &Missile Defense with Spatial Grasp Technology

A high-level technology is revealed that can effectively convert any distributed system into a globally programmable machine capable of operating without central resources and self-recovering from indiscriminate damages. Integral mission scenarios in Distributed Scenario Language (DSL) can be injected from any point, runtime covering & grasping the whole system or its parts, setting operational infrastructures, and orienting local and global behavior in the way needed. Many operational scenarios can be simultaneously injected into this spatial machine from different points, cooperating or competing over the shared distributed knowledge as overlapping fields of solutions. Distributed DSL interpreter organization and benefits of using this technology for integrated air and missile defense are discussed along with programming examples in this and other fields.

Global Electronic Dominance with Spatial Grasp

A high-level control technology will be revealed that can dynamically establish overwhelming dominance over distributed networked systems with embedded electronic devices and any communications between them. It is based on implanting of universal control modules (that may be concealed) into key system points which collectively interpret complex but compact mission scenarios in a special high-level Distributed Scenario language (DSL). Self-evolving and self-spreading in networks, matching them in a super-virus mode, DSL scenarios can analyze their structures and states and set up any behavior needed, including creation of benign or elimination of unwanted infrastructures. The scalable technology allows us to convert any distributed networked systems into a sort of integral spatial brain capable of analyzing and withstanding unpredictable situations in a variety of important domains.

Three Types of Spatial Function Zoning in Key Ecological Function Areas Based on Ecological and Economic Coordinated Development: A Case Study of Tacheng Basin, China

Three types of spatial function zoning is an effective measure for regional environmental protection and orderly development.For ecological and economic coordinated development, spatial function zones should be divided scientifically to clear its direction of development and protection. Therefore, based on ecological constraints, a beneficial discussion would be about the key ecological function areas adopting the concept of ecological protection restriction and supporting socioeconomic development for spatial function zoning. In this paper, the researchers, taking Tacheng Basin, Xinjiang of China as an example, choose township as basic research unit and set up an evaluation index system from three aspects, namely, ecological protection suitability, agricultural production suitability, and urban development suitability, which are analyzed by using spatial analysis functions and exclusive matrix method. The results showed that: 1) This paper formed a set of multilevel evaluation index systems for three types of spatial function zoning of the key ecological function areas based on a novel perspective by scientifically dividing Tacheng Basin into ecological space, agricultural space, and urban space,which realized the integration and scientific orientation for spatial function at the township scale. 2) Under the guidance of three types of spatial pattern, the functional orientation and suggestions of development and protection was clearly defined for ecological protection zones,ecological economic zones, agricultural production zones, and urban development zones. 3) A new idea of space governance is provided to promote the coordinated and sustainable development between ecology and economy, which can break the traditional mode of thinking about regional economic development, and offers a scientific basis and reference for macro decision-making.

The Effect of the Menstrual Cycle on Cognitive Performance: Spatial Reasoning, Visual & Numerical Memory

The menstrual cycle has been a topic of interest in relation to behavior and cognition for many years, with historical beliefs associating it with cognitive impairment. However, recent research has challenged these beliefs and suggested potential positive effects of the menstrual cycle on cognitive performance. Despite these emerging findings, there is still a lack of consensus regarding the impact of the menstrual cycle on cognition, particularly in domains such as spatial reasoning, visual memory, and numerical memory. Hence, this study aimed to explore the relationship between the menstrual cycle and cognitive performance in these specific domains. Previous studies have reported mixed findings, with some suggesting no significant association and others indicating potential differences across the menstrual cycle. To contribute to this body of knowledge, we explored the research question of whether the menstrual cycles have a significant effect on cognition, particularly in the domains of spatial reasoning, visual and numerical memory in a regionally diverse sample of menstruating females. A total of 30 menstruating females from mixed geographical backgrounds participated in the study, and a repeated measures design was used to assess their cognitive performance in two phases of the menstrual cycle: follicular and luteal. The results of the study revealed that while spatial reasoning was not significantly related to the menstrual cycle (p = 0.256), both visual and numerical memory had significant positive associations (p < 0.001) with the luteal phase. However, since the effect sizes were very small, the importance of this relationship might be commonly overestimated. Future studies could thus entail designs with larger sample sizes, including neuro-biological measures of menstrual stages, and consequently inform competent interventions and support systems.

Global and International Security Under Spatial Grasp Paradigm

Global and international security cannot be provided from a single point or a set of separate points whatever powerful these might be(even with quantum supercomputers!).It should rather be deeply embedded and integrated with bodies of real systems wherever in physical,virtual,or combined spaces they may exist.So global security capabilities should not only be distributed,but rather be really spatial,self-organized,and dynamic,also exhibiting overall integrity,awareness,and consciousness features.The paper describes applicability of the patented and revealed in 10 books Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)which conceptually and functionally match security problems of large distributed and heterogeneous systems.It investigates very practical security solutions for finding and tracing distribution of forbidden items,world roaming criminals,recovery from natural and human-made disasters,tracing and elimination of moving dangerous objects in terrestrial and celestial spaces,as well as analysis and restoration of damaged transport networks.It advises how different security infrastructures can be organized and managed,and how to cooperate and integrate within global security systems with higher awareness and consciousness levels over them.The provided security-oriented version of SGL can be quickly implemented and integrated with existing distributed management and security systems.

A Tight Prediction Interval for False Discovery Proportion under Dependence

The false discovery proportion (FDP) is a useful measure of abundance of false positives when a large number of hypotheses are being tested simultaneously. Methods for controlling the expected value of the FDP, namely the false discovery rate (FDR), have become widely used. It is highly desired to have an accurate prediction interval for the FDP in such applications. Some degree of dependence among test statistics exists in almost all applications involving multiple testing. Methods for constructing tight prediction intervals for the FDP that take account of dependence among test statistics are of great practical importance. This paper derives a formula for the variance of the FDP and uses it to obtain an upper prediction interval for the FDP, under some semi-parametric assumptions on dependence among test statistics. Simulation studies indicate that the proposed formula-based prediction interval has good coverage probability under commonly assumed weak dependence. The prediction interval is generally more accurate than those obtained from existing methods. In addition, a permutation-based upper prediction interval for the FDP is provided, which can be useful when dependence is strong and the number of tests is not too large. The proposed prediction intervals are illustrated using a prostate cancer dataset.

Spatial structural characteristics of the Deda ancient landslide in the eastern Tibetan Plateau:Insights from Audio-frequency Magnetotellurics and the Microtremor Survey Method

It is of crucial importance to investigate the spatial structures of ancient landslides in the eastern Tibetan Plateau’s alpine canyons as they could provide valuable insights into the evolutionary history of the landslides and indicate the potential for future reactivation.This study examines the Deda ancient landslide,situated in the Chalong-ranbu fault zone,where creep deformation suggests a complex underground structure.By integrating remote sensing,field surveys,Audio-frequency Magnetotellurics(AMT),and Microtremor Survey Method(MSM)techniques,along with engineering geological drilling for validation,to uncover the landslide’s spatial feature s.The research indicates that a fault is developed in the upper part of the Deda ancient landslide,and the gully divides it into Deda landslide accumulation zoneⅠand Deda landslide accumulation zoneⅡin space.The distinctive geological characteristics detectable by MSM in the shallow subsurface and by AMT in deeper layers.The findings include the identification of two sliding zones in the Deda I landslide,the shallow sliding zone(DD-I-S1)depth is approximately 20 m,and the deep sliding zone(DD-I-S2)depth is 36.2-49.9 m.The sliding zone(DD-Ⅱ-S1)depth of the DedaⅡlandslide is 37.6-43.1 m.A novel MSM-based method for sliding zone identification is proposed,achieving less than 5%discrepancy in depth determination when compared with drilling data.These results provide a valuable reference for the spatial structural analysis of large-deepseated landslides in geologically complex regions like the eastern Tibetan Plateau.

Spatial analysis and evaluation of a coal deposit by coupling AHP & GIS techniques

Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.

The Long-Lived Photon Echo Response Locking Effect in the Presence of External Non-Resonant Laser Pulses with a Different Spatial Orientation

The correlation of the inhomogeneous broadening of the resonance transition at different time intervals and the efficiency of long-lived photon echo response locking by the action of standing waves of non-resonant laser pulses are considered. It is shown that the long-lived photon echo response locking effect may be observed even at the angles of the relative orientation of the non-resonant standing wave laser pulses of less than one degree, due to the change in the correlation coefficient of inhomogeneous broadening at time intervals between the first and the second and after the third resonant laser pulses.

Geospatial Analysis of Urban Heat Island Effects and Tree Equity

In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.

A"messenger zone hypothesis"based on the visual three-dimensional spatial distribution of motoneurons innervating deep limb muscles

Coordinated contraction of skeletal muscles relies on selective connections between the muscles and multiple classes of the spinal motoneuro ns.Howeve r,current research on the spatial location of the spinal motoneurons innervating differe nt muscles is limited.In this study,we investigated the spatial distribution and relative position of different motoneurons that control the deep muscles of the mouse hindlimbs,which were innervated by the obturator nerve,femoral nerve,inferior gluteal nerve,deep pe roneal nerve,and tibial nerve.Locations were visualized by combining a multiplex retrograde tracking technique compatible with three-dimensional imaging of solvent-cleared o rgans(3DISCO)and 3-D imaging technology based on lightsheet fluorescence microscopy(LSFM).Additionally,we propose the hypothesis that"messenger zones"exist as interlaced areas between the motoneuron pools that dominate the synergistic or antagonist muscle groups.We hypothesize that these interlaced neurons may participate in muscle coordination as messenger neurons.Analysis revealed the precise mutual positional relationships among the many motoneurons that innervate different deep muscles of the mouse.Not only do these findings update and supplement our knowledge regarding the overall spatial layout of spinal motoneurons that control mouse limb muscles,but they also provide insights into the mechanisms through which muscle activity is coordinated and the architecture of motor circuits.

DER SPATIAL TURN IN DEN KLASSISCHEN ALTERTUMSWISSENSCHAFTEN(UND SPEZIELL IN DER EPIGRAPHIK)

Since the 1990s the so-called spatial turn has brought back space and topography into the discussion within historical studies,particular ancient studies.This survey reviews current trends and developments within the field and offers some perspectives on possible future developments related to space,material,objects,their agency,and frames.

BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.