Stream Operators Research Articles

Performance and acceptability of the STREAM Disinfectant Generator for infection prevention and control practices in primary health care facilities in Uganda

BackgroundEffective infection prevention and control programs can positively influence quality of care, increase patient safety, and protect health care providers. Chlorine, a widely used and effective chemical disinfectant, is recommended for infection prevention and control in health care settings. However, lack of consistent chlorine availability limits its use. Electrolytic chlorine generators can address limited chlorine supply and stockouts by enabling onsite production of readily usable, high-quality chlorine cost-effectively. We report the feasibility (i.e., performance, acceptability, chlorine availability, and cost) of the electrolytic STREAM Disinfectant Generator (Aqua Research, New Mexico, USA) device for infection prevention and control in primary health care facilities in Uganda.MethodsWe installed STREAM devices in 10 primary health care facilities in central and western Uganda. Commercial chlorine inventory records (stock cards) were reviewed in each facility to calculate average liters of chlorine received and used per month. These values were compared with actual STREAM chlorine production volumes over the study period to determine its impact on chlorine availability. We collected acceptability data from a purposive sample of device users (n = 16), hospital administrators (n = 10), and district health officers (n = 6) who had been directly involved in the operation or supervision of the STREAM device. We descriptively analyzed the acceptability data by user group and evaluated qualitative responses manually using a thematic approach. Cost data were normalized and modeled to determine a break-even and cost-savings analysis across a five-year period (the minimum expected lifespan of the STREAM device).ResultsChlorine was consistently available without any reported stockouts during the evaluation period. STREAM chlorine production resulted in a 36.9 percent cost-savings over a five-year period compared to commercial chlorine. User acceptability of the STREAM device was high among STREAM operators, hospital administrators, and district health officers, with all respondents reporting that STREAM moderately or significantly improved infection prevention and control practices in the health facility. Overall, 88 percent of device users and 100 percent of hospital administrators wished to continue using the STREAM device instead of commercial chlorine products.ConclusionThe STREAM device has demonstrated significant potential to strengthen infection prevention and control practices in health care facilities in Uganda. Based on the preliminary results, the STREAM device should be considered a promising tool for district hospitals and large health centers facing infection prevention and control challenges in Uganda and elsewhere, provided water and electricity are available. Going forward, implementation of the STREAM device could also be considered in smaller health care facilities in Uganda and elsewhere.

The deglacial history of 79N glacier and the Northeast Greenland Ice Stream

The Northeast Greenland Ice Stream (NEGIS) is the main artery for ice discharge from the northeast sector of the Greenland Ice Sheet (GrIS) to the North Atlantic. Understanding the past, present and future stability of the NEGIS with respect to atmospheric and oceanic forcing is of global importance as it drains around 17% of the GrIS and has a sea-level equivalent of 1.6 m. This paper reconstructs the deglacial and Holocene history of Nioghalvfjerdsbræ (or 79N Glacier); a major outlet of the NEGIS.At high elevation (>900 m asl) autochthonous blockfield, a lack of glacially moulded bedrock and pre LGM exposure ages point to a complex exposure/burial history extending back over half a million years. However, post Marine Isotope Stage 12, enhanced glacial erosion led to fjord incision and plateaux abandonment. Between 900 and 600 m asl the terrain is largely unmodified by glacial scour but post LGM erratics indicate the advection of cold-based ice through the fjord. In contrast, below ∼600 m asl Nioghalvfjerdsfjorden exhibits a geomorphological signal indicative of a warm-based ice stream operating during the last glacial cycle. Dated ice marginal landforms and terrain along the fjord walls show initial thinning rates were slow between ∼23 and 10 ka, but post-10 ka it is evident that Nioghalvfjerdsfjorden deglaciated extremely quickly with complete fjord deglaciation below ∼500 m asl between 10.0 and 8.5 ka.Both increasing air and ocean temperatures were pivotal in driving surface lowering and submarine melt during deglaciation, but the final withdrawal of ice through Nioghalvfjerdsfjorden was facilitated by the action of marine ice sheet instability. Our estimates show that thinning and retreat rates reached a maximum of 5.29 ma−1 and 613 ma−1, respectively, as the ice margin withdrew westwards. This would place the Early Holocene disintegration of this outlet of the NEGIS at the upper bounds of contemporary thinning and retreat rates seen both in Greenland and Antarctica. Combined with recent evidence of ice stream shutdown during the Holocene, as well as predictions of changing ice flow dynamics within downstream sections of the NEGIS catchment, this suggests that significant re-organisation of the terminal zone of the ice stream is imminent over the next century.

Technical Perspective: A Fresh Look at Stream Computation through DSP Glasses

Technical Perspective: A Fresh Look at Stream Computation through DSP Glasses

A method for hierarchical weighted fitting of regular grid DSM with discrete points

Abstract. A Digital Surface Model (DSM) is a crucial spatial geographic information data used to describe the shape of the earth’s surface in Geographic Information Systems (GIS). DSM is the core data used in terrain analysis in GIS. A regular grid DSM is generally generated by interpolating a large number of discrete point clouds. This paper proposes a method of using a hierarchical weighted strategy to fit a regular grid DSM with discrete points. This method uses a pyramid hierarchical strategy to refine the target regular grid from one grid with finer parameters of 3*3, until the nth level (the interval of the grid is equal to the expected interval), and then gradually places the discrete point cloud into the corresponding grid by weighted averaging, and uses the result of this level as the initial value of the next level. This algorithm can avoid the problem of low efficiency in retrieving a large number of discrete point clouds, and the indirect interpolation method not considering the contribution of distant neighboring point clouds. The operation of point cloud data is a stream operation, which does not require consideration of the topological information of point clouds, and has simple operation and no additional memory consumption. It is especially suitable for the production of regular grid DSM with massive point clouds. To verify the effectiveness of this method, the article selected six typical terrain data such as high mountains, mountains, hills, plains, urban areas, and lakes for experiments. The results show that compared with the construct-TIN method for producing DSM, this method has very good processing accuracy and processing efficiency.

Effect of Ni/SiO2 catalyst preparation method on methane decomposition and CO2 gasification cycles

Catalytic methane decomposition is a promising reaction to produce CO2-free hydrogen from methane-rich feedstock with solid carbon as a by-product. Significant research conducted on this reaction to find ways to manage and utilize this solid carbon. In this work, the methane decomposition reaction is followed by Reverse Boudouard Reaction using CO2 feedstock to convert the solid carbon to carbon monoxide, which is a valuable starting component for many chemical applications. Realizing this promising concept would require a catalyst that is efficient for both reactions. Herein, we explored the potential of using solution combustion synthesis (SCS) to make a 5 wt% of Ni supported SiO2 catalyst and benchmarked it versus the conventional impregnation method. The catalyst prepared by SCS showed an improved performance at different temperatures, space velocities, and catalyst pellet sizes. The SCS catalyst successfully completed five repeated cycles reaching up to 38.1 h of stable time on stream operation, whereas the impregnated catalyst was not able to complete the second testing cycle with only 14 h of time on stream operation. A thorough characterization using XRD, H2 and O2 TPR, TEM, SEM, XPS, and Raman spectroscopy were conducted to provide an adequate explanation for the observed performances for both catalysts. The Ni nanoparticles size and distribution, the strength of the metal support interaction, and the nature of graphitic carbon were the key factors affecting the catalytic performance. Insights on how to make an optimal catalyst for this promising process is identified which is a step forward toward making separated H2 and CO streams from methane feedstock and CO2, respectively.

Adaptive Fragment-Based Parallel State Recovery for Stream Processing Systems

Today, large-scale cloud organizations are deploying datacenters and “edge” clusters globally to provide their users with low-latency access to their services. Running stream applications across these geo-distributed sites are emerging as a daily requirement, such as making business decisions from marketing streams, identifying spam campaigns from social network streams, and analyzing existing genomes in different labs and countries to track the sources of a potential epidemic. However, while the progress has been encouraging, the existing efforts have dominantly centered around <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">stateless stream processing</i> , leaving another urgent trend- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">stateful stream processing</i> -much less explored. A driving need is that next-generation stream processing systems need to store and update states during processing, and most importantly, successfully recover large distributed states when faults and failures happen. Existing studies exhibit major limitations including: (1) they mostly inherit MapReduce's “single master/many workers” architecture, where the central master is responsible for all scheduling activities and easily becomes a scalability bottleneck; (2) they offer state recovery mainly through the use of three approaches: replication recovery, checkpointing recovery, and DStream-based lineage recovery, which are either slow, resource-expensive or failing to handle multiple failures; and (3) they are not adaptive to heterogeneous hardware settings in the cloud. In this paper, we present A-FP4S, a novel adaptive fragments-based parallel state recovery mechanism for stream processing systems to manage and recover large distributed states for a massive number of stream applications. The novelty of A-FP4S is that we organize stream operators into a distributed hash table (DHT) based peer-to-peer (P2P) overlay. Then we divide each node's local state into many fragments and periodically store them in each node's multiple neighbors (the leaf set nodes of DHT), ensuring that different sets of available fragments can reconstruct failed states in parallel. By doing that, this failure recovery mechanism is extremely scalable to the size of the lost state, significantly reduces the failure recovery time, and can tolerate multiple node failures. A-FP4S is adaptive to heterogeneous hardware settings (e.g., CPU speed, disk/file-system speed, network bandwidth) by automatic parameter tuning over phases. Compared to Apache Storm, A-FP4S achieves a significant 31.8% to 50.5% reduction in recovery latency. It can scale to many simultaneous failures and successfully recover the state, even more than half of the operators fail or get lost. Large-scale experiments using real-world datasets demonstrate A-FP4S's attractive scalability and adaptivity properties.

Checked corecursive streams: Expressivity and completeness

Checked corecursive streams are a novel approach to stream definitions relying on a semantics of function application detecting cyclic calls, and a well-definedness check ensuring that access to an arbitrary index will always return a result. We extend the technique beyond the simple stream operators considered in previous work, notably by adding an interleaving combinator which has a non-trivial recursion scheme. We show that this actually enhances expressive power, since the interleaving operator cannot be expressed by the others, and that it is still possible to perform a sound and complete well-definedness check, through a symbolic computation which mimics access to an arbitrary index.

Bounding substreams in distributed stream processing

A common problem in distributed stream processing is to split a stream into finite chunks of messages (substreams) and to determine their boundaries: stateful streaming operators should clear outdated state; time window operators should release output after all elements within the specified time range have arrived. Most state-of-the-art SPEs use punctuations to divide a stream into bounded substreams of messages. The punctuation approach is powerful but has limitations: it does not support cyclic dataflows, is poorly scalable in some cases due to intensive use of broadcasts, and becomes inefficient when the number of chunks or cluster size becomes significant. We introduce a new substream tracking technique called trAcker that overcomes the limits of punctuations. We experimentally evaluate the properties of trAcker in both synthetic and real-world environments. Experiments show that our technique is scalable, outperforms punctuations for a large number of substreams, and efficiently handles real-world cyclic dataflows.

코로나19로 인한 비대면 카지노 운영의 필요성

Purpose: The purpose of this study is the necessity of non-face-to-face casino operation due to COVID-19. Method: Current literature studies on various video streaming, live streaming, iGaming, and social casino operations in non-face-to-face casino operations due to COVID-19 have been investigated. Results: It was confirmed that foreign-only casinos' business performance was rapidly deteriorating due to COVID-19, while non-face-to-face casino operation performance increased. Conclusion: The introduction of non-face-to-face casino services (video streaming, live streaming, iGaming, social casino) using ICT technology to overcome the COVID-19 and periodic infectious disease crisis and maintain foreign casino customers (VIP, Mass, etc.) is also expected to be another fundamental improvement in responding to the global pandemic. Interdisciplinary Research Implications: This study is a study in the field of tourism on the current status of the non-face-to-face casino industry, and interdisciplinary research with the field of physical education in the future will be able to examine the impact of COVID-19 in the non-face-to-face sports betting market.

Communication-Traffic-Assisted Mining and Exploitation of Buffer Overflow Vulnerabilities in ADASs

Advanced Driver Assistance Systems (ADASs) are crucial components of intelligent vehicles, equipped with a vast code base. To enhance the security of ADASs, it is essential to mine their vulnerabilities and corresponding exploitation methods. However, mining buffer overflow (BOF) vulnerabilities in ADASs can be challenging since their code and data are not publicly available. In this study, we observed that ADAS devices commonly utilize unencrypted protocols for module communication, providing us with an opportunity to locate input stream and buffer data operations more efficiently. Based on the above observation, we proposed a communication-traffic-assisted ADAS BOF vulnerability mining and exploitation method. Our method includes firmware extraction, a firmware and system analysis, the locating of risk points with communication traffic, validation, and exploitation. To demonstrate the effectiveness of our proposed method, we applied our method to several commercial ADAS devices and successfully mined BOF vulnerabilities. By exploiting these vulnerabilities, we executed the corresponding commands and mapped the attack to the physical world, showing the severity of these vulnerabilities.

Live streaming platform operations and coordination under the cap-and-trade regulation: Platform-enabled mode versus platform-agency mode

We consider a supply chain consisting of a supplier and a manufacturer where the manufacturer sells its products directly or through a live streaming platform (LSP). Operating in either the platform-enabled and platform-agency mode under the cap-and-trade regulation, the platform has platform power that reflects its ability to expand the market size. We find that the optimal production quantity in the platform-agency mode may decrease with the cap and platform power. The supplier and manufacturer can always be coordinated under the wholesale price contract in the platform-enabled mode. However, in the platform-agency mode, the two firms can be coordinated under low or high platform power, but whether coordination is achieved under moderate platform power depends on the unit carbon emissions of the products. If the platform power is low or high, the platform-enabled mode yields more total production quantity; otherwise, the platform-agency mode yields more total production quantity. Whether the platform-enabled or platform-agency mode generates a higher profit for the manufacturer highly depends on the promotion cost. By considering product investment and sales effort, we find the following: (i) When considering product investment, the supplier and manufacturer cannot be coordinated under the wholesale price contract in either mode. (ii) When considering sales effort, the firms can be coordinated in the platform-enabled mode, while in the platform-agency mode, whether they can be coordinated under the wholesale price contract depends on the cost coefficient and the unit carbon emissions of the products.

Efficient Separating Collected Seedlings Based on Precise Subdivision Air Streams

Automatic grafting and cutting machines can be employed to satisfy the increasing demand for seedlings without soil-borne diseases in a short period. The main approach used to feed seedlings for automatic grafting and cutting machines is artificial, which limits the improvement of grafting and cutting machine productivity. The separation system with a subdivision air stream can stably feed seedlings for cutting and grafting machines; however, the separation efficiency is low when a few seedlings are in the separator. To solve this problem, a feedback monitoring device with a photosensitive sensor as the sensing element and feedback functions on the status of seedlings in the separator was developed. Through experiments using a photosensitive sensor to monitor the separation process of tomato seedlings, the results showed that the effect on the effective seedling blowing rate varied from large to small depending on the seedling size, light intensity, and sensor diameter. The results of separation experiment showed that the productivity of the entire system was 8784 plants/h, which satisfies the productivity needs of the grafting and cutting machine. Compared with the separation device without feedback monitoring, the productivity increased by 39%, the damage rate decreased by 4%, and the number of subdivided air stream operations was reduced by 47%.

Deriving an Optimal Operation Plan for Hydraulic Facilities with Complex Channels through Unsteady Flow Simulations

In recent years, the frequency of flooding damage has increased owing to torrential rains caused by abnormal weather and rising sea levels, which can be attributed to global warming. In particular, in the case of low-tide rivers, when a high tide and critical rainfall occur simultaneously, the flood damage will increase due to the increased external water level. The establishment of a disaster prevention plan through a simulation of existing inequality streams may be suitable for general rivers; however, it is inadequate for considering the effects of tide changes over time, such as those in a reduced tide stream. Therefore, in this study, an optimal operation plan is formulated based on unsteady flow simulations in regions where a large number of hydraulic facilities are installed, and an optimal river management plan is derived for the flood season. For the Ara Waterway (Ara Stream) and Gulpo Stream managed by the Korea Water Resources Corporation, various hydraulic facilities (weir, inverted syphon, etc.) are operated in conjunction with the West Sea to mitigate the continuous flood damage. In that context, a West Sea drainage gate has been installed. Correspondingly, it is necessary to optimize the flood exclusion capacity by deriving an optimal operation plan because it directly affects the water level in hydraulic facilities such as the Right No. 1, Left No. 1, and flood gates, which are the most important drainage structures for the Gulpo Stream operation. Herein, through a trial-and-error method, an optimal operation plan is derived to reduce the flood frequency in the Ara Waterway and Gulpo Stream.

An immersed boundary/multi-relaxation time lattice Boltzmann method on adaptive octree grids for the particle-resolved simulation of particle-laden flows

We present an immersed boundary/multi-relaxation time lattice Boltzmann method for the particle-resolved simulation of particle-laden flows. The no-slip boundary condition is handled by an explicit feedback immersed boundary method for fixed and moving particles with arbitrary shape. Two special treatments are applied to improve the simulation stability and accuracy: (i) a smoothed discrete delta function (Yang et al. (2009) [47]) is adopted to suppress the spurious force oscillations and (ii) a multi-relaxation time collision operator is utilized to fix the viscosity-dependent numerical slip error of the immersed boundaries. To further reduce the computational effort, we extend the method from fixed and uniform Cartesian grids to adaptive quadtree/octree grids by implementing it in the open-source software Basilisk. A Lax-Wendroff streaming operator is adopted in our method to retain second-order accuracy in both space and time on non-uniform grids, as well as to maintain a unified time scale over the entire computational domain. Consequently, one collision-streaming operation only is required per time step at all grid levels. We test our proposed method on a set of validation cases corresponding to assorted incompressible flows with fixed and moving rigid particles in both 2D and 3D. The accuracy and robustness of our method are demonstrated via thorough comparison with the analytical, experimental and numerical data provided in the literature.

Cancer Clinic Redesign: Opportunities for Resource Optimization.

Ambulatory cancer centers face a fluctuating patient demand and deploy specialized personnel who have variable availability. This undermines operational stability through the misalignment of resources to patient needs, resulting in overscheduled clinics, budget deficits, and wait times exceeding provincial targets. We describe the deployment of a Learning Health System framework for operational improvements within the entire ambulatory center. Known methods of value stream mapping, operations research and statistical process control were applied to achieve organizational high performance that is data-informed, agile and adaptive. We transitioned from a fixed template model by an individual physician to a caseload management by disease site model that is realigned quarterly. We adapted a block schedule model for the ambulatory oncology clinic to align the regional demand for specialized services with optimized human and physical resources. We demonstrated an improved utilization of clinical space, increased weekly consistency and improved distribution of activity across the workweek. The increased value, represented as the ratio of monthly encounters per nursing worked hours, and the increased percentage of services delivered by full-time nurses were benefits realized in our cancer system. The creation of a data-informed demand capacity model enables the application of predictive analytics and business intelligence tools that will further enhance clinical responsiveness.

Highly stable and selective layered Co-Al-O catalysts for low-temperature CO2 methanation

A series of layered Co-Al-O catalysts derived from hydrotalcites for low-temperature CO2 methanation were prepared via a hydrothermal method and reduced at 500, 550, 600, 650, and 700 °C, respectively. The characterisation results from XPS and CO2-TPD revealed that the Co0 content and basic sites over these catalysts were firstly increased and then decreased with the reduction temperature increasing, which led to the efficient dissociation of H2 and CO2 adsorption. In situ DRIFTS measurements revealed that the formation of CH4 proceeded via the hydrogenation of carbonate and formate as intermediates. A superior catalytic performance of Co-Al-O-600 catalyst for CO2 methanation was achieved with a CO2 conversion of 74% and a CH4 selectivity of 99% at low temperature of 250 °C. Moreover, it exhibited excellent resistance to coking and sintering upon a 240 h time on stream operation.

Quantum lattice representation for the curl equations of Maxwell equations

A quantum lattice representation (QLA) is devised for the initial value problem of one-dimensional (1D) propagation of an electromagnetic disturbance in a scalar dielectric medium satisfying directly only the two curl equations of Maxwell. It si found that only 4 qubits/node are required. The collision, streaming, and potential operators are determined so as to recover the two curl equations to second order. Both polarizations are considered.

Road to Salvation: Streaming Clients and Content Delivery Networks Working Together

Streaming media has truly become one of the most popular applications on the Internet. Viewers are spoiled for choice, and content providers compete to provide the best viewer experience. Traditionally, it has been challenging for content providers to get deep insights into the performance of their large-scale streaming operations. A new standard, Common Media Client Data (CMCD), aims to fundamentally change this. After providing an overview of this standard and describing some possible application scenarios, we present an open source sample implementation for readers to explore this topic further in their own practical environments.

Scabbard

Single-node multi-core stream processing engines (SPEs) can process hundreds of millions of tuples per second. Yet making them fault-tolerant with exactly-once semantics while retaining this performance is an open challenge: due to the limited I/O bandwidth of a single-node, it becomes infeasible to persist all stream data and operator state during execution. Instead, single-node SPEs rely on upstream distributed systems, such as Apache Kafka, to recover stream data after failure, necessitating complex cluster-based deployments. This lack of built-in fault-tolerance features has hindered the adoption of single-node SPEs. We describe Scabbard, the first single-node SPE that supports exactly-once fault-tolerance semantics despite limited local I/O bandwidth. Scabbard achieves this by integrating persistence operations with the query workload. Within the operator graph, Scabbard determines when to persist streams based on the selectivity of operators: by persisting streams after operators that discard data, it can substantially reduce the required I/O bandwidth. As part of the operator graph, Scabbard supports parallel persistence operations and uses markers to decide when to discard persisted data. The persisted data volume is further reduced using workload-specific compression: Scabbard monitors stream statistics and dynamically generates computationally efficient compression operators. Our experiments show that Scabbard can execute stream queries that process over 200 million tuples per second while recovering from failures with sub-second latencies.

Reflection and transmission of electromagnetic pulses at a planar dielectric interface: Theory and quantum lattice simulations

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers, it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is described by Maxwell equations with an appropriate description of the plasma as a dielectric medium. Before advancing to the tensor dielectric of a magnetized plasma, this paper considers electromagnetic wave propagation in a one-dimensional inhomogeneous scalar dielectric. The classic theory of scattering of plane electromagnetic waves at a planar interface, separating two different dielectric media, leads to Fresnel equations for reflection and transmission coefficients. In contrast to plane waves, this paper is on the reflection and transmission of a spatially confined electromagnetic pulse. Following an analytical formulation for the scattering of a Gaussian pulse, it is deduced that the maximum transmission coefficient for a pulse is n2/n1 times that for a plane wave; the incident and transmitted pulses propagate in dielectric media with refractive indices n1 and n2, respectively. The analytical theory is complemented by numerical simulations using a quantum lattice algorithm for Maxwell equations. The algorithm, based on the Riemann–Silberstein–Weber representation of the electromagnetic fields and expressed in terms of qubits, is an interleaved sequence of entangling operators at each lattice site and unitary streaming operators, which transmit information from one site to an adjacent lattice site. Besides substantiating results from the theory for Gaussian pulses, numerical simulations show their validity for non-Gaussian pulses. Apart from their time-asymptotic forms, the simulations display an interplay between the incident, reflected, and transmitted pulses in the vicinity of the transition region between two dielectric media.