Sequential Distribution Research Articles

Nigerian Defence Academy Shooting Zone: Soil Speciation of the Kwanar-Doya Military Shooting Range, Kachia, Kaduna State, Nigeria

The speciation of toxic metals of Co, Cr, Cu, Mn, Pb, Zn, Ni and As in Kwanar – Doya Shooting site of the Nigerian Army, Military Training, Base Camp, Kachia, Kaduna State, Nigeria was investigated. The soil physico-chemical parameters, total metal content and sequential extraction methods were determined in duplicates using standard methods. The pH ranged from 3.93–4.51, showing the high acidity of the soil and electro -conductivity gave a mean value of 0.11 ms / cm showing the poor nutrient value of the soil). While the mean total metals values were Zinc: 28.94 mg/kg, Nickel: 13.45mg/kg, Manganese: 78: 12 mg/kg, Lead: 40.6 mg/kg, Arsenic: 305 mg/kg, Chromium: 49.32 mg/kg, Cobalt: 162:50 mg/kg and copper: 7.3 mg/kg. All the metals were above the W.H.O permissible limit for toxic metals in soils except Zinc and Nickel. The sequential partitioning and distribution and variation of toxic metals in the various fractions of the Nigerian Defence Academy Shooting Range soil were in the following order: Cobalt: Residual > Bound to carbonate > Exchangeable > Organic > Fe – Mn Oxide Arsenic: Fe – Mn Oxide > Bound to carbonate > Residual > Organic > Chromium: Bound to carbonate > Exchangeable > Fe – Mn Oxide > Organic > Residual. Nickel: Fe – Mn Oxide > Exchangeable > Bound to carbonate > Residual > Organic. Manganese: Residual > Fe – Mn Oxide > Bound to carbonate > Organic > Exchangeable. Lead: Residual > Organic > Bound to carbonate > Exchangeable > Fe – Mn Oxide. Zinc: Fe – Mn Oxide > Residual > Organic > Bound to carbonate > Exchangeable. Copper: Residual > Fe – Mn Oxide > Exchangeable > Bound to carbonate > Organic. The Toxic metals speciation of the soil samples indicate that the toxic metals were predominately in the non-residual fractions suggestive of input by anthropogenic sources and human activities due to military exercise and are readily available for plant uptake. This could pose serious health risk to the military personnel using the training period. Thus phyto-remediation technique which is cheap and non-destructive is recommended to be applied to remedy the affected toxic metals in the soil for its continual use as a military training ground and also preserve the soil fertility for continued agricultural use of the area when there is no military operation.

High-intensity transient signals during transcatheter aortic valve implantation assessed by ultrasonic carotid artery blood-flow monitoring: A single center prospective observational study

BackgroundNo reports to date have assessed the procedural patterns of high-intensity transient signals (HITS) by monitoring blood flow in cervical arteries. The aim of this study was to examine the sequential distribution of HITS in each procedural phase and predictive factors for HITS during transcatheter aortic valve implantation (TAVI) by monitoring blood flow in the common carotid artery. MethodsThis prospective observational study included 73 patients who underwent TAVI via the transfemoral artery approach. We continuously evaluated and analyzed HITS from administration of heparin to valve implantation. ResultsHITS peaked during balloon valvuloplasty (BAV), amounting to almost 30% of the total HITS count, followed by valve implantation [BAV 141 (73–186) and valve implantation 86 (64–126), respectively]. In univariate and multivariate analysis, the Agatston score of the aortic valve and low-density lipoprotein were confirmed as independent predictors of HITS frequency with logarithmically converted coefficients of 0.00015 (p < 0.001) and 0.0032 (p = 0.027), respectively. ConclusionsThese results provide the first evidence that micro-emboli deriving from calcified burden were scattered primally during BAV, followed by valve implantation. The Agatston score may be a predictor for the amount of HITS.

A comparative evaluation of unsupervised deep architectures for intrusion detection in sequential data streams

Cybersecurity data remains a challenge for the machine learning community as the high volume of traffic makes it difficult to properly disambiguate anomalous from normal behaviour. That decision is the core of an intelligent Intrusion Detection System (IDS), a component responsible for raising alerts whenever a potential threat is detected. However, with high volume data in contemporary systems, these IDSs generate numerous alerts, too large for human operators to exhaustively investigate. Moreover, simply reporting a single possible threat is often not sufficient, since the security analyst has to investigate the alert without any further clues of the underlying cause. In order to combat these issues, we empirically compare popular deep neural learning architectures for the problem of intrusion detection in sequential data streams. Contrary to a majority of research studies, we do not take a classification-based approach that requires labeled examples of hostile attacks. Instead, we adopt an unsupervised anomaly detection approach that aims to model a benign sequential data distribution against which new test instances are compared to. We also examine one additional deep network in the form of an attention model capable of providing explanations in addition to its predictions; such information is of crucial importance to network operators since it provides additional guidance to resolve potential threats. For our experiments, we evaluate the models against a variety of data sets of different complexities, ranging from simple unidimensional (synthetic and Yahoo!) to more complex multi-source (CICIDS2017 and small real-world enterprise network) data streams. In order to facilitate end-user needs, we focus on ranking-based metrics for comparing different deep neural architectures. This evaluation is especially important for security analysts to prioritize their anomaly investigations. Overall, our experiments demonstrate that a variant of a recurrent neural network generally outperforms a popular non-sequential deep autoencoder commonly used for unsupervised anomaly detection. The attentional model did not provide sufficiently good performance and explanations that we discuss in our analysis. Nonetheless, given that the global financial outlays for cybersecurity are calculated in trillions of dollars, our evaluation and identification of the top-performing RNN architectures for anomaly detection in sequential data streams can lead to improved intelligent IDS design, while our contributions of attentional explanation will hopefully lay the foundations for future improvements to the explanatory capability of these intelligent learning-based IDSs.

“You Must Adhere Strictly to the Time and Days of Intake”: Medical Advice and Negotiations of Medical Authority in Nigerian HIV Consultations

Using the methodology of conversation analysis, this paper examines the practice of offering medical advice and its implication for negotiations of medical authority in Nigerian HIV consultations. Analyses of ninety treatment recommendation sequences from seventy audio-recorded interactions between doctors and HIV-positive patients reveal that doctors issue instructions as a form of medical advice on patients’ adherence to medical recommendations. During the advisory interactions, patients are held accountable for maintaining medical wellness, although the doctors’ reasons for offering medical advice, and the turn design and sequential distribution of the advice-giving sequence indicate that advice serves to enact authoritative roles. The findings are a counter-balance to the position, in existing conversation analysis research, that patients’ actions palliate medical authority. This paper calls for a broader conceptualisation of “adherence” and “medical authority” within medical institutional settings.

Distribution patterns of tau pathology in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a 4R-tauopathy predominated by subcortical pathology in neurons, astrocytes, and oligodendroglia associated with various clinical phenotypes. In the present international study, we addressed the question of whether or not sequential distribution patterns can be recognized for PSP pathology. We evaluated heat maps and distribution patterns of neuronal, astroglial, and oligodendroglial tau pathologies and their combinations in different clinical subtypes of PSP in postmortem brains. We used conditional probability and logistic regression to model the sequential distribution of tau pathologies across different brain regions. Tau pathology uniformly predominates in the neurons of the pallido-nigro-luysian axis in different clinical subtypes. However, clinical subtypes are distinguished not only by total tau load but rather cell-type (neuronal versus glial) specific vulnerability patterns of brain regions suggesting distinct dynamics or circuit-specific segregation of propagation of tau pathologies. For Richardson syndrome (n = 81) we recognize six sequential steps of involvement of brain regions by the combination of cellular tau pathologies. This is translated to six stages for the practical neuropathological diagnosis by the evaluation of the subthalamic nucleus, globus pallidus, striatum, cerebellum with dentate nucleus, and frontal and occipital cortices. This system can be applied to further clinical subtypes by emphasizing whether they show caudal (cerebellum/dentate nucleus) or rostral (cortical) predominant, or both types of pattern. Defining cell-specific stages of tau pathology helps to identify preclinical or early-stage cases for the better understanding of early pathogenic events, has implications for understanding the clinical subtype-specific dynamics of disease-propagation, and informs tau-neuroimaging on distribution patterns.

Astroglia and Tau: New Perspectives.

Astrocytes contribute to the pathogenesis of neurodegenerative proteinopathies as influencing neuronal degeneration or neuroprotection, and also act as potential mediators of the propagation or elimination of disease-associated proteins. Protein astrogliopathies can be observed in different forms of neurodegenerative conditions. Morphological characterization of astrogliopathy is used only for the classification of tauopathies. Currently, at least six types of astrocytic tau pathologies are distinguished. Astrocytic plaques (AP), tufted astrocytes (TAs), ramified astrocytes (RA), and globular astroglial inclusions are seen predominantly in primary tauopathies, while thorn-shaped astrocytes (TSA) and granular/fuzzy astrocytes (GFA) are evaluated in aging-related tau astrogliopathy (ARTAG). ARTAG can be seen in the white and gray matter and subpial, subependymal, and perivascular locations. Some of these overlap with the features of tau pathology seen in Chronic traumatic encephalopathy (CTE). Furthermore, gray matter ARTAG shares features with primary tauopathy-related astrocytic tau pathology. Sequential distribution patterns have been described for tau astrogliopathies. Importantly, astrocytic tau pathology in primary tauopathies can be observed in brain areas without neuronal tau deposition. The various morphologies of tau astrogliopathy might reflect a role in the propagation of pathological tau protein, an early response to a yet unidentified neurodegeneration-inducing event, or, particularly for ARTAG, a response to a repeated or prolonged pathogenic process such as blood-brain barrier dysfunction or local mechanical impact. The concept of tau astrogliopathies and ARTAG facilitated communication among research disciplines and triggered the investigation of the significance of astrocytic lesions in neurodegenerative conditions.

A Method for Cleaning Power Grid Operation Data Based on Spatiotemporal Correlation Constraints

Bad data in a power system fail to accurately reflect its state of operation. Cleaning bad data is thus necessary for the situational analysis of a data-based power system. Methods for the identification and modification of bad data based on state estimation may fail to converge in iterative calculations, and yield poor results when the errors are significant. State estimation also involves non-linear computation, which incurs a significant computational overhead and makes it difficult to efficiently handle large volumes of data. To solve these problems, this paper proposes a method for the detection and identification of bad data based on constraints on spatial–temporal correlation. In the spatial domain, we fix the equivalent power balance condition through the topology of the network. In sequential distribution, we establish data constraints based on the similarity of data among temporal sections. We then check the data in combination with the spatial–temporal correlation constraints. The proposed method was applied to an IEEE 14-bus system and a provincial grid, and the results show that it can reliably detect and modify bad data to significantly improve their quality. The proposed approach avoids non-linear calculations, is computationally efficient, and can quickly detect and modify bad data.

Real-time Reliability Evaluation Based on Stochastic Degradation Process and Sequential Joint Distribution Estimation

According to the different performance degradation paths, reliability curves and parameters of each product in service phase, the reliability and remaining life of components at current moment can be evaluated in real-time reliability assessment by integrating real-time status, historical information and service time of components. The realtime reliability evaluation is valued because it is more personalized, precise, real-time and lean than traditional methods. Furthermore, the results from real-time reliability assessment can also represent the health status of component at current time. In the current research, real-time reliability assessment mainly relies on regression analysis and time series analysis, but these two methods are mainly used to describe the component degradation process, and cannot reflect the influence of external random environment on the component state change. At the same time, due to these limitations of time, economy and test conditions, it is also worth studying how to obtain more accurate and practical reliability distribution and determine a detection interval under the condition of less data. Therefore, based on the analysis of real-time reliability evaluation principle, a more appropriate real-time reliability evaluation method and the detection interval decision model are proposed by means of random degradation process, parameter sequence test joint distribution estimation and failure risk. The result from this method is a quantized value, which is convenient for the direct application of the follow-up maintenance decision research. Therefore, the research in this paper has extensive reference value and practical application prospect.

Improvement of the Method of Calculation of Steady-State Modes of Urban Electric Networks Taking into Account Consumer Energy Sources

The method of calculation of the steady-state mode of the open city distribution electric network with small generation sources is offered. It is shown that the city electric network consists of passive and active physical elements. Passive elements include power transformers and linear regulators, overhead and cable power lines, current-limiting reactors, etc. Active elements of networks are power sources (transformer inputs of low voltage of feeding substations and distributed small generation sources) and loads, mathematical models of which can be various. Power sources in urban distribution networks of 10 kV and below are classified by type and power and can be of two kinds, viz. power feeding centers of the network and small generation sources. Consumer loads are modeled by current sources connected to network nodes. The parameters of the current sources are usually graphs of the change of the module of the actual current value and the power factor in time. The values of these parameters in single-line substitution schemes of 6–10 kV distribution networks with isolated neutral are assumed to be average for three phases. The power centers are transformer inputs of low voltage power substations of the main electric networks of 35 kV and above, equipped with digital devices of the account of the electric power connected to the automated system of control and accounting of power resources. The developed technique allows receiving the refined balanced calculation model of the steady mode of the open city network for the set time of the daily schedule. It includes the sequential distribution of the specified power of each network power supply between its loads, followed by clarification of flows and power losses in the sections, as well as voltages and actual loads in the nodes of the scheme by the overlay method.

Clustering Coastal Land Use Sequence Patterns along the Sea–Land Direction: A Case Study in the Coastal Zone of Bohai Bay and the Yellow River Delta, China

Specific knowledge about the characteristics of coastal land use along the sea–land direction helps to better understand the spatial heterogeneity of coastal land use, which could offer scientific support for rational land management and the sustainable development of the coastal zone. However, the traditional methods including buffering or the regional method are hard to extract detailed spatial structure and location correlations of coastal land use along the sea–land direction. Therefore, we developed a model, called sequence–based clustering of coastal land use pattern (SCCLUP), to mine the coastal land use sequence patterns (CLUSPs) along the sea–land direction. As a case study in the major coastal zone of Bohai Bay and the Yellow River Delta from 1990 to 2010, we found that: (1) The land use showed a sequential distribution along the sea–land direction. And the land use closed to shoreline and inland boundary had relative stable sequential location along the sea–land direction. However, the middle land uses had dynamic sequential locations that led to multiple CLUSPs; (2) due to the increasing percent of construction land, the artificial level of CLUSPs was continuously increasing and new CLUSPs tended to distribute around port areas. Different CLUSPs with similar land use sequential relationships tended to have similar land use structure along the sea–land direction; (3) the land uses sequential location along the sea–land direction revealed the actual distance of land use to the shoreline and had a tight correlation with environmental factors (salinity, water, and landform). The land use with large increasing and wide adaptivity (like construction land) had a large impact on the changes of CLUSPs in the study area. Therefore, strong control should be provided for the excessive expansion of land use like construction land to limit the over changes in land use pattern along the sea–land direction. Additionally, the spatial heterogeneity of land use along the sea–land direction should be considered to a better understanding of anthropic impacts on the coastal zone.

Hurst entropy: A method to determine predictability in a binary series based on a fractal-related process.

Shannon's concept of information is related to predictability. In a binary series, the value of information relies on the frequency of 0's and 1's, or how it is expected to occur. However, information entropy does not consider the bias in randomness related to autocorrelation. In fact, it is possible for a binary temporal series to carry both short- and long-term memories related to the sequential distribution of 0's and 1's. Although the Hurst exponent measures the range of autocorrelation, there is a lack of mathematical connection between information entropy and autocorrelation present in the series. To fill this important gap, we combined numerical simulations and an analytical approach to determine how information entropy changes according to the frequency of 0's and 1's and the Hurst exponent. Indeed, we were able to determine how predictability depends on both parameters. Our findings are certainly useful to several fields when binary times series are applied, such as neuroscience to econophysics.

Fast Wireless Power Transfer for Multiple Receivers in Linear Topology

In a wireless power transfer (WPT) system in which multiple receivers are lined up on one side of a transmitter, the farthest receiver can experience difficulty receiving the required power from the transmitter because most of the power tends to be transferred to the nearest receiver. It is therefore necessary to find some means for providing sufficient power to charge the farthest receiver, in order to complete the charging of all the receivers within a reasonable time. In this paper, we propose two fast WPT methods: equal power distribution (EPD), and sequential power distribution (SPD). EPD allows all receivers to receive the same power by adjusting their load resistances and thus completing their charging at the same time, while SPD sequentially charges receivers in order according to location, and incorporates each charged receiver into the relay to assist with charging the next receiver. We analyze the charging times of the two methods based on equivalent circuit models and validate them using experiments by fabricating resonators. The analysis and experimental results show that the proposed EPD and SPD decrease the system charging time considerably compared with the conventional method in which there is no control.

On detecting changes in the jumps of arbitrary size of a time-continuous stochastic process

This paper introduces test and estimation procedures for abrupt and gradual changes in the entire jump behaviour of a discretely observed Itō semimartingale. In contrast to existing work we analyse jumps of arbitrary size which are not restricted to a minimum height. Our methods are based on weak convergence of a truncated sequential empirical distribution function of the jump characteristic of the underlying Itō semimartingale. Critical values for the new tests are obtained by a multiplier bootstrap approach and we investigate the performance of the tests also under local alternatives. An extensive simulation study shows the finite-sample properties of the new procedures.

Understanding the Relevance of Aging-Related Tau Astrogliopathy (ARTAG)

Aging-related tau astrogliopathy (ARTAG) is an umbrella term that encompasses a spectrum of morphological abnormalities seen in astrocytes of the aging brain using immunostaining for pathological forms of the microtubule-associated protein tau. Morphologies of ARTAG include thorn-shaped astrocytes (TSA), and additionally granular/fuzzy astrocytes (GFA) characterized by fine granular tau immunoreactivity extending into the astrocytic processes. Thorn-shaped astrocytes can be present in the same brain in subpial, subependymal, perivascular, and white and gray matter locations together with GFAs, which are seen in the gray matter. Primary tauopathies show ARTAG-related morphologies as well, moreover, GFA has been proposed to present a conceptual link between brain ageing and primary tauopathies. Sequential distribution patterns have been recognized for subpial, white and gray matter ARTAG. This either suggests the involvement of astrocytes in the propagation of tau pathology or reflects the consequence of a long-term pathogenic process such as barrier dysfunction, local mechanical impact, or early response to neuronal degeneration. The concept of ARTAG facilitated communication among neuropathologists and researchers, informed biomarker researchers with focus on tau-related indicators and motivated further exploration of the significance of astrocytic lesions in various neurodegenerative conditions.

Label Stacking Scenarios in Hybrid Wavelength and Code-Switched GMPLS Networks

Multi-protocol label switching (MPLS) is a promising solution to implement high-speed internet protocol (IP) networks by reducing the layer number. To meet the increasing demand for data traffic, optical packet switching (OPS) is integrated under IP to provide high bandwidth to end users. Generalized MPLS (GMPLS) is perfectly compatible with the routing algorithm in IP/MPLS as it supports packet-switching functions. In this paper, we investigate the label stacking scenarios in GMPLS networks. In GMPLS, label stacking is done to reduce the node complexity by appending multiple labels to a single packet. Wavelength-division multiplexing (WDM) and optical code-division multiplexing (OCDM) signals have been widely used as identifying labels. As the labels can be permutated among the wavelengths or code dimensions, the structure of a label stack can be varied. However, studies on the relationship between label stacking scenarios and network performance are limited. To investigate this issue, we propose three label stacking models: sequential code distribution; sequential wavelength distribution, and random label distribution. The simulation results show that the sequential wavelength assignment, wherein the labels are uniformly distributed among the wavelengths, exhibits the best system performance in terms of the label-error rate (LER).

Bony pseudoteeth of extinct pelagic birds (Aves, Odontopterygiformes) formed through a response of bone cells to tooth-specific epithelial signals under unique conditions

Modern birds (crown group birds, called Neornithes) are toothless; however, the extinct neornithine Odontopterygiformes possessed bone excrescences (pseudoteeth) which resembled teeth, distributed sequentially by size along jaws. The origin of pseudoteeth is enigmatic, but based on recent evidence, including microanatomical and histological analyses, we propose that conserved odontogenetic pathways most probably regulated the development of pseudodentition. The delayed pseudoteeth growth and epithelium keratinization allowed for the existence of a temporal window during which competent osteoblasts could respond to oral epithelial signaling, in place of the no longer present odontoblasts; thus, bony pseudoteeth developed instead of true teeth. Dynamic morphogenetic fields can explain the particular, sequential size distribution of pseudoteeth along the jaws of these birds. Hence, this appears as a new kind of deep homology, by which ancient odontogenetic developmental processes would have controlled the evolution of pseudodentition, structurally different from a true dentition, but morphologically and functionally similar.

Learning-Aided Stochastic Network Optimization With State Prediction

We investigate the problem of stochastic network optimization in the presence of state prediction and non-stationarity. Based on a novel state prediction model featured with a distribution-accuracy curve, we develop the predictive learning-aided control ( PLC ) algorithm, which jointly utilizes historic and predicted network state information for decision making. PLC is an online algorithm that consists of three key components, namely, sequential distribution estimation and change detection, dual learning, and online queue-based control. We show that for stationary networks, PLC achieves a near-optimal utility-delay tradeoff. For non-stationary networks, PLC obtains an utility-backlog tradeoff for distributions that last longer than a time proportional to the square of the prediction error, which is smaller than that needed by backpressure (BP) for achieving the same utility performance. Moreover, PLC detects distribution change $O(w)$ slots faster with high probability ( $w$ is the prediction size) and achieves a convergence time faster than that under BP. Our results demonstrate that state prediction helps: 1) achieve faster detection and convergence and 2) obtain better utility-delay tradeoffs. They also quantify the benefits of prediction in four important performance metrics, i.e., utility (efficiency), delay (quality-of-service), detection (robustness), and convergence (adaptability) and provide new insight for joint prediction, learning, and optimization in stochastic networks

The Impact of E-book Distribution on Print Sales: Analysis of a Natural Experiment

Digital distribution introduces many new strategic questions for the creative industries—notably, how the use of new digital channels will impact sales in established channels. We analyze this question in the context of e-book and hardcover sales by exploiting a natural experiment that exogenously delayed the release of a publisher’s new Kindle e-books in April and May 2010. Using new books released simultaneously in e-book and print formats in March and June 2010 as the control group, we find that delaying e-book availability results in a 43.8% decrease in e-book sales but no increase in print book sales on Amazon.com or among other online or offline retailers. We also find that the decrease in e-book sales is greater for books with less prerelease buzz. Together, we find no evidence of strong cannibalization between print books and e-books in the short term and no support for the sequential distribution of books in print versions followed by e-book versions. This paper was accepted by Lorin Hitt, information systems.

Sequential stages and distribution patterns of aging-related tau astrogliopathy (ARTAG) in the human brain

Aging-related tau astrogliopathy (ARTAG) describes tau pathology in astrocytes in different locations and anatomical regions. In the present study we addressed the question of whether sequential distribution patterns can be recognized for ARTAG or astroglial tau pathologies in both primary FTLD-tauopathies and non-FTLD-tauopathy cases. By evaluating 687 postmortem brains with diverse disorders we identified ARTAG in 455. We evaluated frequencies and hierarchical clustering of anatomical involvement and used conditional probability and logistic regression to model the sequential distribution of ARTAG and astroglial tau pathologies across different brain regions. For subpial and white matter ARTAG we recognize three and two patterns, respectively, each with three stages initiated or ending in the amygdala. Subependymal ARTAG does not show a clear sequential pattern. For grey matter (GM) ARTAG we recognize four stages including a striatal pathway of spreading towards the cortex and/or amygdala, and the brainstem, and an amygdala pathway, which precedes the involvement of the striatum and/or cortex and proceeds towards the brainstem. GM ARTAG and astrocytic plaque pathology in corticobasal degeneration follows a predominantly frontal-parietal cortical to temporal-occipital cortical, to subcortical, to brainstem pathway (four stages). GM ARTAG and tufted astrocyte pathology in progressive supranuclear palsy shows a striatum to frontal-parietal cortical to temporal to occipital, to amygdala, and to brainstem sequence (four stages). In Pick’s disease cases with astroglial tau pathology an overlapping pattern with PSP can be appreciated. We conclude that tau-astrogliopathy type-specific sequential patterns cannot be simplified as neuron-based staging systems. The proposed cytopathological and hierarchical stages provide a conceptual approach to identify the initial steps of the pathogenesis of tau pathologies in ARTAG and primary FTLD-tauopathies.

Insights into the kinematics and dynamics of the Luanshibao rock avalanche (Tibetan Plateau, China) based on its complex surface landforms

Complex topographic features on the surfaces of rock avalanche deposits have been regarded as important indicators for understanding avalanche kinematics and dynamics. Based on a combination of remote sensing data and in-situ observations of surface landforms, including toreva blocks, transverse and longitudinal ridges, ridges separated by conjugate troughs, and hummocks, a giant Holocene rock avalanche on the Tibetan Plateau is recognized. This work aims to understand the kinematics of this event. In planview, the tongue-shaped rock avalanche exhibits a clear sequential distribution of various landforms. The translation zone (II) is characterised by toreva blocks originating from extension. In subzone III-1 of the accumulation zone (III), compression-related transverse ridges are well developed. Longitudinal ridges resulting from lateral velocity differences due to radial spreading are present in the front part of subzone III-1. Farther down, ridges separated by conjugate troughs (generated by a combination of compression and radial spreading) are common in subzone III-2. Subzone III-3 is characterised by abundant scattered hummocks with circular to oval shapes. Based on the distributions of these landforms, this rock avalanche is proposed to have mainly experienced a motion featuring laminar flow with radial spreading in its distal and marginal parts. During transport, three distinct processes appear to have occurred in the avalanche mass from the proximal to the distal zones: extension-dominated sliding in zone II, compression-dominated sliding in subzones III-1 and III-2, and rapid radial spreading in subzone III-3.