Manufacturing processes involving chemical agents are evolving at great speed. In this context, managing chemical risk is especially important towards preventing both occupational accidents and major accidents. Directive 89/391/EEC and Directive 2012/18/EU, respectively, are enforced in the European Union (EU) to this end. These directives may be further complemented by the recent ISO 45001:2018 standard regarding occupational health and safety management systems. These three management systems are closely related. However, scientific literature tackles the researching of these accidents independently. Thus, the main objective of this work is to identify and analyse the links and transitional spaces between the risk management of both types of accident. Among the results obtained, three transitional spaces can be pointed out which result from the intersection of the three systems mentioned. Similarly, the intersection of these spaces gives shape to a specific transitional space defined by the individual directives linked to Directive 89/391/EEC. These results are limited from a regulatory and technical perspective. Thus, the results are a starting point towards developing models that integrate the management systems studied.  In the past few years, manufacturing processes involving chemical substances have evolved to a great extent, from the new technologies applied to these processes to the new products and materials produced and their regulatory framework. The chemical industry is at the heart of the European Union (EU) manufacturing industry, representing approximately 7% of EU industrial production and a 1.1% share of EU GDP. It supplies two-thirds of its production to other sectors within the manufacturing industry [In regard to the regulatory framework in the EU, two relatively-recent regulations stand out at first glance. Regulation (EC) No 1907/2006 on Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH Regulation), aims to protect human health and the environment by ensuring greater safety in the production and use of chemical substances. The REACH Regulation, which entered into force in 2007, applies to all chemical substances and thus has an impact on many businesses .In 2018, approximately 145,000 substances were classified according to the CLP Regulation [This context of change generates both opportunities and challenges in many fields of knowledge. Among these fields, risk management is particularly important, both from a systemic point of view and from more specific perspectives. Among these specific perspectives, chemical risk management should be noted in order to prevent both occupational accidents and major accidents in manufacturing environments where hazardous materials are used. For this, two separate and solid legislative frameworks exist in the EU.In the case of the risk management of occupational accidents, Directive 89/391/EEC on the introduction of measures to encourage improvements in occupational safety and health (OSH) should be pointed out . This diIn the case of the risk management of major accidents and hazards involving dangerous substances, Directive 2012/18/EU is applicable .Hence, these risk management frameworks are closely related  and, as In this regard, using the ScienceDirect database , the seaThis circumstance defines a closed border between these management systems, making it difficult to develop integrative techniques and methodologies that favour the reduction of risk due to hazardous substances. In addition to the described relationship between directives, the recent opportunity defined by the ISO 45001:2018 standard on OSH management systems  should bThus, the main objective of this study is to identify and analyze the links and transitional spaces between the risk management of occupational accidents and major accidents involving hazardous materials. To achieve this goal, the methodology followed by this study is based on researching and carrying out a comparative analysis of the legal and standardised context described above. To this end, this work is organised as follows: (1) study of the legal context within the framework of the EU; (2) comparative analysis between management systems derived from Directive 89/391/EEC  and DireDirective 2012/18/EU  is applicable in regard to the management of major accidents and hazards involving dangerous substances. This directive states that its provisions should be applied without prejudice to the provisions of Union law relating to OSH and the working environment, and, in particular, without prejudice to Council Directive 89/391/EEC. The object of Directive 89/391/EEC  is to introduce measures to encourage improvements in OSH. To this end, it contains general principles concerning the prevention of occupational risks, the protection of safety and health, the elimination of risk and accident factors, the informing, consultation, balanced participation in accordance with national laws and/or practices and training of workers and their representatives, as well as general guidelines for the implementation of said principles.The Framework Directive serves as basis for more specific directives covering all the risks connected with safety and health in the workplace. Thus, 20 specific directives have been enacted to date since 1989, as listed in Considering that the objectives of this study are linked to major accidents and occupational accidents, both concepts will be defined below. Then, the main relationships that exist between the directives involved in the legal context set out here will be analysed.Directive Seveso III defines ‘major accident’ as an occurrence such as a major emission, fire, or explosion resulting from uncontrolled developments in the course of the operation of any establishment covered by this directive, and leading to serious danger to human health or the environment, immediate or delayed, inside or outside the establishment, and involving one or more dangerous substances.The Framework Directive and its specific directives do not define occupational accidents. To this end, others sources are required. For example, Eurostat defines an occupational accident (or accident at work) as a discrete occurrence during the course of work which leads to physical or mental harm . The ISOComparing the definitions for major accidents and occupational accidents, it could be said that a major accident could also be considered an occupational accident whenever there is harm to workers . Among the specific directives developed following the Framework Directive, Directive 98/24/EC on chemical agents  is the oIn any case, there are other directives besides Directive 98/24/EC on chemical agents  that areThese events are covered by the industrial safety technologies (IST) studied by Sebastián and Brocal , which cSebastián and Brocal  studied Directive 98/24/EC defines ‘Chemical agent’  as any cThe main difference observed on comparing the definitions of ‘dangerous substance’ (Seveso III) and ‘hazardous chemical agent’ (Directive 98/24/EC ), lies iThus, Directive 98/24/EC  will be Additionally, Directive 98/24/EC defines ‘Activity involving chemical agents’ as any work in which chemical agents are used, or are intended to be used, in any process, including production, handling, storage, transport or disposal and treatment, or which result from such work . DirectiThe main difference observed in regard to criteria regarding the presence of dangerous substances again lies in the variables collected in Annex I of Directive Seveso III. Thus, Directive 98/24/EC  will be Directive 98/24/EC on chemical agents  is complValor Límite Ambiental) have been identified according to the document on the limits of chemical agents for professional exposure in Spain [With the aim of establishing these links, in Spain .VLA are reference values for chemical agent concentration in the air and represent the conditions for which it is believed that, based on current knowledge, most workers may be exposed to on a daily basis throughout their work life without suffering adverse effects on their health .Thus, the 7 substances mentioned will be subject to the implementation of Directive Seveso III according to the figure collected in columns 2 and 3. Additionally, these substances fall within the scope of Directive 98/24/EC  wheneverAlthough not contained in Directive 89/654/EEC  lays dowOn the other hand, Directive Seveso III shall apply to establishments. Establishment means the whole location under the control of an operator where dangerous substances are present in one or more installations, including common or related infrastructures or activities; establishments are either lower-tier establishments or upper-tier establishments. Thus, establishments under Seveso III are also workplaces under the definition of Directive 89/654/EEC .Directive Seveso III defines ‘installation’ as a technical unit within an establishment and whether at or below ground level, in which dangerous substances are produced, used, handled or stored; it includes all the equipment, structures, pipework, machinery, tools, private railway sidings, docks, unloading quays serving the installation, jetties, warehouses or similar structures, floating or otherwise, necessary for the operation of that installation.Also, Directive 2009/104/EC defines ‘work equipment’ as follows: any machine, apparatus, tool or installation used at work . InstallAs a result, the concept of installation, as defined by Directive Seveso III, may be considered to be part of the scope of Directive 2009/104/EC on work equipment , as wellFurthermore, Directive 98/24/EC  specificDirective Seveso III indicates that member states shall require the operator to draw up a document in writing setting out the major-accident prevention policy (MAPP) and to ensure that it is properly implemented. The MAPP shall be implemented by appropriate means, structures and by a safety management system, in accordance with Annex III of this directive, and it will be proportionate to the major-accident hazards, and the complexity of the organization or the activities of the establishment. The Framework Directive does not explicitly develop a safety management system. However, it contains general principles concerning the prevention of occupational risks, the protection of safety and health, the elimination of risk and accident factors, the informing, consultation, balanced participation in accordance with national laws and/ or practices and training of workers and their representatives, as well as general guidelines for the implementation of the said principles.In themselves, the aforementioned general principles form the basis for a management system; in this case, a system to manage the safety and health of workers. To develop this, each member state of the European Union must transpose the Framework Directive into their national legal systems. By way of example, Law 31/1995 on occupational risk prevention transposes the Framework Directive into Spanish law . This LaAlso, Royal Decree 39/1997, which validates the Regulation on Prevention Services, develops those aspects that make it possible to integrate occupational risk prevention management into the undertaking’s activities and across the hierarchical levels thereof, based on a plan that includes work techniques, organisation and conditions . Thus, aCorrespondence may be classified as strong, weak or non-existent. Correspondence is strong when an issue in Annex III has its direct equivalence  with one or more articles of the Framework Directive. Correspondence is weak when an issue only has partial equivalence. And, obviously, correspondence is non-existent whet there is no equivalence.Considering this, there is strong correspondence in regard to the following sections of Annex III: (i) Organization and personnel, (ii) Identification and evaluation of major hazards, (iv) Management of change, and (v) Planning for emergencies.Correspondence is weak in sections (iii) Operational control and (vi) Monitoring performance. In regard to section (iii), the Framework Directive does not explicitly state: the management and control of risks associated with ageing equipment installed in the establishment and corrosion. In regard to section (vi), the Framework Directive does not explicitly state: the adoption and implementation of procedures for the ongoing assessment of compliance with the objectives set by the operator’s MAPP and safety management system; near misses. There is no (explicit) correspondence in regard to section (vii) regarding Audit and review.Furthermore, the Framework Directive contains specific guidelines in regard to chemical agents. These guidelines may be understood in terms of the relevance of the risk of such agents on occupational risk overall. Specifically, article 6.2 of the directive states as one of the general principals of preventive activity: replacing the dangerous by the non-dangerous or the less dangerous. Also, article 6.3.a: evaluate the risks to the safety and health of workers, inter alia in the choice of work equipment, the chemical substances or preparations used, and the fitting-out of workplaces. In order to carry out such assessment regarding chemical substances, Directive 98/24/EC  and DireConsidering that these directives are part of the development of the Framework Directive, they share with it the general principles of risk management. As a result, the minimum provisions for the protection of workers contained in each directive must be managed under the said general management principles. Thus, a correspondence may be observed between the said principles and provisions, from the general to the specific.Such correspondence makes it possible, in turn, to relate the sections of Annex III of Directive Seveso III with the specific provisions of each directive. This correspondence with the aforementioned directives may be seen in Thus, comparing the results of Implementing an OSH management system conforming to the ISO 45001:2018 standard enables an organization to manage its OSH risks and improve its OSH performance . AccordiAs indicated by the ISO 45001:2018 standard, its adoption in a given organization, however, will not in itself guarantee prevention of work-related injury and ill health to workers, provision of safe and healthy workplaces and improvement of OSH performance . So, in As with the previous section, which carried out a comparative analysis between management systems derived from the Framework Directive and Directive Seveso III, this section contains a similar analysis, using the same criteria, comparing between management systems derived from the ISO 45001:2018 standard  and DireHence, as The results from such analysis establish a strong correspondence with all sections from Annex III except with section (iii) Operational control, where aspects related to management and control of the risks associated with ageing equipment installed in the establishment and corrosion are not explicitly stated by the ISO 45001:2018 standard . This isAs a result of this correspondence, the ISO 45001:2018 standard  is linkePlan: determine and assess OSH risks, OSH opportunities and other risks and other opportunities, establish the OSH objectives and processes necessary to deliver results in accordance with the organization’s OSH policy;Do: implement the processes as planned;Check: monitor and measure activities and processes with regard to the OSH policy and OSH objectives, and report the results;Act: take actions to continually improve OSH performance towards achieving the intended outcomes;On the other hand, the OSH management system approach defined by the ISO 45001:2018 standard  is foundThe ISO 45001:2018 standard incorporates the PDCA concept into a new framework . This frAn analysis is carried out below of the main transitional spaces that arise from the results obtained in the previous sections. Each of these transitional spaces may be understood as the intersection between the correspondences identified between the different sets analysed: that is, the legal context and management systems derived from Directive Seveso III, the Framework Directive and the ISO 45001:2018 standard .As a result of the analysis carried out in the legal context section, To show these links summarily, the same thread has been followed that configures the structure of the legal context section. To this end, the basic outline of a general manufacturing process has been considered, involving chemical agents  of the Framework Directive, are not within the remit of this study. However, it should be pointed out that there may be connections to other regulations, such as the REACH Regulation  and CLP Activity involving chemical agents: Directive 98/24/EC on chemical agents [l agents  will be l agents , as showWorkplaces: Directive 98/654/EEC on Workplaces [rkplaces  is applirkplaces . This coInstallation: Directive 2009/104/EC on work equipment [quipment , as wellquipment , will beThe main transitional spaces between these links, as shown in The four transitional spaces (TS) represented conceptually in Transitional space TS 1 is configured by the correspondence that exists between the structure of the Framework Directive and the management systems derived from Directive Seveso III. Similarly, TS 2 is configured by the correspondence that exists between the structure of the ISO 45001:2018 standard and the management system derived from Directive Seveso III. Transitional space TS 3 may be considered a ‘natural space’ between the Framework Directive and the ISO 45001:2018 standard  since thIn any case, given that the result of implementing the ISO 45001:2018 standard  may be uAdditionally, given that the provisions of Directive 98/24/EC on chemical agents  and DireThe said results may be considered as a specific correspondence transferred from transitional space TS 1 to transitional space TS 4 when the intersection of the three systems takes place. Thus, TS 4 may be considered to include, at least, the provisions of Directive 98/24/EC  and DireEven if this specific transitional space has been studied in regard to the aforementioned directives, it should be pointed out that other directives, from those considered in There are signs of a revitalizing interest in foundational issues in risk assessment and management, which is welcome and necessary for meeting the challenges currently faced by the field of risk. These are related to societal problems and complex technological and emerging risks  which caThe second European Survey of Enterprises on New and Emerging Risks reveals that dangerous substances  are most prevalent in the European Union in certain sectors such as manufacturing (51.7%) . As a reIn this context, Brocal et al.  considerThere is a general research focus on dynamic risk assessment and management rather that static or traditional risk assessment , which cHowever, this study does not distinguish between the risk management of both types of risks; that is, between traditional risk and emerging risk. This is due to the general characteristics of the legal and standardised context in which this study has been carried out, towards meeting the main objective set out.In any case, this objective may be extended in future research in the direction of emerging risk management. In this regard, the CWA 16649:2013 standard on managing emerging technology-related risks may be considered to be a reference management system . Such a In regard to the definitions for ‘accident’ considered in this study, ‘major accident’ is defined by Directive Seveso III, while ‘occupational accident’ is not defined by the directives studied. Therefore, other sources are required. Besserman and Mentzer  considerIn any case, a major accident can also be considered to be an occupational accident if harm to workers exists. Inversely, an occupational accident can also be a major accident when it meets the requirements set out in Directive Seveso III. The causality relationship between both types of accident has not been studied here, although its interest in the sphere of safety is evident. In the 1970s, the effect of human actions and organizational factors on accident occurrence was recognized, but it took until the mid- 1980s before management became aware that they were key to achieving a good level of both occupational and process safety . The incThe main correspondence between risk management in both types of accidents is the presence in the manufacturing process of one or more of the hazardous substances included in Annex I of Directive Seveso III, for which directives derived from the Framework Directive are also applicable. The said directives may be understood as the deployment of this correspondence into further links that are more specific, giving rise to two types of transitional spaces: functional transitional spaces and regulatory transitional spaces.Functional transitional spaces  are interconnected as briefly outlined in As regarding regulatory transitional spaces, they are defined by the intersections between the risks management systems studied through the Framework Directive, Directive Seveso III and the ISO 45001:2018 standard.The links shown in This result is coherent under the perspective of the Framework Directive, which compiles a set of general guidelines that are further developed by specific directives, as shown in the results in As regards the correspondence between management systems derived from the ISO 45001:2018 standard and Directive Seveso III, shown also in These results are also coherent with the aim of an OSH management system as defined by the ISO 45001:2018 standard. Moreover, these results make it possible to draw up a coherent correspondence between the structures of the ISO 45001:2018 standard  and the As regards TS 4, given that it may be considered to be a specific transitional space resulting from the intersection of three general transitional spaces, it is key to defining and channelling the transitions between systems by means of the corresponding individual directives in each case, including at least Directive 98/24/EC on chemical agents . This coThe risk assessment techniques are a key structuring element between the functional and regulatory transition spaces, as shown in the results of These links and transitional spaces may facilitate system integration. In this regard, Li and Guldenmund  point ouIn the process of integrating systems, besides the existence of transitional spaces, non-traditional spaces also exist as a result of the specific aspects of each system that have no direct correlation with the other systems. These non-transitional spaces have not been studied here, yet may be equally important in any integration process, since they define the frontiers necessary to avoid unwanted interference with the transitional spaces.The main objective of this study has been met through identifying and analysing the links and transitional spaces between the risk management of occupational accidents and major accidents that involve hazardous substances in manufacturing processes. To this end, the risk management systems derived from Directive Seveso III, the Framework Directive and the ISO 45001:2018 standard  have beeThe first result of this analysis, the main link identified between the risk management of both types of accidents, is the presence in a manufacturing process of any of the hazardous substances included in Annex I of Directive Seveso III, for which the directives derived from the Framework Directive are also applicable, and the principles and guidelines of the ISO 45001:2018 standard are applicable on a voluntary basis .As a second result, the intersection of Directive Seveso III, the Framework Directive and the ISO 45001:2018 standard, configures three general transitional spaces . In turn, and as a third result, the intersection of these three general transitional spaces configures a specific transitional space (TS 4), which is key to defining and channelling the transition between systems by means of the individual directives that may correspond in each case, which will, at least, include the directive on chemical substances. This will enable integration processes between the systems considered.The above results are limited from a regulatory and technical perspective. In regard to the regulatory perspective, the context is limited to the EU, as well as Directive Seveso III, the Framework Directive and any individual directives that further develop it. Other directives and regulations that are especially relevant in the sphere of safety, as for instance the REACH Regulation  and CLP The results and limitations stated above may point towards future paths of research, from which models to integrate the risk management of occupational accidents and major accidents may be developed based on real experiences and data.By way of final conclusion, the identification and analysis of the links and transitional spaces carried out by this study aspire to being a starting point that will inspire other researchers to continue and further develop this study with the end goal of efficiently integrating risk management systems related to accidents derived from dangerous substances in manufacturing processes.


With the advancement of cloud computing and fog computing, more and more services and data are being moved from local servers to the fog and cloud for processing and storage. Videos are an important part of this movement. However, security issues involved in video moving have drawn wide attention. Although many video-encryption algorithms have been developed to protect local videos, these algorithms fail to solve the new problems faced on the media cloud, such as how to provide a video encryption service to devices with low computing power, how to meet the different encryption requirements for different type of videos, and how to ensure massive video encryption efficiency. To solve these three problems, we propose a cloud-fog-local video encryption framework which consists of a three-layer service model and corresponding key management strategies, a fine-grain video encryption algorithm based on the network abstract layer unit (NALU), and a massive video encryption framework based on Spark. The experiment proves that our proposed solution can meet the different encryption requirements for public videos and private videos. Moreover, in the experiment environment, our encryption algorithm for public videos reaches a speed of 1708 Mbps, and can provide a real-time encryption service for at least 42 channels of 4K-resolution videos. The sensor cloud system, having gained momentum in the recent years, is identified as an inevitable choice for many problems in the big data age. Multimedia  are major parts of big data, and building a media cloud based on sensors has become a major strategy of the media industry. In a sensor cloud, a large number of sensors are deployed to collect video and audio to the cloud, and finally build a huge multimedia transceiver system. Utilization of the media cloud can alleviate the workload of video service providers and give video users convenient and real-time access to video services.However, as data are not stored or processed locally, data security emerges as an inevitable concern in deployment and operations of cloud computing platforms . CompareFirst, how to provide uniform video encryption service for devices with different computing power. Devices connected to the media cloud, such as set-top boxes (STBs), computers, and mobile devices, are diverse and differ in computing power. It is difficult to deploy encryption algorithms that require intensive computing on devices with low computing power. Eiza et al.  and Pei Second, how to meet the different encryption requirements for different type of videos. Generally, there are two types of videos on the media cloud: public videos and private videos. Pubic videos, such as TV programs, user-generated content (UGC) and short videos, aim to attract audience and make profit. This type of video requires encryption but not to the degree of complete unrecognizable. Private videos like surveillance videos, personal videos and conference videos, are highly private, so the content of this type of video should be hidden as much as possible and real-timeliness should be ensured. Whether public video or private video, the implementation of fine-grained encryption for a single video is the basis to meet their different security requirements. Traditional video encryption algorithms in ,8, howevThird, how to ensure massive video encryption efficiency. As more 4K- and 8K-resolution videos are produced, the size of videos grow. Assuming that the compression ratio of H.265 videos is between 300:1 and 1000:1 , we can In this paper, we propose a cloud-fog-local video encryption service framework to provide a uniform video encryption service for devices with different computing power. In this framework, the key management is deployed on the cloud layer to produce, store, distribute and destroy keys. The video encryption is deployed on the fog layer and provides encryption service to the nearby terminals of varied computing power. Compared with cloud computing, fog computing is closer to the local users and can provide computing resources of low latency and high elasticity . In ordeFirst, we proposed a three-layer  video encryption framework and designed a corresponding three-layer key management scheme. The framework can provide a uniform video encryption service for devices with different computing power.Second, this paper is the first that designs a uniform video encryption algorithm to meet the different encryption requirements for public and private videos, and makes in-depth analysis of the encryption effect. The experiment proves that the algorithm we designed can meet encryption requirements of different types of videos.Third, we deployed the video encryption algorithm on Spark, and increased the encryption efficiency and scalability. The experiment proves that the cluster deployed on the two servers under the experiment conditions can realize real-time encryption of at least 42 channels of 4K-resolution videos.The major contribution of this paper is as follows.Noted that the focus of our paper is on the mechanism of video encryption, so authentication and authorization are not described in detail. However, when designing the key management scheme, we preset a session key as an interface to connect with secure authentication and authorization strategies .The rest of this paper is arranged as follows. Video encryption has long been a focus of the video encoding and information security industries. When the video is large in size, complex in structure and requires real-time transmission, encryption becomes challenging. According to the encrypted content, video encryption can be categorized into full encryption and selective encryption.Compared with full encryption, selective encryption has fewer encrypted data and higher encryption efficiency. By the timing of encryption, selective encryption can be categorized into encryption-before-encoding, encryption-after-encoding, and joint encryption-encoding  3]..3].In the encryption-before-encoding scheme, people first find the regions of interest and then realize accurate encryption which ensure security of the video and realize format compliance ,12. HoweIn the joint encryption-encoding scheme, there are basically two types. The first type encrypts the original compressed information, such as the intra-frame prediction model, the discrete cosine transform (DCT) coefficients, and motion vectors, as described in ,14,15,16In the encryption-after-encoding scheme, the advantages are that it can minimize the influence of the video encoding algorithms on encryption and ensure zero compression loss ,22,23,24Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users ,28. AbbaIn prior studies, we have proposed a “cloud-edge-local” media cloud service hierarchy . Based oThe tasks of each layer in the cloud-fog-local framework are as follows. The cloud layer, as the control center of the whole system, has two tasks. The first is to send video processing commands  to the fog layer, and recollect the index files similar to m3u8. The other is to verify legitimacy of the devices on the local layer, and complete authentication operations. The fog layer first allocates computing resources for proximate devices, and then encrypts/decrypts the videos. The local layer simulates different user terminals. In the encryption process, it sends video encryption requests to the cloud layer and uploads the videos onto the fog layer. In the decryption process, it sends decryption requests to the cloud layer and receives the decrypted videos from the fog layer. Encryption of large-scale videos will inevitable produce a large number of secret keys. In order to ensure secure distribution, storage and updating of secret keys, a specific key management scheme is needed ,32. We iThe first-level keys are content keys (CKs). The payloads in different groups  are matched with different content keys. The second-level keys are service keys (SKs) that are used to encrypt different parts in the index files. For instance, two services are provided now: Service 1 allows the ordinary users to decrypt only the first six minutes of a video, and Service 2 is provided to VIP users to decrypt the whole video. The index information of the first six minutes of a video will be encrypted by SK1, and the rest index content is encrypted by SK2. When decrypting, ordinary users can only acquire SK1, but VIP users can obtain secret keys for both Service 1 and Service 2 (SK1 and SK2). The third-level keys are session keys that are normally created by security authentication protocols and used to encrypt service keys.Both H.264/AVC and H.265/HEVC use a double-layered structure that consists of a video coding layer (VCL) and a network abstract layer (NAL). The compressed video data on VCL is encapsulated into NALUs (NAL units). NALU consists of two parts: the NALU header and the NALU payload.The NALU header has a fixed length (one byte for H.264 and two bytes for H.265) and records the content features of NALUs and network information. Thus, to preserve information of NALU headers can guarantee fault tolerance of the video information when transmitted online.rbsp_trailing_bits in the format of 100… is added. To avoid emulation between the byte streams in NALU payload and the NALU start code and end code, the RBSP must be byte-aligned and prevent emulation  is full-byte-length information that records video compression data on VCL. In H.264 and H.265, a RBSP is a sequence of bytes (8 bits) filled by a binary string of data bits (SODB) produced by the video encoder. When the last byte of RBSP is filled by SODB, then the mulation .nal-unit-type), we can analyze the content of different types of RBSP to reduce the content for encryption and increase encryption efficiency. The definition of NALU types differs between H.264 and H.265. In H.264, the video parameters are encapsulated NAL packets termed sequence parameter sets (SPS) and picture parameter sets (PPS); but in H.265, aside from SPS and PPS, the video parameter set (VPS) is introduced to store the global information of the video. The content in RBSP is what we want to encrypt. As the RBSP are divided into different types in the NALU header .For private videos, especially the user’s personal videos, the possibility of video content leakage should be minimized and high encryption efficiency should be ensured. For these videos, NALUs that contain the video’s global information should be selected to encrypt so that the fields to be encrypted can be minimized and no unauthorized decoder can decode the videos. Therefore, for private videos encoded by H.264, the SPS and PPS  are selected for encryption; for private videos encoded by H.265, the VPS, SPS and PPS  are selected for encryption, as shown in The last step is the emulation prevention. In order to prevent emulation of encrypted fields with NALU start codes and end codes, the sequence 0 × 000,000 needs to be processed . The AESIn this section, Apache Spark is used to execute encryption of massive video. First, massive video NALUs are taken as Spark datasets and form an independent resilient distributed dataset (RDD) for encryption. The video segments are suitable for the high-through-put and fault-tolerant stream processing system of Spark. Second, selective encryption is a complex operation with high computing load, and memory-based processing can increase the encryption efficiency. Last, the Spark framework is scalable and can distribute workload of each node intelligently, hence suitable for the allocate-on-demand encryption service.Deploy the Hadoop distributed file system (HDFS) for storing to-be-encrypted videos and encrypted videos;Compile the proposed encryption algorithm as “encryption.so” and deploy it on node servers;Spark executor instances developed by Java call the “encryption.so” from the executor of worker through the JNI interface to execute encryption.Steps to deploy the video selective encryption algorithm onto the Spark framework are as follows:Massive videos are upload and segmented, then the generated, to-be-encrypted segments are stored in HDFS;The Master node receives the tasks and obtains to-be-encrypted video segments from HDFS;The Worker node executes the tasks and encrypt the video segments;The encrypted segments are stored in HDFS, and the encryption is completed.The process of massive video encryption based on Spark are as follows :MassiveTwo servers are used to build the Spark experiment environment, and the gigabit router is used to realize communication between servers. In each server, there are 3 worker nodes, and each node contains 3 CPU cores and 4G of memory.mapToPair function is used to convert RDDs into JavaPairRDDs, and the encryption algorithm is called during the conversion process to encrypt all RDDs. The parameter type of JavaPairRDD is <LongWritable, BytesWritable>, in which the key of the type LongWritable is assigned the video segment ID, the value of the type BytesWritable is assigned the video segment; the Master constructs the logic graph of the elastic distributed dataset, that is, the directed acyclic graph (DAG), and transmits the DAG to DAGScheduler. The number of partitions in RDD determines the number of tasks, and the Master uses TaskScheduler, the shared memory agent node scheduling algorithm, to distribute each element in the distributed dataset to each Worker for processing according to the node performance and use conditions. Encryption of video segments are executed on the Executor on the Worker nodes.The realization of the Spark-based massive video selective encryption framework is as follows. The video segments processed by Spark are from HDFS; Spark is in the standalone mode, consisting of Master and Worker. Spark converts the HDFS video segments into resilient distributed datasets (RDDs) required for distributed processing; the The standard test sequences are used in the experiment, as shown in The YUV-format files are encoded into H.264 or H.265 videos by FFMPG , and theTo ensure credibility of the experiment, we tested the performance of encrypted videos with different code rates and different resolution ratios. Different code rates can be considered as heterogenous network environments with different communication capabilities, and different resolution ratios can simulate terminal devices with different resolution ratios.A satisfying video encryption algorithm should not only meet requirements for different security levels, but also minimize encryption/decryption-caused computing consumption and reduce encryption-induced loss of compression. Thus, the performance of the proposed fine-grained video encryption framework is discussed with regard to three aspects: security, encryption efficiency and compression loss. Then, we discuss how to realize fine-grained access control of video in our proposed scheme.In , Tang prPrivate videos will lose the global information after being encrypted and cannot be played, so it is meaningless to discuss the encryption quality. For public videos, the best effect of encryption is: when an unauthorized user watches an encrypted video, the user can acquire the contour information of the pictures, but have no see to the detailed information. The peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM) are two major indicators of video encryption quality . PSNR isVideos of different resolution ratios are encoded into H.264 and H.265 formats by FFMEPG, and then encrypted by the encryption algorithm we proposed. Tests on a video under different code rates can simulate the encryption effect of video code streams in different network environments, and tests on a video of different resolutions and a fixed code rate (5000 kbps) can simulate the encryption effect of video streams on devices with different resolution ratios.Typical PSNR values for good quality pictures range between 30 and 40 dB . Figure SSIM is a metric to assess similarity of two images and has been widely used in video quality assessment. In , Yeung eAs the experiment result shows, videos encrypted by our encryption algorithm according to the security standard for public videos have small average values of PSNR (16.43 dB for H.264 videos and 10.57 dB for H.265 videos) and high average values of SSIM (0.61 for H.264 videos and 0.32 for H.265 videos). 128, which is large enough.To resist brute-force attacks, video encryption should have large key space and ciphertext space. Our proposed massive video selective encryption algorithm uses AES to encrypt video segments, the key length is 128 bits, and the key space reaches 2There are two encryption levels: one is the private-video encryption level and the other is public-video encryption level. As the requirements for encryption efficiency differ among videos, two encryption levels have different ciphertext space.Private-video encryption level. Sequence parameter sets and picture parameters sets (video parameter sets are included in H.265 videos) are encrypted in the private video encryption scheme. Parameters with a GOP size of 8 are chosen for encoding. The frame per second (fps) is set as 24. If HLS segments a video into segments of 10 s [ of 10 s , the fraPublic-video encryption level. The encryption space ratio (ESR) is calculated as the ratio of the encrypted bits to all the bits of a compressed video bitstream. In summary, our proposed algorithm has large key space and ciphertext space, so it can defend against brute-force attacks and replacement attacks.In differential attack, the attackers try to guess the keys by investigation of the encrypted bitstream streams. Video encryption algorithm should be sensitive to keys. A slight change of decryption key will make the ciphertext completely unable to decrypt. In our proposed encryption scheme, when the decryption key K2 is only 1 bit different from the encryption K1, the video cannot be decrypted correctly. In this type of attacks, the attackers use the known plaintext and the corresponding ciphertext to obtain the key or the whole plaintext. However, our proposed algorithm has enough ciphertext space. For example, the test sequence “BasketballDrive” contains 501 frames. The compressed video encoded by H.264 according to Selectively encrypted video is vulnerable to interference attack . AttackeMassive video encryption is provided to video manufacturers and individuals that are sensitive to encryption efficiency, and scenarios like video conferences and live sports have high standard for real-time transmission. Moreover, as the cloud computing service is very flexible, the encryption service should have high flexibility and scalability .We use the Spark streaming processing system to extend the selective video encryption algorithm. In the experiment, we segment the 100G video with 120 s as the fixed unit, and execute the encryption algorithm for ten times. For massive videos, loss of compression will cause large consumption of the storage space and transmission bandwidth. The massive video selective encryption algorithm we propose executes encryption after video encoding, which can in theory reduce the loss of compression to 0. By comparing the size of videos before and after encryption , we consMassive video fine-grained access control allows operators to develop more flexible services, but increases the workload for key management. The service framework we propose uses a layered key management scheme. In this scheme, the video encryption layer takes the NALU as the basic encryption unit, each NALU is matched with one content key, and it realizes NALU-level fine-grained encryption and stores video information and corresponding content keys into the video index. In the service layer, the different parts in the encrypted video’s index file are encrypted by the service keys which are generated according to different services. In the authentication & authorization layer, the session keys are built between users and the server, and then used to transport service keys to the corresponding users. In this way, fine-grained access to a particular part of one video is realized. Because massive amounts of content keys are stored in the index, the key management module only needs to manage a few service keys.Video content contains more information than textual content, but faces more problems with regard to copyright and privacy leakage, so it is important to ensure security when the videos are transmitted to the cloud server. Terminal devices, due to limited computing capability, are not suitable for large-scale encryption, and the services have different requirements for real-timeliness and encryption security. To solve these problems, we propose a fine-grained video encryption service that consists of the cloud-fog-local framework, a fine-grained video encryption algorithm based on NALU and a massive video encryption framework based on Spark. Compared with other cloud computing services, our proposed service deploys video encryption on the fog layer that is closer to the local servers, and the cloud layer is only responsible for key management and authority control, so the framework reduces latency of video services. The experiment and analysis verify that our proposed video encryption algorithm can meet the security requirements for both public videos and private videos, and incurs no loss of compression. The encryption speed of encrypting public videos by using the Spark cluster in the experiment environment reaches 1708 Mbps, so it can meet real-time encryption for at least 42 channels of 4K-resolution videos.In future, our main work will include the following two aspects. First, for the private-video encryption level, we have paid more attention to the efficiency than the security. However, it is necessary to further explore its security capability. Based on the security analysis, we will improve the private video encryption schemes. Second, although the layered key management mechanism can greatly save the workload of the key management center, there is also a new problem, namely that the video encryption key CK cannot be directly updated and revoked. Part of our future work will be focused on how to realize the periodic, automatic and efficient update of CKs.


Refer to the research article “Predicting CO2 Residual Trapping Ability Based on Experimental Petrophysical Properties for Different Sandstone Types” [1] for data interpretation. The reader can expect to find experimental conditions including temperature, pressure, fluid pair types, as well as flow rates. Furthermore, the raw CT images and the processed three-dimensional (3D) voxel-level porosity, permeability, and CO2 saturation maps for each of the nine sandstone samples are also supplied.This data article provides detailed explanation and data on CO The two CO2 saturation maps contain a post-drainage initial CO2 saturation map and a post-imbibition residual CO2 saturation map. Using these two CO2 saturation maps, residual trapping relationships can be calculated for all core samples provided. All of the 3D maps are illustrated in There are two parts to the data. The first part of the data includes 22/water coreflooding experiments at reservoir conditions have been conducted on nine sandstone rock samples. The samples come from the Berea, Massillon, Bentheimer, Fontainebleau, and the Shezaf sandstone formations. The nine core samples also have a wide range of heterogeneity and internal features. The experiments contain both drainage and imbibition stages. The CT scans with the highest post-drainage CO2 saturation are selected as the initial scans and the corresponding CT scans after 100% water imbibition are selected as the residual scans to be presented with this article. Both the CO2 saturation maps and the porosity maps are directly obtainable through manipulating CT images, whereas the permeability maps are calculated through an extensive iterative procedure involving reservoir simulation Steady-state CO2/water interfacial tension σ = 35 mN/m and water viscosity μ = 5.4843 × 10−4 Pa s at 50 °C 2 saturation maps and the fourth row shows the residual CO2 saturation maps. All CO2 saturation data provided is steady-state result and the processed data has been averaged over three independent CT scans. For exact voxel sizes, refer to Ni et al.


Arteriovenous malformations (AVMs) are defined as tortuous connections between arteries and veins that bypass the capillary system. Cerebral AVMs are rare with a general prevalence of 0.5%-1% with approximately one-fifth of these being diagnosed in infancy or childhood. Although most AVMs go undetected, the most common presenting symptom is hemorrhage. Despite a broad differential diagnosis for syncope described in the pediatric literature, there has been no report of AVM as the underlying etiology. We present a case of a seven-year-old female who presented with a single syncopal episode and was later found to have a large AVM involving mainly the thalamus on the right side and the basal ganglia with large intraventricular draining veins into the galenic venous system. To our knowledge, this is the only case reported of an AVM presenting as syncope in a pediatric patient. Arteriovenous malformations (AVMs) are defined as tortuous connections between arteries and veins that bypass the capillary system resulting in hypertrophy of the arterial and venous components . AVMs arSyncope in children has a reported incidence of 0.1%-0.5% -10. The There have been cases described in the literature of adult patients with AVM who have presented with syncope -12. To oA seven-year-old female with no significant past medical history initially presented with a syncopal episode while at a birthday party, with loss of consciousness for 2-3 seconds and mild upper body stiffness without a postictal state. The patient reportedly was on the swing at a local park when she experienced her syncopal episode. As per her mother, who watched the entire episode, she did not fall off the swing and immediately returned to normal activity. The patient had no prior history of syncope, headaches, seizures, vomiting, diplopia, or blurry vision, and no family history of seizure disorder, cardiac abnormality, CNS disorder, or AVM. Upon follow up with her pediatrician the next day, the patient was alert, happy, and in no apparent distress. A comprehensive physical exam performed including extensive neurological examination was unremarkable.Despite this, the pediatrician chose to order a head CT to rule out intracranial pathology, as well as a CBC with differential, CMP, thyroid profile, 2D echo with doppler of the heart, and 12-lead electrocardiogram. All her laboratory results were within normal limits. Head CT revealed marked abnormality to the thalamus, lateral ventricle, and the periventricular area on the right side extending into the foramen of Monroe and causing hydrocephalus. Based upon this, a differential diagnosis including brain tumor, AVM, and neurofibromatosis was developed.At this point, the pediatrician ordered an MRA that showed an AVM. The patient was subsequently sent for an MRI of the brain with gadolinium which revealed hydrocephalus and a large AVM involving mainly the thalamus on the right side and the basal ganglia with large intraventricular draining veins into the galenic venous system Figure . The sizThree subsequent neurosurgical evaluations demonstrated an unremarkable neurological examination with no asymmetries on cranial nerve examination, strength, muscle tone, or reflexes. Her sensory and cerebellar examinations were within normal limits as well, and the neurologist concluded that the AVM was not associated with any neurological deficits and no symptoms referable to the ventricular obstruction. An EEG obtained showed no abnormalities. An ophthalmology consult demonstrated a normal ophthalmological examination with no evidence of AVM in the retina. Due to the AVM size and structural involvement, surgery was ruled out as a possible course of treatment. All neurosurgical consults concluded that the patient should receive routine imaging every six months to ensure no change in size and bleeding status. A repeat MR angiogram Figure  and MRI Arteriovenous malformations are considered embryological in origin and as the result of arteriovenous shunting due to a tortuous direct connection between arteries and veins that results in hypertrophy of the arterial and venous components of the AVM . AlthougSyncope is defined as a transient loss of consciousness and postural tone due to cerebral hypoperfusion . The incThere have been reports of adults with AVMs presenting with recurrent syncopal episodes. De Biase et al. reported a case of recurrent episodes of syncope in a 66-year-old patient with cerebral AVM suggestive of an epileptogenic mechanism . CarboniThis case illustrates that abnormal physical examination and laboratory findings should not be required to justify imaging studies to exclude intracranial pathology, particularly when there is no identifiable etiology of syncope. Additionally, our case suggests that AVM should be included in the differential diagnosis of syncope in a pediatric patient.


Three standardized clinical scenarios that were recorded on video were executed. A checklist was applied for the evaluation, administered by a reviewer blinded to the assignment of the type of debriefing. The two debriefing strategies increased the technical and behavioral neonatal resuscitation skills of the participants, without one being superior to the other. The coefficient of the difference in the compliance percentage between the two types of debriefing was − 3.6% (95% CI − 13.77% to 6.47%). When comparing the development of technical and behavioral skills among the professionals evaluated, no significant differences were found between the types of debriefing. The two debriefing strategies increase compliance percentages, reaching or approaching 100%.A simple blind randomized clinical trial was conducted. Twenty-four professionals  were randomly assigned for two interventions; one group received oral Trial Registration ClinicalTrials.gov NCT03606278. July 30, 2018. Retrospectively registeredThe online version of this article (10.1186/s13104-018-3831-6) contains supplementary material, which is available to authorized users. Debriefing is an essential component of the teaching process based on simulation [Neonatal resuscitation is an event of high complexity and stress for the teams responsible for critical neonatal care . Performmulation –9. The dmulation , 10. Themulation . The litdebriefing strategies, a structured instructor-guided oral debriefing compared with a structured instructor-guided oral debriefing assisted by video, in the development of neonatal resuscitation skills in health professionals responsible for the care of the newborn in a high-complexity university Hospital.The present study aims to evaluate two A simple blind randomized clinical trial was conducted. Staff for the care of critical newborn of the Clinica Universidad de La Sabana were invited to participate. Professional nurses, respiratory therapists, and pediatricians were included. The Medical Ethics Committee of the Clinic approved the protocol. The participants signed an informed consent statement.debriefings in the group with video and for the evaluation of subsequent performance with a checklist, was performed by an evaluator blinded to the assignment of the debriefing type. Each scenario was followed immediately by an instructor-guided debriefing session , stratified by the type of health professional. For this randomization, the random function of Excel was used, sorting the participants in a random number order and assigning the first half to the oral group and the other half to the video-assisted group. For the conformation of the teams, a second randomization was performed, in which the professionals within an assigned group  were randomized to form a resuscitation team. In this randomization, Excel’s random function was also used, sorting the participants in a random number order and assigning the one that was ordered first to team 1, the second to team 2, and so on, until completing four teams per intervention, each with three professions: pediatrician, professional nurse, and respiratory therapist. The same team was maintained during the participation of each scenario . Finally, a sample size of 24 participants was used (12 for each intervention), which allowed organizing resuscitation teams of three participants each, for a total of four teams per debriefing type.A sample size was calculated using the information published in the study by Luna et al. . The nordebriefing methods, a generalized estimating equations model was constructed, which is used to develop regression models in correlated data that come from repeated measurements of the same individual over time, as was the case. The dependent variable was the compliance percentage, and the independent variables were the type of debriefing, the scenario, the profession, and the group. The analyses were performed using the Stata® 10 program.Descriptive analyses were performed. Box-and-whisker plots were constructed for the compliance percentage, for each profession and in each of the scenarios evaluated. To compare the debriefing strategies. The coefficient of the difference in the compliance percentage between the two types of debriefing was − 3.6% (95% CI − 13.77% to 6.47%). When comparing the development of technical and behavioral skills, no significant differences were found between the types of debriefing, with − 6.34% (95% CI − 19.93% to 7.25%) and − 0.19% (95% CI − 10.85% to 10.46%), respectively.Table debriefing was determined after each scenario, and it was found that the participants of the oral group increased their score by 26.29% (95% CI 20.44% to 32.14%) after each debriefing episode, while those of the video group increased by 33.55% (95% CI 27.9% to 39.2%). When performing this same analysis by profession, it was found that the two debriefing strategies increased their compliance percentages and that the therapists increased their scores by the greatest percentages after each scenario (Table The participants of the video-assisted group started at a lower point regardless of profession Fig. . Given tdebriefing on the performance of pediatric postgraduate students during a neonatal resuscitation, without showing differences between the two educational strategies [The two strategies improved the overall skills and differentiated as cognitive, technical, and behavioral in the different professions, without significant statistical differences between the two. These findings are consistent with what has been found by other authors. Sawyer et al. and Cheng et al. compared the effectiveness of video-assisted vs. oral rategies , 14. Fanrategies .debriefing: the type and quality of the video recording; the selection of the video segment that permits highlighting the learning objectives; the amount of video time reviewed; the time, the space, and the duration of the debriefing; and the expertise and knowledge of the instructor who performs the debriefing [Several factors can influence the development of competencies in briefing , 13. In briefing . In the The respiratory therapists had higher coefficients of improvement throughout the scenarios in both groups. It was considered that these improvements could be because they were also the group of professionals who started with lower pre-test scores. It can be stated that despite having different profiles, professions, and levels of knowledge, all achieved optimal performance thanks to their overall participation in the course.debriefing have included a population of undergraduate medical or nursing students [It was not possible to compare this result with similar results since no other study has permitted the comparison of roles between different professions. In this study, the neonatal resuscitation teams were formed with the professionals exercising the role they play in the care of the newborn in the real clinical context. Other studies that have sought to evaluate the effects of simulation and students , 14, of students , 16. In Debriefing shows a potential benefit for increasing the skills in neonatal resuscitation. In this study, neonatal resuscitation teams were formed that were similar to those in the real clinical context and with clinical staff having experience and expertise in advanced neonatal resuscitation. In this context, the results showed that when debriefing is performed immediately and assisted by a facilitator, the strategy structured by video is not superior to the oral structured strategy in the development of skills in neonatal resuscitation, including technical/cognitive and behavioral skills.There could be some variability in the way debriefing is performed, there were two instructors for the execution of the debriefing after each of the scenarios. However, both facilitators were instructors for the neonatal resuscitation program with expertise in debriefing.We do not have a control group that has not received debriefing. This is because it has already been widely corroborated in other studies the clear improvement in performance obtained by the participants when receiving the debriefing.Additional file 1: Figure S1. Flowchart of the study design. Source: Prepared by the authors.Additional file 2: Appendix S1. Checklist: neonatal resuscitation performance evaluation tool.


Marker-less video-based pose estimation promises to allow us to do movement science on existing video databases. We revisited the old question of how people synchronize their walking using real world data. We thus applied pose estimation to 348 video segments extracted from YouTube videos of people walking in cities. As in previous, more constrained, research, we find a tendency for pairs of people to walk in phase or in anti-phase with each other. Large video databases, along with pose-estimation algorithms, promise answers to many movement questions without experimentally acquiring new data. To successfully navigate any environment, a walker must adapt to the surface they walk on, avoid obstacles, change speed, and plan movements according to their goals ,2. ProceCoordination of movements with others during everyday activities helps to achieve shared goals efficiently and fluently, for example when playing sports, moving an object together, or walking side-by-side. In many cases, synchronization is needed to successfully carry out the task at hand. However, evidence from laboratory experiments suggests that synchronization between people does not only take place when it is required by the task. There is evidence for uninstructed movement coordination from laboratory experiments where subjects are asked to perform various artificial tasks, for example, sway pendulums, sit in rocking chairs, or spontaneously move their arms –11. CoorPrevious laboratory-based studies have investigated if people walking side-by-side synchronize their movements. Walker synchronization is common when people walk side-by-side, and has been found in over-ground walking studies ,12–14 anHowever, as with many movement science paradigms, it is not known if walker synchronization occurs in real world settings, outside of the laboratory. This is especially relevant for the walking studies in the laboratory: researchers have found a substantial difference in biomechanics between walking on the treadmill and walking on level ground ,22. The There have been previous examinations of walker synchronization during over ground walking in laboratory settings. Most laboratory studies used motion capture systems applied to the limbs to quantify walking parameters. Research relied on reviewer ratings to address walking over ground in one study . In a seHere we apply pose estimation to online videos to ask how people synchronize their movements when they walk side-by-side. We used a state-of-the-art pose-estimation algorithm, OpenPose, to extract human body pose from 2D videos . OpenPosWe wanted to obtain videos of people walking in a naturalistic setting. To find this data, we searched for videos on youtube.com using the search term “walking in” followed by the names of major cities: Bangkok, London, Paris, Dubai, New York, Singapore, Kuala Lumpur, Istanbul, Tokyo, Seoul, Hong Kong, Barcelona, Amsterdam, Milan, Taipei, Rome, Osaka, Vienna, Shanghai, and Prague. Videos were ranked by relevance by YouTube. We examined the most relevant videos for each search term that were over 20 minutes long. In our analysis, we included videos that contained pairs of people walking with low camera movement and where limbs of people in the video were uncropped. We selected videos that met these criteria from the 20 most relevant results on YouTube. Our methodology complies with the terms of service and use of YouTube. This study was approved by the University of Pennsylvania Institutional Review Board (protocol 827723).https://figshare.com/articles/PONE-D-18-34216_Walker_synchronization/7722278. The data in the linked repository constitutes our minimal data set, which along with the information given in this manuscript is sufficient to replicate our analysis.The URLs from the 348 video segments included in the final analysis are included as Supporting information . The filWe provide examples of OpenPose outputs overlaid on video frames in We needed a method to quantify the synchronization of walker pairs from 2D videos. We therefore began by extracting human pose from video frames, using OpenPose, a pose-estimation algorithm that detects body part positions from 2D RGB images . OpenPosWe first needed to identify video segments of people walking side-by-side from the downloaded YouTube videos. We therefore built an algorithm to search through YouTube videos and extract the particular segments containing pairs of people walking . First, From each frame of the subsampled YouTube video, we extracted human pose, resulting in a set of x, y coordinates indicating body part position and a person index. We included skeletons that contained at least 14 out of the total 18 parts. As movement synchronization is typically quantified by relative phase between two oscillatory motions, we created a measure of walking phase by using the ankle position. Therefore, we required that both ankles be detected for a given skeleton. This resulted in a set of pose estimates for each video frame with people present.Using pose estimates from each frame, we then detected pairs of walkers on a frame-by-frame basis. We built a bounding box around each skeleton pair found in the image. To ensure that walkers were side-by-side, we selected pairs where the aspect ratio (height:width) of the bounding box was between 1:1 and 3:1, and where ankles of the pair were within 15% of the bounding box from each other in y-coordinates. To avoid data with low spatial resolution, we selected pairs where the height of the bounding box was over 120 pixels. To ensure that we analyzed pairs of adult walkers and not adult-child pairs, we only included pairs where the ratio between the larger and smaller skeleton was less than 1.25:1. This resulted in a set of detected person pairs from each video frame.To produce video segments of pairs of walkers, we identified sequences of video frames that contained at least one pair of walkers for the whole duration of the segment, with a minimum segment lasting 2 seconds. We excluded pairs where two or more walker pair detections contained a common element (person) for 3 consecutive subsampled frames or more (1.5 seconds), which would suggest a group of walkers. We then extracted video segments of pair of walkers from the original YouTube video sampled at the original frame rate. We manually selected videos that contained non-occluded pairs of adults walking continuously toward or away from the camera on flat surfaces in well-lit conditions, where people were not carrying large objects or using an assistive device. In order to increase the quality of our data, we modified the duration of segments, either removing segments without walking pairs or increasing the duration of the segment until the point in the video where the walking pair was no longer visible. This resulted in video segments containing pairs of people walking together.i is a keypoint index, j is a frame, n is the number of keypoints that are present in both frames, x is the x-coordinate of a key point and y is the y-coordinate of the key point. To track a given person, we iterated through the frames of the video and minimized the distance for each frame pair. Common problems were switches in person identity across frames and failure to accurately track the ankle. We therefore manually selected videos for inclusion in our analysis where the algorithm successfully tracked people through frames of the video.From each video segment, we needed to extract pose and track individuals through the video, in order to obtain cyclic walking signals for each person. We extracted pose estimates for all frames. Using the pose estimates, we tracked pairs of walkers through the frames of the video. We tracked pairs of walkers by first running the previous walker pair detection step on the first frame of the segment. We then minimized the distance between skeletons in the video from one frame to the next averaged across the key points present in both frames, To quantify walker synchronization from pose estimates, we analyzed the vertical displacement between the ankle joints, using this as a way of quantifying the relative walking phase. Our analysis was adapted to measuring walking phase from people walking toward or away from the camera. We chose to analyze the video data in this way firstly because inspection of the video data revealed that walkers more often moved toward or away from the camera rather than across the frame. Second, visual occlusion between walkers prevented us from accurately extracting the pose for both walkers when they walked side-by-side in profile, with one walker occluding the other in the video frame. Although the profile view provides greater variance in leg angle and in this sense is less prone to noise than metrics extracted from the frontal/dorsal view, occlusion would prevent us from finding and then analyzing videos with a profile perspective. Therefore, analyzing vertical ankle displacement extracted from the frontal/dorsal angle was a strategy which was adapted to most of the data available in our video data set and also allowed us to avoid problems related to occlusion.In order to extract walking phase from pose estimates, we processed the data as follows. We first replaced missing values using linear interpolation. We did not have control over video recordings and so, in most video segments, the distance between the camera and the walkers was not fixed. We therefore needed to detrend the ankle coordinates. To do so, within each frame, we computed the distance of the ankle relative to a reference body part and divided this distance by the height of the skeleton. We selected the neck as the reference part since this is typically the least occluded part. We combined this data across frames to form a time series of detrended ankle coordinates. We handled outliers by replacing points which were two standard deviations or more from the mean with linearly interpolated values. We then normalized the signal by subtracting its mean and dividing by its standard deviation. We low-pass filtered the ankle displacement signal using a third order Butterworth filter with a cutoff frequency of 2 Hz. This resulted in a signal from which we could extract the vertical ankle displacement and walking phase.π and +π. The relative phase between walkers was simply computed by subtracting the walking phase of one walker from the other. We also wrapped the phase difference so that it could not extend outside −π and +π. Thus, the relative phase was a continuous circular variable that wrapped at the +π. This resulted in a time series of relative phases for each pair of walkers. We analyzed the distribution of relative phase for each pair of walkers by computing the mean phase angle computed using a circular mean statistic.For each pair of walkers, we wanted to analyze the walking phase relationship using the positions of the ankles. Our analysis of walking phase is described in π would mean that walking in anti-phase is a dominant mode.In order to combine estimates of walker synchronization across different videos, we used circular statistics to compute mean of the relative phase distribution and the variance of the relative phase distribution from each video segment. Using the R package movMF, we then fitted a mixture of von Mises distributions to the distribution of mean relative phase extracted from all videos, and identified the peaks of the best fitting distribution for up to four components. The mixture of von Mises distributions is a circular approximation of a mixture of Gaussian distributions. The aim of this analysis was to quantify the location of the peaks of the relative phase distribution. Peak phase of 0 would mean that walking in phase is a dominant mode of walker synchronization, and peak phase of +We extracted the frequency of walking by examining displacement between left and right ankles in y coordinates. The displacement signal is positive when the left ankle is above the right and negative when the left ankle is below the right. This displacement signal is cyclic, and one cycle represents two steps. We extracted the frequency by computing the peak value of the discrete fast Fourier transform. We doubled this frequency in cycles/second to obtain the walking frequency conventionally defined as steps/second.In our video data, we had no control over how the video was recorded. For example, the camera was often in movement and camera angle was variable, both of which could have an influence on our measure of ankle position. We therefore wanted to ensure that pose estimation did not produce results on frequency and relative walking phase were unbiased.We verified that the mean relative phase extracted from pose estimates was consistent with the mean relative phase extracted from labels of foot strike timing labels provided by two human labelers. Our “ground-truth” data set consisted of 5-second-long segments from 43 randomly-selected videos from our final data set. We built a signal that accurately reflected the walking angle using human labels of foot strike timings. We then compared the relative phase computed from ‘ground-truth’ human labels with the relative phase computed from pose estimates. We performed the same analysis on a signal constructed from human labels that was applied to the ankle displacement signal computed from pose estimates. Agreement between the analyses applied to human labels and pose estimates will suggest that pose estimates allow unbiased estimation of relative walking phase.https://ant.umn.edu/) by manually labelling the timing of foot strikes for each walker . This resulted in a set of left and right foot strike events for the two walkers in each video clip. Note that the foot strike is one of the most salient kinematic event for locomotion, and its timing is easy to estimate [We required a signal that would approximate walking angle which we could construct from human labels. We therefore labelled videos with foot-strike timing events for the left and right feet of each walker. We annotated videos using a video annotation tool . After screening, we included a total of 199 videos, which gave us a reasonably sized dataset for quantifying synchronization.Within these videos, our algorithm identified 888 video segments with pairs of people walking lasting at least 2.5 seconds. Some segments were unsuitable because 1.) the segment did not contain pairs of adults walking continuously towards or away from the camera in well-lit conditions (258 segments), 2.) the segment included large amounts of camera movement, occlusion, or cropping of body parts from the video which prevented successful pose-tracking (197 segments). In the end, we extracted pose from the 433 suitable video segments containing 441 pairs of walkers, among which pose estimation or tracking failed for 93 walking pairs. Thus, our final sample for walking analyses include 348 video segments with a mean duration of 4.73 seconds ; walker frequency: R2 = .23 (N = 43)). Therefore, despite the variability of recording conditions, we were able to meaningfully extract information about walking patterns from pose estimates.We wanted to validate the outputs from pose estimates. We thus compared the walking frequency and mean relative phase computed from pose estimates with those extracted from a ground truth signal. We found reasonable agreement between the ground-truth estimates and pose estimates , phase locking occurs close to 0 and ±π. Therefore, our analysis of the relative phase variance indicates phase locking in near phase or near anti-phase in 35–70% of walking pairs in our sample.A second indicator of synchronization is a stable relative phase signal between walkers. Low variance between walkers indicates phase locking in walking patterns. Phase locking can occur at different mean phases. High variance indicates a lack of phase locking that is consistent throughout the segment, but here is difficult to separate from the effects of noise on pose estimates. We analyzed the distribution of the relative phase variance computed for each walking pair . First, π both in cases with and without hand contact  and without hand contact between walkers (N = 288). We observe synchronization indicated by peaks at 0 and ± contact . Therefoπ, which reflects a tendency for pairs of walkers to walk in phase or in anti-phase with each other. Using pose estimation applied to online videos, we confirmed findings from more constrained laboratory experiments on a larger sample and in more naturalistic conditions. We have thus shown that a pose estimation algorithm applied to 2D videos can be used to address questions about naturalistic movement.We asked how people synchronize their movements when they walk side-by-side, by analyzing pose estimates extracted from online videos. We searched for videos on youtube.com using the search term ’walking in’ followed by the names of major cities. We analyzed the relative phase and walking frequency computed from the vertical displacement between the ankles in each video. We validated our analysis from pose estimates through comparison with ground-truth data and found reasonable agreement between estimates of mean relative phase and walking frequency. The mean frequency of walkers was 1.85 Hz, close to the average of 2 Hz reported in the literature . We founπ radians, suggesting that in-phase and anti-phase walking occur for different walking pairs. In agreement with our findings, when pairs walked on treadmills, phase locking occurred close to 0 and ±π radians [The trend for walking in-phase or in anti-phase in our data is consistent with previous laboratory studies from treadmill studies ,18,20. W radians ,18,20. H radians . This doWhile findings from treadmill studies provide evidence for walker synchronization, they do not provide direct evidence for walker synchronization in naturalistic unconstrained situations. Treadmills are set at a fixed walking speed  and biomOur study builds on previous work on walker synchronization during over ground walking. In previous work on over-ground walking, human raters judged pairs as exhibiting synchronized walking on an ordered scale, providing qualitative evidence for in-phase and anti-phase synchronization. A second study quantified walker synchronization during over-ground walking using accelerometers applied to the trunk . SynchroWe developed a pipeline to study walking behavior from videos. Using this pipeline, we were able to extract sufficient information to carry out a group analysis across hundreds of video segments. Outside the scope of this work, various interesting questions arise on how synchronization occurs in the real world. One may ask how sensory feedback, biomechanics, and social factors influence walker synchronization. Addressing most of these questions in our data set would require a more detailed analysis of individual data, which is precluded by the level of noise in our data and the lack of longer video segments in our data set. Larger data sets and more precise pose estimation algorithms will make many of these investigations possible in future.Previous work has examined the necessary conditions for walker synchronization. Sensory feedback is needed for synchronization behavior to occur. In order to synchronize movement, pairs of walkers use auditory, visual, and tactile sensory feedback from their partner ,14,23. SIn the laboratory, biomechanical and environmental parameters modulate synchronization behavior, such as differences in leg length, walkway slope and over-ground speed between partners ,18. In fQuestions also arise on the interpersonal factors that influence synchronization. Synchronization between pairs who intentionally walk together is a specific case, where walkers share the goal of walking side by side. This presumably captures much of the data analyzed in this work. However, synchronization could occur across a group of walkers of more than two people, as there is evidence of synchronization in collective animal behavior ,33. SyncAlthough pose estimation is a promising tool for movement science and related applications, its application at present involves limitations. One challenge is the presence of different sources of variability in videos. Due to imperfect pose estimation, our measure of ankle joint position varied around the true position. To remove noise, more sophisticated forms of denoising than the standard signal processing techniques used here can be applied. For example, measuring the contribution of different noise sources would allow the application of deconvolutional techniques to separate the walking phase signal from noise. Another problem is that camera angle, which constantly changes in the videos that we used, influenced the ankle displacement variable. Signal cleaning that uses machine-learning based predictions from, for example, recurrent neural networks would allow the algorithm to learn the mapping of 2D-joint positions to walking phase . AlthougA second limitation is that most existing pose-estimation algorithms output two-dimensional pose estimates ,27. WithA third challenge is continuous tracking of person identity in videos. Pose estimation algorithms provide joint position coordinates for each frame but do not track person identity throughout a video. Simple tracking algorithms that minimize distance across frames often fail because large amounts of occlusion present in natural scenes. Improvements of optimization methods for tracking algorithms and integrating pose estimation with tracking on whole videos will allow more successful analysis of movement in natural and dynamic scenes ,37.Besides algorithmic solutions, we can devise practical solutions using specialized setups to meet the above challenges. For example, we could carefully place multiple cameras in naturalistic settings. Alternatively, we could place lab-grade sensors on people in the real world. While all these approaches are feasible and have been used in past research, having scalable approaches that can leverage large datasets is particularly promising.Many real-world applications are calling for automatic pose estimation based on videos. Improved pose tracking will allow the field to quantify movement variables from easily obtained data, thus paving the way for a host of video-based applications in fields including medicine and sport . MovemenMovement science stands to gain the most from adopting pose estimation from 2D videos as part of its standard toolkit. Movement science and the field of psychology more generally have been limited by small data set sizes and a set of overly constrained laboratory tasks that may invoke qualitatively different mechanisms to those at play during real world tasks ,40. ExamS1 FileCSV file containing: video # index, video URL, start of video segment in seconds, duration of video segment, name of corresponding file in database (pose estimates and video), video license information, and presence of hand contact.(CSV)Click here for additional data file.


Reports on the use of various smartphone-based video conference applications to guide point-of-care ultrasound (POCUS) examinations in resource-limited settings have been described. However, the use of an augmented reality-enabled smartphone video conference application in this same manner has not been described. Presented is a case in which such as application was used to remotely guide a point of care ultrasound examination. The ability to improve the quality of care to resource-limited settings is often a logistical challenge resulting from the lack of specialized medical practitioners and services. This is often secondary to geographic, demographic, and socioeconomic factors. The implementation of technology in healthcare is often a contributor to this problem rather than a solution. However, recent innovations in smartphone technology and point-of-care ultrasound (POCUS) devices have proven to be key examples of how technological advances are poised to elevate the quality of care in resource-limited settings. Indeed, the use of smartphone devices to provide real-time video conferences has proven to improve rural medicine across many medical specialties ,2,3,4,5.Point-of-care ultrasound refers to the use of ultrasonography at the patient’s bedside for diagnostic and therapeutic purposes . The proRecently, smartphone-based video conference technologies have been used with point-of-care ultrasound. Several studies have demonstrated the ability to remotely educate, guide, and provide image interpretation of POCUS examinations. While these studies have shown promise, a new modality, augmented reality (AR), has recently been implemented in the point-of-care ultrasound education space . The useThis report highlights the use of a novel smartphone application  to provide AR remote assistance to guide a POCUS examination. The application works on most smartphone devices and web browsers and provides an augmented reality video conference interface that allows each user to notate the other’s environment see . The easChalk-enabled smartphone  to the Hôpital Adventiste d’Haiti. During the visit, the onsite and visiting faculty identified a 35-year-old male patient scheduled to undergo an external fixator removal and replacement. The patient required a regional anesthesia popliteal nerve block. The ability to use ultrasound to perform this block was not routinely available, and local providers had not been trained to perform this procedure. To evaluate the capability of the AR application to provide remote guidance for this procedure a connection was established, via the Chalk application, between the visiting faculty’s smartphone in Port-au-Prince, Haiti to a remote faculty in CA, USA. Consent was obtained from the patient to report this case.Faculty from the tertiary care center traveled with a low-cost ($2000 USD) handheld portable ultrasound device  and a Chalk was used to send a call to the expert ultrasonographer , who then used the AR platform to guide probe placement on the patient to obtain the appropriate ultrasound image. Once the onsite examiner had obtained the appropriate probe position and ultrasound image, the smartphone camera was adjusted to visualize the ultrasound image from the POCUS device. Specifically, the smartphone POCUS exam was placed on the patient’s bed in-between their legs and the second smartphone with the AR platform was held over this device such that the ultrasound image and the AR notations could be visualized by the physician performing the exam  provided by the onsite faculty. the exam . ImportaThe procedure was performed successfully, and the nerve block demonstrated appropriate efficacy. After the procedure, the one onsite and the one remote provider completed a survey on the image quality of the video connection. In addition, the remote provider completed a survey of the image quality of the ultrasound image viewed from the video conference app and the onsite provider completed a survey of the AR notations created by the remote provider during the guidance of the nerve block. All surveys were scored using a validated 5-point Likert scale .Survey results showed that the image quality of the video communication was rated 5/5 for both video communication and ultrasound image interpretation by the one onsite and one remote practitioner. The onsite practitioner scored the clarity of the AR notations to identify probe placement position on the body as 5/5 and identification of anatomy and nerve on the ultrasound image as 4/5.Technologic advances in medical ultrasound imaging are helping remove the barriers of costs and portability. These innovations are improving the ability to use medical ultrasound in resource-limited settings as a point of care device. However, a barrier that remains is the skill/training of the providers in these settings. Programs to teach POCUS, in-person, have demonstrated to be effective , but havIn recent years, the development of AR has also been applied to POCUS. Wang et al. evaluated the feasibility of using a specific AR hardware/software platform, Microsoft HoloLens , to remotely guide novice medical trainers through a trauma ultrasound examination . While tOur report demonstrates the use of a smartphone app that allows for the creation of a real-time augmented reality environment in a manner very similar to common smartphone video conference applications. This proof-of-concept case report presents positive feedback from all of the providers involved and supports further exploration in this area. Of note, none of the onsite physicians involved in the case had used the Chalk app before this event. Additional discussion after the event between the onsite and remote providers highlighted that the use of this platform was an improvement over traditional smartphone video conferencing by allowing both users to provide real-time visual cues over the ultrasound image during the procedure. In addition, the AR interface provided a greater ability for depth perception compared to traditional smartphone video conferencing.Importantly, there are several limitations for the setup described in this report. While providers reported no issues with screen glare, the use of two mobile devices to achieve the AR guidance resulted in a limitation of the field-of-view of the remote examiner. In addition, the setup described requires another individual to hold and manipulate the AR smartphone. Additionally, the placement of the ultrasound and AR devices will be different based on patient position and care setting. Finally, the AR video communication in this case report did not include the transfer of any protected health information, as this requires secure communication pathways, which have previously been described . Truly, Indeed, the potential widespread availability of a smartphone-based augmented reality training/guidance application makes this platform very exciting for improving healthcare in resource-limited environments by potentially providing a higher level of communication than standard video conferencing. It is the authors’ hope that this report can be an example to stimulate formal research in this area.