Butterfly Network Research Articles

On Some Ev-Degree and Ve-Degree Dependent Indices of Benes Network and營ts Derived Classes

One of the most recent developments in the field of graph theory is the analysis of networks such as Butterfly networks, Benes networks, Interconnection networks, and David-derived networks using graph theoretic parameters. The topological indices (TIs) have been widely used as graph invariants among various graph theoretic tools. Quantitative structure activity relationships (QSAR) and quantitative structure property relationships (QSPR) need the use of TIs. Different structure-based parameters, such as the degree and distance of vertices in graphs, contribute to the determination of the values of TIs. Among other recently introduced novelties, the classes of ev-degree and ve-degree dependent TIs have been extensively explored for various graph families. The current research focuses on the development of formulae for different ev-degree and ve-degree dependent TIs for dimensional Benes network and certain networks derived from it. In the end, a comparison between the values of the TIs for these networks has been presented through graphical tools.

Wide-Band Butterfly Network: Stable and Efficient Inversion Via Multi-Frequency Neural Networks

We introduce an end-to-end deep learning architecture called the wide-band butterfly network (WideBNet) for approximating the inverse scattering map from wide-band scattering data. This architecture incorporates tools from computational harmonic analysis, such as the butterfly factorization, and traditional multi-scale methods, such as the Cooley–Tukey FFT algorithm, to drastically reduce the number of trainable parameters to match the inherent complexity of the problem. As a result, WideBNet is efficient: it requires fewer training points than off-the-shelf architectures and has stable training dynamics which are compatible with standard weight initialization strategies. The architecture automatically adapts to the dimensions of the data with only a few hyper-parameters that the user must specify. WideBNet is able to produce images that are competitive with optimization-based approaches, but at a fraction of the cost, and we also demonstrate numerically that it learns to super-resolve scatterers with a full aperture configuration.

Quantum network coding via time-bin multiplexing

<p indent="0mm">Quantum network coding is used to overcome the congestion problem in quantum networks, which can effectively improve the transmission efficiency and total throughput of quantum networks. Here, we propose a time-bin complexing network coding method for crossly transmitting two arbitrary single-qubit states over the butterfly network. To solve the congestion problem, a single photon with polarization and time-bin degrees of freedom acts as a bridge to entangle the two-dimensional quantum memories of two intermediate nodes in a heralded way. Finally, quantum 2-pair unicast communication is completed based on quantum teleportation and the heralded double entangled channels. Concerning dishonest intermediate nodes being concerned, a security-enhanced quantum 2-pair unicast communication protocol is presented. Security and performance are analyzed, and the result shows that the improved protocol is secure against the general entangle-measure attack of intermediate nodes. It can be extended to multiple unicast communication over a more general quantum network by exploiting the time-bin complexing technique.

Automatic separation of laminar-turbulent flows on aircraft wings and stabilisers via adaptive attention butterfly network

Many of the laminar-turbulent flow localisation techniques are strongly dependent upon expert control even-though determining the flow distribution is the prerequisite for analysing the efficiency of wing & stabiliser design in aeronautics. Some recent efforts have dealt with the automatic localisation of laminar-turbulent flow but they are still in infancy and not robust enough in noisy environments. This study investigates whether it is possible to separate flow regions with current deep learning techniques. For this aim, a flow segmentation architecture composed of two consecutive encoder-decoder is proposed, which is called Adaptive Attention Butterfly Network. Contrary to the existing automatic flow localisation techniques in the literature which mostly rely on homogeneous and clean data, the competency of our proposed approach in automatic flow segmentation is examined on the mixture of diverse thermographic observation sets exposed to different levels of noise. Finally, in order to improve the robustness of the proposed architecture, a self-supervised learning strategy is adopted by exploiting 23.468 non-labelled laminar-turbulent flow observations.

Comparison of four handheld point-of-care ultrasound devices by expert users

BackgroundPoint-of-care ultrasound (POCUS) is rapidly becoming ubiquitous across healthcare specialties. This is due to several factors including its portability, immediacy of results to guide clinical decision-making, and lack of radiation exposure to patients. The recent growth of handheld ultrasound devices has improved access to ultrasound for many clinicians. Few studies have directly compared different handheld ultrasound devices among themselves or to cart-based ultrasound machines. We conducted a prospective observational study comparing four common handheld ultrasound devices for ease of use, image quality, and overall satisfaction. Twenty-four POCUS experts utilized four handheld devices (Butterfly iQ+™ by Butterfly Network Inc., Kosmos™ by EchoNous, Vscan Air™ by General Electric, and Lumify™ by Philips Healthcare) to obtain three ultrasound views on the same standardized patients using high- and low-frequency probes.ResultsData were collected from 24 POCUS experts using all 4 handheld devices. No single ultrasound device was superior in all categories. For overall ease of use, the Vscan Air™ was rated highest, followed by the Lumify™. For overall image quality, Lumify™ was rated highest, followed by Kosmos™. The Lumify™ device was rated highest for overall satisfaction, while the Vscan Air™ was rated as the most likely to be purchased personally and carried in one’s coat pocket. The top 5 characteristics of handheld ultrasound devices rated as being “very important” were image quality, ease of use, portability, total costs, and availability of different probes.ConclusionsIn a comparison of four common handheld ultrasound devices in the United States, no single handheld ultrasound device was perceived to have all desired characteristics. POCUS experts rated the Lumify™ highest for image quality and Vscan Air™ highest for ease of use. Overall satisfaction was highest with the Lumify™ device, while the most likely to be purchased as a pocket device was the Vscan Air™. Image quality was felt to be the most important characteristic in evaluating handheld ultrasound devices.

Adiposity Assessment with a Novel Portable Ultrasound Device

ObjectivesUltrasound (US) systems are increasingly being used to quantify total body and regional adiposity (Epub 2015. PMID: 26,740,255) along with providing estimates of muscle fat infiltration (echogenicity; Epub 2020. PMID: 33,111,338). The aim of the current study was to evaluate the feasibility of a small, relatively low-cost ultrasound device (ButterflyIQ; Butterfly Network, Guilford, CT) that interfaces with an iPad to assess total body fat quantified with dual-energy X-ray absorptiometry (DXA).MethodsParticipants were a convenience sample of 59 healthy adults who were diverse in age, ethnicity, and adiposity. Total and regional fat masses were measured using DXA (Hologic, Marlborough, MA). Fat thicknesses were taken using the Butterfly at two points on the right thigh. Echogenicity of the rectus femoris was also determined using ImageJ (NIH, Bethesda, MD). Regression analysis was used to evaluate the associations between US-derived fat thickness and DXA-measured total body and leg fat mass. Correlations were also examined between US echogenicity and phase angle at 50 kHz (InBody S10; Seoul, South Korea), an established method for estimating muscle quality.ResultsOf the 59 participants, 2 females and 1 male were excluded due to low US image quality. Mid-thigh US adipose tissue layer thickness showed the strongest correlations (R2s) with total and right leg fat mass: females, 0.80 and 0.87; males, 0.56 and 0.53 (all p < 0.001). Corresponding correlations at the third-thigh site were smaller in magnitude (0.68 and 0.79; 0.41 and 0.37). A significant (p < 0.05) inverse relationship (R2, 0.10) was present between US echogenicity and phase angle at 50 kHz.ConclusionsThe evaluated small and portable US device has the important potential to phenotype adiposity and muscle quality in clinical and field settings that lack availability of larger, more costly, and complex measurement systems.Funding SourcesThis work was partially supported by National Institutes of Health NORC Center Grants P30DK072476, Pennington/Louisiana; and P30DK040561, Harvard; and R01DK109008, Shape UP! Adults.

Quantum network coding based on six-qubit entangled state

In order to improve the security and transmission efficiency of quantum network coding (QNC), we propose a new QNC scheme based on butterfly network. The scheme uses two groups of GHZ states to distribute quantum entangled states through intermediate nodes, so as to establish the connection between multiple nodes and achieve safe and reliable quantum traffic. This paper can not only improve the security of QNC, but also reduce the transmission of particles and improve the anti-interference ability of information. Compared with the traditional network coding method based on a priori entanglement, our scheme is a better attempt.

MO362: Braunschweig Body Composition, Butterfly Sonography and Drug Dosing in AKI Study (B3 D2 AKI––Study)

Abstract BACKGROUND AND AIMS In-hospital AKI is associated with increased morbidity and mortality. AKI Alert systems are frequently used to allow time detection of AKI patients based on changes in creatinine. We aimed to examine the hydration status, medication errors and prior existing CKD in a series of AKI 3 patients in a tertiary care hospital. METHOD Prospective single centre cohort study. Study was approved by the local IRB. Hydration status was assessed by Bioimpedance using the body composition monitor (Fresenius Medical Care). Renal size and exclusion of postrenal failure were accomplished using a point of care ultrasound system (Butterfly Network Inc.). Pharmacotherapy was entered into the Federal Medication Plan of Germany (Bundesmedikationsplan). RESULTS A total of 101 patients with AKI 3 were identified based on changes in creatinine only. The median (IQR) age was 74.0 (64.7–82.0) years with a BMI of 27.8 (23.5–34.2) kg/m2. The baseline creatinine of the patients was 1.53 (0.92–2.85) mg/dL. At the time of AKI 3 diagnosis the median [IQR] 4.1 (1.9–5.9) L. Systolic blood pressure was 116 (100–140) mmHg (Fig. 1). Median (IQR) kidney length was 10.4 (9.2–11.7) cm. Polypharmacy (&amp;gt; 5 drugs) was seen in 89.7% of all patients. Almost half of the patients (48.3%) received 10 or more drugs. A total of 38% of patients receiving an antibiotic received an inadequately high dose, followed by 7.8% receiving an inadequate dosing of oral antidiabetic drugs. CONCLUSION Patients detected by an AKI alert in a tertiary care hospital did mostly neither exhibit low blood pressure nor volume depletion. Postrenal AKI was undetected in 1 out of 101 patients. Medication dosing errors were frequently seen, especially in the dosing of antibiotics. A joined nephron-pharmacological approach seems to be important in patients with hospital acquired AKI 3.

A secure crossing two qubits protocol based on quantum homomorphic encryption

In order to solve the information leakage caused by dishonest intermediate nodes in quantum network coding, we apply quantum homomorphic encryption to the butterfly network, and propose a secure protocol for crossing two qubits. Firstly, in the communication process between two senders and the first intermediate node, two senders encrypt their measured particles and send them to the first intermediate node for encoding. If two intermediate nodes are dishonest and know the encryption rules between two senders and two receivers, or there is an external eavesdropper, none of them can recover the transmitted qubits of two senders from the encrypted transmitted particles. In this way, our protocol can transmit two qubits safely and crossly in the butterfly network. Secondly, by analyzing the internal participant attack and the external eavesdropper attack launched by dishonest intermediate nodes and an external eavesdropper respectively, it is confirmed that our protocol is secure. Finally, the experimental simulation results based on the Qiskit framework prove that our protocol is feasible.

Network Coding-Based D2D Transmission for Public Safety Networks over LTE HetNets and 5G Networks

Device to Device (D2D) communications appear like an emergency solution for the Public Safety Network (PSN) when the LTE cell range is limited. D2D networks can use the unlicensed frequency bands, as this makes their transmissions cheaper and easier to deploy. Therefore, the development of this technology must deal with the security challenge. On the one hand, it is important to know how to design a secure D2D solution within the small cells, and on the other hand, the new scheme needs to deal with the problem of radio resources limit, since it will be used during emergency situations. This paper develops a new algorithm, named Generalized Secure Network Coding-based Data splitting algorithm (G-SNCDS), to ensure a secure data transmission for Public Safety D2D communications over LTE Heterogeneous Networks (HetNets) and 5G networks, without using additional radio resources. Our approach consists of performing Network Coding (NC) data packets transmissions based on a new Data Splitting (DS) technique, which we developed, based on a constructed butterfly effect that uses a new Butterfly network algorithm that we propose. Our solution enhances the security without affecting the level of Quality of Service (QoS). Thus, it is more suitable when network resources are limited. The simulation results show that our approach provides a secure D2D communication without increasing the overhead in the network.

Wireless Communication Strategy with BATS Codes for Butterfly Network

In this paper, two transmission schemes for batched sparse(BATS) codes based on a multicast protocol in a butterfly network are studied. For both of the schemes, a source file is first segmented into several packets at the source node, which are then coded with outer coder of the BATS codes to generate potentially unlimited batches. Rather than the linear network, in which the packets are directly transmitted to the next node, the packets will be forwarded to multiple nodes in the butterfly network. All the intermediate nodes which receive the packets recode them with random linear network coding (RLNC). At the destination node receivers, the sink node decodes the packets transmitted from different links. The Scheme I requires the intermediate nodes to recode the packets until all of them are received. On the contrary, the intermidate nodes of Scheme II just recode the packets as soon as receiving them and forward the recoded packets to the next node immediately. The Belief Propagation(BP) decoders of these two schemes are studied and applied to Scheme I and Scheme II respectively. The simulation results show that Scheme I consumed fewer batches than Scheme II, which indicates Scheme I outperforms Scheme II.

Twin vertices in fault-tolerant metric sets and fault-tolerant metric dimension of multistage interconnection networks

A set of vertices S⊆V(G) is a resolving set of a graph G if for each x,y∈V(G) there is a vertex u∈S such that d(x,u)≠d(y,u). A resolving set S is a fault-tolerant resolving set if S∖{x} is a resolving set for every x∈S. The fault-tolerant metric dimension (FTMD) β′(G) of G is the minimum cardinality of a fault-tolerant resolving set. It is shown that each twin vertex of G belongs to every fault-tolerant resolving set of G. As a consequence, β′(G)=n(G) iff each vertex of G is a twin vertex, which corrects a wrong characterization of graphs G with β′(G)=n(G) from [Mathematics 7(1) (2019) 78]. This FTMD problem is reinvestigated for Butterfly networks, Benes networks, and silicate networks. This extends partial results from [IEEE Access 8 (2020) 145435–145445], and at the same time, disproves related conjectures from the same paper.Dedicated to Dr. Bharati Rajan on her 70th birthday

Modified Zagreb Connection Indices for Benes Network and Related Classes

The study of networks such as Butterfly networks, Benes networks, interconnection networks, David‐derived networks through graph theoretical parameters is among the modern trends in the area of graph theory. Among these graph theoretical tools, the topological Indices (TIs) have been frequently used as graph invariants. TIs are also the essential tools for quantitative structure activity relationship (QSAR) as well as quantity structure property relationships (QSPR). TIs depend on different parameters, such as degree and distance of vertices in graphs. The current work is devoted to the derivation of 2‐distance based TIs, known as, modified first Zagreb connection index and first Zagreb connection index (ZC1) for r− dimensional Benes network and some classes generated from Benes network. The horizontal cylindrical Benes network (HCB(r)), vertical cylindrical Benes network (VCB(r)), and toroidal Benes network (TB(r)) are the three classes generated by identifying the vertices of the first row with the last row, the first column with the last column of the Benes network. The obtained results are also analyzed through graphical tools.

Reaching Efficient Byzantine Agreements in Bipartite Networks

For reaching efficient deterministic synchronous Byzantine agreement upon partially connected networks, the traditional broadcast primitive is extended and integrated with a general framework. With this, the Byzantine agreement is extended to fully connected bipartite networks and some bipartite bounded-degree networks. The complexity of the Byzantine agreement is lowered and optimized with the so-called Byzantine-levers under a general system structure. Some bipartite simulation of the butterfly networks and some more refined properties of bipartite bounded-degree networks are also provided for building efficient incomplete Byzantine agreement under the same system structure. It shows that efficient real-world Byzantine agreement systems can be built with the provided algorithms with sufficiently high system assumption coverage. Meanwhile, the proposed bipartite solutions can improve the dependability of the systems in some open, heterogeneous, and even antagonistic environments.

Point-of-Care Ultrasound Curriculum for Endotracheal Tube Confirmation for Pediatric Critical Care Transport Team Through Remote Learning and Teleguidance

ObjectivePoint-of-care ultrasound (POCUS) is used to manage patients in real time. This study aimed to teach pediatric critical care team members to use POCUS for endotracheal tube (ETT) placement confirmation. A secondary aim was to assess the feasibility of a remote curriculum for this purpose. MethodsThe Kern 6-step approach was used. The curriculum involved virtual didactics, asynchronous learning modules, and remote hands-on sessions using teleguidance with the Butterfly IQ+ probe, Butterfly Network, Inc, Guilford, CT. Participants learned direct and indirect methods of ETT placement confirmation and were directed to practice independently. Outcomes included attitudes and satisfaction, knowledge and skills acquisition and retention, and the use of POCUS on shift. ResultsTen participants completed the curriculum. The average knobology and quiz scores improved by 29.3% and 20.8%, respectively. Improvement was sustained at re-evaluation. Seven of 10 participants performed independent scans. At the 3-month reassessment, most demonstrated mastery of thoracic scans. All required prompting for satisfactory tracheal scans. All felt positively toward POCUS and the remote curriculum. ConclusionPediatric critical care team members acquired and retained knowledge and skills for POCUS basics and ETT placement confirmation through a remote curriculum. Participants were satisfied with the course. Further studies are needed to reassess longer-term knowledge and skill retention and the effects on patient outcomes.

Edge Forcing in Butterfly Networks

A zero forcing set is a set S of vertices of a graph G, called forced vertices of G, which are able to force the entire graph by applying the following process iteratively: At any particular instance of time, if any forced vertex has a unique unforced neighbor, it forces that neighbor. In this paper, we introduce a variant of zero forcing set that induces independent edges and name it as edge-forcing set. The minimum cardinality of an edge-forcing set is called the edge-forcing number. We prove that the edge-forcing problem of determining the edge-forcing number is NP-complete. Further, we study the edge-forcing number of butterfly networks. We obtain a lower bound on the edge-forcing number of butterfly networks and prove that this bound is tight for butterfly networks of dimensions 2, 3, 4 and 5 and obtain an upper bound for the higher dimensions.

Quantum network recovery from multinode failure using network encoding with GHZ states on higher-order butterfly networks

We propose a protocol to transmit three quantum states crossly in a butterfly network with prior entanglement, in the form of GHZ states, between three senders. The proposed protocol requires only one qubit transmission or two classical bits transmission in each channel of the network. We generalize this protocol to higher number of qubits with multiqubit GHZ states towards quantum network operability using network coding with multiqubit GHZ states on higher-order butterfly networks.

A Novel Tradeoff Analysis between Traffic Congestion and Packing Density of Interconnection Networks for Massively Parallel Computers

From disaster prevention to mitigation, drug analysis to drug design, agriculture to food security, IoT to AI, and big data analysis to knowledge or sentiment mining, a high computation power is a prime necessity at present. As such, massively parallel computer (MPC) systems comprising a large number of nodes are gaining popularity. To interconnect these huge numbers of nodes efficiently, hierarchical interconnection networks are an attractive and feasible option. A Tori-connected flattened butterfly network (TFBN) has been proposed by the authors in a prior work for future generation MPC systems. In the previous study, the static network performance and static cost-effectiveness were evaluated. In this research, a novel trade-off factor named message traffic congestion vs. packing density trade-off factor has been proposed, which characterizes the message congestion in the network and its packing density. The factor is used to statically assess the suitability of the implementation of an interconnection network. The message traffic density, packing density, and new factor have been evaluated for the proposed network and similar competitive networks such as TTN, TESH, 2D-Mesh, 3D-Mesh, 2D-Torus, and 3D-Torus. It has been found that the performance of the TFBN is superior to the other networks.

High dimensional quantum network coding based on prediction mechanism over the butterfly network

The high-dimensional quantum system greatly improve the quantum channel capacity and information storage space, and achieve high-dimensional quantum information transmission, which enhance the speed of quantum computing and quantum information processing. In this paper, a high-dimensional quantum teleportation protocol without information loss is proposed. We consider pre-sharing a high-dimensional non-maximum entangled state as a quantum channel between sender and receiver. By adding auxiliary particle and performing high-dimensional local operations, it is possible to achieve high-dimensional quantum teleportation without information loss. Simultaneously, we apply the protocol to butterfly network, and propose a novel high-dimensional quantum network coding based on prediction mechanism. In our scheme, we use Z-{|0⟩, |1⟩} basis to predict the transmission of high dimensional states over the butterfly network. When the prediction is successful, the deterministic transmission of high-dimensional quantum states can be realized over the butterfly network. Our scheme greatly saves the usage of quantum and classical channels, which improves the utilization efficiency of both channels.

Safety and Efficacy of Letetresgene Autoleucel (lete-cel; GSK3377794) Alone or in Combination with Pembrolizumab in Relapsed and Refractory Multiple Myeloma

Safety and Efficacy of Letetresgene Autoleucel (lete-cel; GSK3377794) Alone or in Combination with Pembrolizumab in Relapsed and Refractory Multiple Myeloma