Bidirectional Channel Research Articles

Enhancing convolution-based sentiment extractor via dubbed N-gram embedding-related drug vocabulary

Everyday patients’ narratives on social media can reveal crucial public health issues. Mining those online narratives, which remained so far unconsidered, may mirror further hidden patient health status. Deep learning-based sentiment analysis (SA) approaches broadly focus on grammar directions such as semantic direction or only center on extract sentiment words. They provide both richer representation capabilities and better performance but do not consider the related medication concepts. As a result, the inaccurate recognition of related drug entities may seriously fail to retrieve the relevant sentiment expressed, leading to a lower recall than desired. Thus, the frequent use of informal medical language, non-standard format, wrongly spelled, and abbreviation forms, as well as typos in social media messages, has to be taken into consideration. In other words, the core of efficiently quantifying the sentimental aspects for related medication texts hardly involves a degree of medical language comprehension. In this paper, we seek to improve the importance of considering related drug entities that keep appearing in new Unicode Versions, ranging from drugs’ names, disease symptoms, drug misuse to potentially adverse effects. We propose N-gram-based convolution vocabulary scheme, which is dedicated mainly to featuring text under medical setting and clarifying related sentiment at the same level. This vectorization results in highly sentiment extraction, which produces medical concept normalization under distributed dependency. This architecture’s layers are a shared neural network between the medical featuring channel and the bidirectional sentiment information detector channel. Fewer approaches are proposed in this matter, we evaluate the effectiveness and transferability of this study across five benchmarking datasets and various online medication-related posts (Twitter posts, Parkinson’s disease forum’s discussions), which were significantly better than all other baselines.

A pragmatic study of oath swearing in late Anglo Norman and Middle English

AbstractProfanity has attracted much scholarly attention for the reason that swearing, oaths, and insults “manifest language use in its most highly charged state” (Taavitsainen 1997: 815). This article examines the possible functions of swearingper membra Christi[by Christ’s limbs], starting with a particularly revealing example from a group of late medieval pedagogical dialogues, theManières de langage. Taking the perlocutionary reaction to this utterance as a starting point, the wider phenomenon of swearing on the body parts of Christ in both Middle English and Anglo Norman will be explored. This behaviour was initially conceptualised (and widely condemned) as an act of blasphemy, the notion of dismembering Jesus being especially widespread. However, this article also concerns itself with the emotive interjectory function of swearing oaths on God and Christ, and will posit that this behaviour is caught in a long process of pragmaticalisation during the high and late Middle Ages. This research supports the view of a bidirectional channel of influence between Middle English and Anglo Norman, and suggests a similar trajectory of both pragmatic development and language attitudes.

BR$^2$Net: Defocus Blur Detection Via a Bidirectional Channel Attention Residual Refining Network

Due to the remarkable potential applications, defocus blur detection, which aims to separate blurry regions from an image, has attracted much attention. Although significant progress has been made by many methods, there are still various challenges that hinder the results, e.g., confusing background areas, sensitivity to the scale and missing the boundary details of the defocus blur regions. To solve these issues, in this paper, we propose a deep convolutional neural network (CNN) for defocus blur detection via a Bi-directional Residual Refining network (BR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> Net). Specifically, a residual learning and refining module (RLRM) is designed to correct the prediction errors in the intermediate defocus blur map. Then, we develop a bidirectional residual feature refining network with two branches by embedding multiple RLRMs into it for recurrently combining and refining the residual features. One branch of the network refines the residual features from the shallow layers to the deep layers, and the other branch refines the residual features from the deep layers to the shallow layers. In such a manner, both the low-level spatial details and highlevel semantic information can be encoded step by step in two directions to suppress background clutter and enhance the detected region details. The outputs of the two branches are fused to generate the final results. In addition, with the observation that different feature channels have different extents of discrimination for detecting blurred regions, we add a channel attention module to each feature extraction layer to select more discriminative features for residual learning. To promote further research on defocus blur detection, we create a new dataset with various challenging images and manually annotate their corresponding pixelwise ground truths. The proposed network is validated on two commonly used defocus blur detection datasets and our newly collected dataset by comparing it with 10 other state-of-the-art methods. Extensive experiments with ablation studies demonstrate that BR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> Net consistently and significantly outperforms the competitors in terms of both the efficiency and accuracy.

Context perspective on University-Industry Collaboration processes: A systematic review of literature

Studies on University-Industry Collaboration (UIC) have mainly focused on processes at the individual and institutional levels. The result has been a proliferation of literature on aspects of UIC implementation processes often accounting for contextual differences. A survey of previous systematic reviews showed a gap in integration of knowledge on UIC implementation processes from a holistic and economic context perspective. This systematic review of the literature seeks to cover that gap by integrating the literature on UIC implementation processes from developed and developing countries contexts. In total 68 publications were reviewed and the data extracted were qualitatively analyzed using a grounded theory approach. Three major themes are distinguished: channels of interaction, UIC mechanisms, and barriers to UIC. The channels of interaction were often presented in categories. The most comprehensive were found to be bi-directional, traditional, commercial and service channels. It was found that commercial channels are ranked by both industry and academia as the least important and the least preferred by collaboration actors. The review discerned three major forms of UIC implementation processes: (1) educational collaboration, (2) academic entrepreneurship and (3) research related collaboration. Mechanisms of implementing these three forms of interaction vary, but continuous interactions are frequently proposed as the best method of knowledge transfer, contrasting with the traditional linear view of UIC processes. Regarding barriers to collaboration, five categories of barriers (misalignment barriers; motivation related barriers; capability related barriers; governance-related barriers and contextual barriers) are identified. The review indicated also that there is still a research coverage gap in developing countries compared to developed countries, and that the educational collaboration form is somehow neglected. It is therefore recommended to use an action research approach to advance research in developing countries and to provide extra attention to educational collaboration mechanisms since this form is among the preferred means of UIC.

A Bitcoin payment network with reduced transaction fees and confirmation times

The high transaction fees and confirmation times made Bitcoin unfeasible for many applications when the payments are in small amounts and require instant approval. As a result, many other cryptocurrencies were introduced for addressing these issues, but the Bitcoin network is still the most widely used payment system. Without doubt, to benefit from its network of users, there is a need for novel solutions that can successfully address the problems about high transaction fees and transaction verification times. Recently, payment network ideas have been introduced including the Lightning Network (LN) which exploits off-chain bidirectional payment channels between parties. As off-chain links can be configured to perform aggregated transactions at certain intervals without writing to blockchain, this would not only reduce the transaction fees but also decrease the verification times significantly. Nevertheless, LN still deploys relay nodes which charge fees and its growth leads certain nodes to become monopolies which defeat the very purpose of decentralization. Despite the thought that LN will provide a “scale-free network mechanism” along with high decentralization, how to form such a network among multiple parties is never studied before. Therefore, in this paper, by exploiting the LN, we offer to form a purely decentralized payment network which will allow Bitcoin to handle a lot of transactions with enough capacity. The idea is to form a network of retailers (i.e., nodes) which do business with Bitcoin by connecting them through off-chain links (i.e., payment channels) based on the business needs. The problem is initially modeled as a network optimization but since scalability would be a concern the next steps follow a heuristic approach where certain links are pruned to force evenly distributed payment flows while minimizing the total investments made to create initial off-chain links. The evaluations demonstrate the extent of scalability of the network along with the trade-offs between the distribution of flows and the initial flow capacities of the nodes.

双向大气信道激光传输的信道互易性研究

双向大气信道激光传输的信道互易性研究

Antenna Correlation Under Geometry-Based Stochastic Channel Models

Antenna correlation is an important measure for designing multiple-input–multiple-output (MIMO) antenna systems. A lower antenna correlation indicates a better MIMO performance that can be achieved with the underlying antenna systems. In the antenna design community, it is very common to evaluate the antenna correlation with isotropic or nonisotropic (e.g., Gaussian-distributed) angular power spectrum (APS) as baselines. On the other hand, antenna correlation can also be evaluated via channel transfer function (CTF) under the given propagation channel, e.g., drawn from the bidirectional geometry-based stochastic channel model. In this letter, the analytic forms for the antenna correlation based on the APS and the CTF are derived, respectively, with their similarities and differences explained. Moreover, a numerical example is also given with a standard channel model to support our findings.

Remote Monitoring and Management of High-Risk Patients Being Started on Antineoplastic Treatment

Background Suboptimal management of cancer-related symptoms can lead to potentially preventable emergency department visits. Early detection and management of these symptoms leads to improved patient outcomes. The goal of this program is to capture symptom data on a daily cadence from patients beginning started on antineoplastic treatment and make these data available to staff who would intervene with the aim of mitigating symptom escalation. The aims of this pilot were patient acceptance of automated questionnaires, use of data by clinical staff, and integration of digital tools into workflows. Objective The objective was development and initial evaluation of a digitally enabled program to monitor and manage symptoms of cancer patients being started on treatment with antineoplastic drugs. Methods Memorial Sloan Kettering Cancer Center (MSKCC) patients being started on antineoplastic treatment were eligible for inclusion. The technology supporting the program included: (i) a predictive model identifying patients at high risk for emergency department visit in the next 6 months, (ii) a patient portal enabling symptom questionnaires to be sent to enrolled patients, (iii) an internally developed application that allows staff to review and trend symptom data, (iv) “alerts” for concerning symptoms that are sent to a dedicated team of oncology registered nurses and nurse practitioners, and (v) a secure messaging platform for communication between staff and patients. The predictive model runs nightly to identify eligible patients. Physicians review the risk information and decide whether to enroll each patient. Enrolled patients receive a daily patient-reported outcome questionnaire to capture symptoms. Alerts are generated based on the patient’s response to the symptom questions. The team reviews symptom data and interacts with the patient via phone, secure messaging, or televisits. The team collaborates with the primary oncology team as appropriate. Results The program went live in October 2018. Fifteen medical oncologists are participating in the pilot. As of June 21, 2019, 302 patients have been evaluated by the predictive model, of which 53 have been high risk and 249 have been low risk. Physicians have enrolled a total of 86 patients. Enrolled patients have completed 4198 out of 7287 symptom questionnaires, for a completion rate of 57.6%. Of the 4198 questionnaires, 1638 have generated a “red alert” (severe) symptom. Over 1200 secure messages have been exchanged between patients and staff. Lessons learned include: (i) patient acceptance of daily questionnaires has been high, (ii) the use of alerts assists the team in proactively managing participating patients, and (iii) patients and caregivers are reporting that they find the program valuable. The pilot demonstrated that daily symptom monitoring through a technology-enabled platform and a dedicated team is feasible and we are examining how the program might be scaled across our organization. Conclusions Through the use of automated symptom questionnaires and various bidirectional communication channels, remote monitoring and management of symptoms in cancer patients is feasible. This program enables providers at MSKCC to have visibility into patient symptomatology between visits and improves our understanding of the patient’s needs. The workflows of the staff monitoring the symptoms and how best to coordinate symptom management across multiple providers are areas of ongoing refinement.

Class-E Isolated DC–DC Converter With High-Rate and Cost-Effective Bidirectional Data Channel

In this article, we propose a methodology to create a through-the-barrier bidirectional communication channel between the two sides of an isolated class-E resonant dc-dc converter. Our methodology is innovative since communication occurs through the same transformer used for energy transfer, and relies on connecting and disconnecting an auxiliary capacitance. By doing so, the converter switches between a faster and a slower response without any change in the clock controlling its activity. With this, it is possible to achieve a very high-rate bidirectional communication (up to 1 b per switching clock period) with virtually no limitations in the converter power with respect to a standard class-E implementation. Measurements performed on a prototype operating at 1 MHz and capable of delivering up to 1.2 W is presented as a proof-of-concept.

Aquaporins mediated arsenite transport in plants: Molecular mechanisms and applications in crop improvement

Arsenic (As) is a carcinogen and it is ubiquitous in the environment. Its accumulation in plants can enter the food chain, thereby causing adverse impacts on human health. Based on studies using Xenopus oocytes, engineered microbes, and model plants, aquaporins play key roles in arsenite (AsIII) passage across the cell membrane. Herein, we summarized the roles of aquaporins in AsIII uptake, transport, and accumulation. The coupling action between polar-localized aquaporins and positive transporters probably explains the efficient As transport mediated by bi-directional channels. The expression of aquaporins is regulated at both transcriptional and post-transcriptional levels via microRNAs. However, in response to As, the proteins can be modified through phosphorylation and be degraded via the ubiquitin 26S proteasome system. Further, a proposed model comprising reactive oxygen species, Ca, Ca-dependent kinases, and transcriptional factors is constructed to reveal the signaling pathways and aquaporins’ responses to As in model plants. We also provided strategies to identify and investigate putative aquaporins in plants. Identification and modification of aquaporins’ residues critical for their substrate selectivity, and optimization of their expression pattern by employing appropriate promoters can be employed to reduce As accumulation in crops. Based on the characteristics of their functions and expression patterns, it is promising to employ aquaporins for genetic-engineering of crops to reduce As content and increase food safety.

Measurement-device-independent quantum key distribution coexisting with classical communication

The possibility for quantum and classical communication to coexist on the same fiber is important for deployment and widespread adoption of quantum key distribution (QKD) and, more generally, a future quantum internet. While coexistence has been demonstrated for different QKD implementations, a comprehensive investigation for measurement-device independent (MDI) QKD—a recently proposed QKD protocol that cannot be broken by quantum hacking that targets vulnerabilities of single-photon detectors—is still missing. Here we experimentally demonstrate that MDI-QKD can operate simultaneously with at least five 10 Gbps bidirectional classical communication channels operating at around 1550 nm wavelength and over 40 km of spooled fiber, and we project communication rates in excess of 10 THz when moving the quantum channel from the third to the second telecommunication window. The similarity of MDI-QKD with quantum repeaters suggests that classical and generalized quantum networks can co-exist on the same fiber infrastructure.

Aquaporin 4 Suppresses Neural Hyperactivity and Synaptic Fatigue and Fine-Tunes Neurotransmission to Regulate Visual Function in the Mouse Retina

The bidirectional water channel aquaporin 4 (AQP4) is abundantly expressed in the neural tissue. The advantages and disadvantages of AQP4 neural tissue deficiency under pathological conditions, such as inflammation, and relationship with neural diseases, such as Alzheimer’s disease, have been previously reported. However, the physiological functions of AQP4 are not fully understood. Here, we evaluated the role of AQP4 in the mouse retina using Aqp4 knockout (KO) mice. Aqp4 was expressed in Müller glial cells surrounding the synaptic area between photoreceptors and bipolar cells. Both scotopic and photopic electroretinograms showed hyperactive visual responses in KO mice, gradually progressing with age. Moreover, the amplitude reduction after frequent stimuli and synaptic fatigue was more severe in KO mice. Glutamine synthetase, glutamate aspartate transporter, synaptophysin, and the inward potassium channel Kir2.1, but not Kir4.1, were downregulated in KO retinas. KIR2.1 colocalized with AQP4 in Müller glial cells at the synaptic area, and its expression was affected by Aqp4 levels in primary Müller glial cell cultures. Intraocular injection of potassium in wild-type mice led to visual function hyperactivity, as observed in Aqp4 KO mice. Mitochondria molecules, such as Pgc1α and CoxIV, were downregulated, while apoptotic markers were upregulated in KO retinas. AQP4 may fine-tune synaptic activity, most likely by regulating potassium metabolism, at least in part, via collaborating with KIR2.1, and possibly indirectly regulating glutamate kinetics, to inhibit neural hyperactivity and synaptic fatigue which finally affect mitochondria and cause neurodegeneration.

Exploiting Bi-Directional Channel Reciprocity in Deep Learning for Low Rate Massive MIMO CSI Feedback

Channel state information (CSI) feedback is important for multiple-input multiple-output (MIMO) wireless systems to achieve their capacity gain in frequency division duplex mode. For massive MIMO systems, CSI feedback may consume too much bandwidth and degrade spectrum efficiency. This letter proposes a learning-based CSI feedback framework based on limited feedback and bi-directional reciprocal channel characteristics. The massive MIMO base station exploits the available uplink CSI to help recovering the unknown downlink CSI from low rate user feedback. We propose two deep learning architectures, DualNet-MAG and DualNet-ABS, to significantly reduce the CSI feedback payload based on the multipath reciprocity. DualNet-MAG and DualNet-ABS can exploit the bi-directional correlation of the magnitude and the absolute value of real/imaginary parts of the CSI coefficients, respectively. The experimental results demonstrate that our architectures bring an obvious improvement compared with the downlink-based architecture.

Stabilization of Two-Port Networked Systems With Simultaneous Uncertainties in Plant, Controller, and Communication Channels

In this paper, we study robust stabilization for the networked control system (NCS) over the communication channels described by cascaded two-port networks. Such an NCS involves simultaneous uncertainties in the plant, controller, and two-port communication channels. The cascaded two-port connections arise when signals in the NCS are transmitted through bidirectional communication channels separated by a sequence of relays. Distortions and interferences occurring in communications are taken into account. We consider ${\mathcal H}_{\infty }$ -norm bounded uncertainties in the transmission matrices of the two-port channels, and the gap-type uncertainties in the plant and controller models. A necessary and sufficient condition for the robust stability of the NCS is presented in the form of an “arcsine” inequality, which states that the NCS is stable whenever the uncertainties quantified by the aforementioned metrics are well bounded and satisfy the “arcsine” inequality. A stability margin related to the Gang of Four transfer matrix is obtained, based on which the controller synthesis problem can be solved through a special ${\mathcal H}_{\infty }$ optimization with favorable properties. Furthermore, a generalized stability condition is studied in terms of frequency-wise bounded uncertainties, and the corresponding controller synthesis problem is proposed and solved.

The climate of the past millennium and online public engagement in a scientific debate

AbstractAfter the publication in 1999 of a reconstruction of the Northern Hemisphere temperature popularly known as “the hockey‐stick,” climate scientists and Internet bloggers engaged in a heated and often stalemated public debate on the validity of paleoclimate reconstructions and on their implications for the wider question of anthropogenic climate change. The Internet emerged as an important medium for channeling the direct participation of the public almost at the same level as the professional climate scientist. It also allowed dissemination of largely unfiltered information. I argue that, although paleoclimate research did benefit in some technical aspects, the public debate around the hockey‐stick focused on issues that were not scientifically central, like the existence of the Medieval Warm Period or the characterization of 1998 as the warmest year of the millennium. In contrast, much more relevant points, such as constraining the value of climate sensitivity using reconstructions of past climate, remained restricted within purely academic circles. The public resonance of the hockey‐stick debate was also clearly framed by the politicization of climate science and the impacts of the series of IPCC reports, in particular the Third Assessment Report, published in 2001. This resonance was amplified by the expanding use of the Internet. The Internet represented a new bidirectional channel through which the public and academia could interact to achieve a transparent, democratic, and participative evaluation of science. I argue that, although we could have hoped for a positive outcome of the hockey‐stick controversy, this opportunity for a new constructive public engagement in scientific debates was missed.This article is categorized under: Paleoclimates and Current Trends &gt; Paleoclimate Social Status of Climate Change Knowledge &gt; Sociology/Anthropology of Climate Knowledge

Dynamic setup of IPsec VPNs in service function chaining

This article describes a novel mechanism for the automated establishment of dynamic Virtual Private Networks (VPN) in the application domain of Network Function Virtualization (NFV). Each hop in an NFV Service Function Chain (SFC) lacks the capability of per-flow encryption, that makes the traffic flow in federated NFV environments vulnerable for eavesdropping. Due to the possible lack of bidirectional data plane communication channels between VNFs in an SFC, the Internet Security Key Exchange protocol (IPsec-IKE) is not applicable inside a VNF. Hence, this article introduces an alternative to IPsec-IKE that is specifically designed for NFV environments. This component is named Software Defined Security Associations (SD-SA), which is shown through a proof of concept evaluation to perform better than IPsec-IKE with respect to bandwidth and resource consumption.

Implementation &amp; Performance Analysis of Bidirectional FSO channel in Hybrid TDM/WDM Gigabit Passive Optical Network

In this paper, experimental work is performed on hybrid TDM/WDM Gigabit Passive Optical Network by replacing the last mile optical fiber with Free Space Optical channel. A Hybrid GPON system is a more intelligent choice of today’s passive optical networks because it provides benefits of both TDM as well as WDM technologies at Giga b/s. And the use of Free Space Optical channel will bring the last mile network to its peak performance. This paper demonstrates the performance of hybrid TDM/WDM GPON system utilizing FSO channel in terms of Quality of factor and Bit error rate along with eye diagrams. This system is a full bidirectional system working on 2.5Gb/s downstream and 1.244Gb/s upstream transmission. The system is using varying lengths of FSO channel to analyze the GPON network performance. The simulation results using Optisystem v.15 verify the fully functional bidirectional transmission of FSO link between OLT and ONU and achieve BER of the order of 10–16 and 10–12 at a distance of 100 m for both upstream and downstream respectively.

Sulfur-Doped Anatase TiO2 as an Anode for High-Performance Sodium-Ion Batteries

Sulfur-doped anatase TiO2 was prepared through a calcination conversion route for the first time. The grain size of TiO2 with S-doping obviously decreased after S-doping, manifesting that the introduction of S species could inhibit the crystal growth. Applied as an anode material for sodium-ion batteries, this material exhibited an impressive specific capacity of 174.4 mA h g–1 at a high current density of 10 C after 10 000 cycles. The remarkable performance results from the unique crystal structure of anatase TiO2 with bidirectional pore channels for sodium-ion intercalation, and S-doped TiO2 could increase the electronic conductivity, as well as enlarge the channel structure. Furthermore, density functional theory calculations manifested that the S-doping increases the volume of the lattice slightly, leading to the ease of insertion for sodium ions into anatase TiO2 and a reduced band gap with higher electronic conductivity. Therefore, S-doped TiO2 showed high reversible capacities and excellent long-te...

Open-Source Hardware Platforms for Smart Converters with Cloud Connectivity

This paper presents the design and hardware implementation of open-source hardware dedicated to smart converter systems development. Smart converters are simple or interleaved converters. They are equipped with controllers that are able to online impedance match for the maximum power transfer. These conversion systems are particularly feasible for photovoltaic and all renewable energies systems working in continuous changing operating conditions. Smart converters represent promising solutions in recent energetic scenarios, in fact their application is deepening and widening. In this context, the availability of a hardware platform could represent a useful tool. The platform was conceived and released as an open hardware instrument for academy and industry to benefit from the improvements brought by the researchers’ community. The usage of a novel, open-source platform would allow many developers to design smart converters, focusing on algorithms instead of electronics, which could result in a better overall development ecosystem and rapid growth in the number of smart converter applications. The platform itself is proposed as a benchmark in the development and testing of different maximum power point tracking algorithms. The designed system is capable of accurate code implementations, allowing the testing of different current and voltage-controlled algorithms for different renewable energies systems. The circuit features a bi-directional radio frequency communication channel that enables real-time reading of measurements and parameters, and remote modification of both algorithm types and settings. The proposed system was developed and successfully tested in laboratory with a solar module simulator and with real photovoltaic generators. Experimental results indicate state-of-art performances as a converter, while enhanced smart features pave the way to system-level management, real-time diagnostics, and on-the-flight parameters change. Furthermore, the deployment feasibility allows different combinations and arrangements of several energy sources, converters (both single and multi-converters), and modulation strategies. To our knowledge, this project remains the only open-source hardware smart converter platform used for educational, research, and industrial purposes so far.

Circulator-free on-chip bidirectional four-wave mixing.

On-chip bidirectional four-wave mixing (FWM), which may meet the rapidly increasing demands on integration level and system versatility, has never been implemented for the lack of competent on-chip optical circulators that are indispensable for separating the bidirectional channels. In this scenario, we first propose and demonstrate a circulator-free scheme that fully utilizes the inherent clockwise and counter-clockwise transmission natural of an add-drop microring resonator to implement on-chip bidirectional FWM. It should be noted that the proposed scheme additionally provides a universal solution for multichannel nonlinear operations and the related applications, with the advantages of compact structure and low crosstalk. The implementation for multimode channels is investigated for demonstration, as the mode division multiplexing technique is of particular interest in integrated optoelectronics and the resonance-enhanced nonlinear structure with superior dimension compared to straight waveguides has never been implemented for a multimode case. The experimental results exhibit that the FWM efficiencies of the two-mode channels are -26.78 and -28.69 dB, respectively, and the crosstalk is lower than -35 dB.