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Abstract Enantioselectivity of helical aggregation is conventionally directed either by its homochiral ingredients or by introduction of chiral catalysis. The fundamental question, then, is whether helical aggregation that consists only of achiral components can obtain enantioselectivity in the absence of chiral catalysis. Here, by exploiting enantiospecific interaction due to chiral-induced spin selectivity (CISS) that has been known to work to enantio-separate a racemic mixture of chiral molecules, we demonstrate the enantioselectivity in the assembly of mesoscale helical supramolecules consisting of achiral cobalt phthalocyanines. The helical nature in our supramolecules is revealed to be mesoscopically incorporated by dislocation-induced discretized twists, unlike the case of chiral molecules whose chirality are determined microscopically by chemical bond. The relevance of CISS effect in the discretized helical supramolecules is further confirmed by the appearance of spin-polarized current through the system. These observations mean that the application of CISS-based enantioselectivity is no longer limited to systems with microscopic chirality but is expanded to the one with mesoscopic chirality.

Abstract Patients with severe acute liver injury (SLI) usually recover spontaneously. However, some SLI patients progress to acute liver failure with varying degrees of hepatic encephalopathy. Acute liver failure is associated with high mortality and can be substantially reduced by liver transplantation. Therefore, distinguishing SLI patients who might progress to acute liver failure and are at a risk of death is important when evaluating patients needing liver transplantation. The present study aimed to determine whether technetium-99m-diethylenetriaminepentaacetic acid galactosyl human serum albumin (Tc-99m GSA) scintigraphy can predict the prognosis of patients with SLI. This prospective observational study included 69 SLI patients. The accuracy of Tc-99m GSA for predicting death or liver transplantation for 6 months was assessed. Between the two groups of patients stratified based on the cut-off values from the receiver operating characteristic curves, 6-month transplant-free survival was compared. Sixteen (23.2%) patients died or underwent liver transplantation from admission (poor outcome). The hepatic accumulation index was calculated by dividing the radioactivity of the liver region of interest by that of the liver-plus-heart region of interest at 15 min (i.e., LHL15). The LHL15 in the 16 patients (0.686) was significantly lower than that in survivors (0.836; P

The threat of terrorism has spread all over the world, and the situation has become grave. Suspicious object detection in the Internet of Things (IoT) is an effective way to respond to global terrorist attacks. The traditional solution requires performing security checks one by one at the entrance of each gate, resulting in bottlenecks and crowding. In the IoT paradigm, it is necessary to be able to perform suspicious object detection on moving people. Artificial intelligence (AI) and millimeter-wave imaging are advanced technologies in the global security field. However, suspicious object detection for moving persons in the IoT, which requires the integration of many different imaging technologies, is still a challenge in both academia and industry. Furthermore, increasing the recognition rate of suspicious objects and controlling network congestion are two main issues for such a suspicious object detection system. In this paper, an AI-based W-band suspicious object detection system for moving persons in the IoT paradigm is designed and implemented. In this system, we establish a suspicious object database to support AI technology for improving the probability of identifying suspicious objects. Moreover, we propose an efficient transmission mechanism to reduce system network congestion since a massive amount of data will be generated by 4K cameras during real-time monitoring. The evaluation results indicate that the advantages and efficiency of the proposed scheme are significant.

As an extension of the Internet of Things (IoT), the Internet of Health Things (IoHT) plays an important role in the remote exchange of data of different physical processes such as patient monitoring, treatment progress, observation, and consultation. In IoHT, connectivity, integration, computation, and interoperability are enabled through various sensors, actuators, and controllers, thereby providing seamless connectivity with efficient utilization of resources. With advances in telemedicine, telesurgery, and other healthcare applications, streaming has become an essential part of IoHT. The data traffic in IoHT applications, such as interactive multimedia streaming, real-time image processing, traffic generated from faulty sensors and vital signs, can tolerate packet loss but has stringent delay requirements. On the other hand, video streaming applications cannot tolerate jitter. Similarly, the low-power devices are sensitive to packet loss and the periodic physiological traffic of medical traffic can tolerate delay or jitter, but not packet loss. Routing data in different IoHT applications has varying quality-of-service (QoS) requirements in terms of delay, packet loss, jitter, and throughput.

In fifth-generation wireless communications, data transmission is challenging due to the occurrence of burst errors and packet losses that are caused by multipath fading in multipath transmissions. To acquire more efficient and reliable data transmissions and to mitigate the transmission medium degradation in the 5G networks, it is important to study the error patterns or burst the error sequences that can provide insights into the behavior of 5G wireless data transmissions. In this paper, a two-state Markov-based 5G error model is investigated and developed to model the statistical characteristics of the underlying error process in the 5G network. The underlying 5G error process was obtained from our 5G wireless simulation, which was implemented based on three different kinds of modulation methods, including QPSK, 16QAM, and 64QAM, and was employed using the LDPC and TURBO coding methods. By comparing the burst or gap error statistics of the reference error sequences from the 5G wireless simulations and those of the generated error sequences from the two-state Markov error model, we show that the error behaviors of the coded OFDM 5G simulations can be adequately modeled by using the two-state Markov error model. Our proposed two-state Markov-based wireless error model can help to provide a more thorough understanding of the error process in 5G wireless communications and to evaluate the error control strategies with less computational complexity and shorter simulation times.

Information-centric networking (ICN) is a new approach to networking contents rather than devices that hold the contents. It has recently attracted much attention of network research and standardization communities. National and multi-national funded research projects have progressed worldwide. International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) started ICN standardization activities in 2012. In parallel, the standards-oriented research cooperation is progressing in the Information-Centric Networking Research Group (ICNRG) of the Internet Research Task Force (IRTF). All these global efforts have been collectively advancing the novel network architecture of ICN. However, there are very few surveys and discussions on the detailed ICN standardization status. To update the reader with information about the ICN research and standardization related activities, this paper starts with the history of global activities on ICN from 2010, giving references to various projects. It then describes the recent progress in the standardization of ICN component technologies in ITU-T and various documents produced by ICNRG. Lastly, it discusses the future directions for progressing ICN.

Information-Centric Networking (ICN) was born in an era that more and more users are shifting their interests to the content itself rather than the location where contents are stored. This paradigm shift in the usage patterns of the Internet, along with the urgent needs for content naming, pervasive caching, better security, and mobility support, has prompted researchers to consider a radical change to the Internet architecture. However, ICN is still in its infancy and development stage, and many issues still exist and need to be addressed. The common ICN architecture is lacking the host-centric communication ability and difficult to provide seamless mobility in current solutions. To solve this problem, our team had proposed the Named-Node Networking (3N) concept, which not only naming the content but also naming the node and it proved to have better performance of providing seamless mobility in the simulation. However, the previous contributions were limited in the 3N namespace for seamless mobility support in both producer and consumer. In this paper, we have proposed a 3N system which includes 3N naming, data delivery, mobility support, and data security. Moreover, we have created a 3N-based real-time video streaming system to evaluate data delivery performance and mobility handoff performance. The evaluation result proofs that our system performs better than TCP video streaming in a multi-client situation and a WiFi-based handoff was demonstrated.

The development of an energy storage system with abundant elements is a key challenge for a sustainable society, and the interest of Na intercalation chemistry is extending throughout the research community. Herein, the impact of Ti integration into NaMnO2 in a binary system of x NaMnO2–(1–x) TiO2 (0.5≤x≤1) is systematically examined for rechargeable Na battery applications. Stoichiometric NaMnO2, which is classified as an in-plane distorted O′3-type layered structure, delivers a large initial discharge capacity of approximately 200 mAh g-1, but insufficient capacity retention is observed, most probably associated with dissolution of Mn ions on electrochemical cycles. Ti-substituted samples show highly improved electrode performance as electrode materials. However, the appearance of a sodium-deficient phase, Na4Mn4Ti5O18 with a tunnel-type structure, is observed for Ti-rich phases. Among the samples in this binary system, Na0.8Mn0.8Ti0.2O2 (x=0.8), which is a mixture of a partially Ti-substituted O′3-type layered oxide (Na0.88Mn0.88Ti0.12O2) and tunnel-type Na4Mn4Ti5O18 as a minor phase elucidated by Rietveld analysis on both neutron and X-ray diffraction patterns, shows good electrode performance on the basis of energy density and cyclability. Both phases are electrochemically active as evidenced by in situ X-ray diffraction study, and the improvement of reversibility originates from the suppression of Mn dissolution on electrochemical cycles. From these results, the feasibility of Mn-based electrode materials for high-energy rechargeable Na batteries made from only abundant elements is discussed in detail.

This research proposes a novel wireless information-centric networking (ICN) architecture, namely, Context-Aware Green ICN Model (CAGIM), which can adapt the power consumption of network nodes to optimized values according to the associated link utilization. The power adaption in ICN nodes is conducted through dynamically adjusting the link-rate corresponding to content popularity and traffic load to reduce wasteful energy consumption. Moreover, we propose a smart popularity-based caching strategy, called distinguished caching scheme (DCS), with the introduction of hot and cold-caching partitions of ICN node's cache storage for popular and non-popular content objects, respectively. DCS improves the content diversity of the cache storage by adjusting, for each content, the number of chunks to be cached at ICN nodes based on its type and popularity level. DCS thus can further decrease the network system power consumption, thanks to its improved cache hit that reduces network traffic load. Toward the goal of realizing a context-aware green wireless network system with efficient content delivery, we also design a WiFi Direct based scheme as an alternative approach to minimize power consumption and latency by sharing essential/important content objects via direct communications with power-saving mechanisms in the case that wireless local area network connections are not available. The evaluation results show that CAGIM can improve network efficiency by reducing both hop-count and power consumption considerably compared with existing wireless network systems with different well-known caching schemes. This proposal enables a flexible and efficient content delivery mechanism for future networks with various real-life scenarios, like Green building, Green company, and Green campus content accesses.

In this paper, we introduce a key technology, polarization modulation (PM), which should be taken into account when standardizing outdoor optical wireless communications (OWC), also known as free-space optical communications (FSO). We analyze the distortion of the polarization state when a laser beam propagates through the atmospheric channel. The floating range of the optical polarization was estimated and the necessity of researching the proposed technology was discussed. Moreover, we conducted a comparison between the PM-based FSO system and intensity modulation-based FSO system. The conclusions will be helpful in establishing the FSO standard architectures.

A method for estimating Doppler velocities using ultra-wideband radar data is presented. Unlike conventional time-frequency analysis, the proposed method can directly obtain Doppler velocities without searching for peaks in a spectrum. By exploiting closed-form solutions for the Doppler velocities, it avoids the trade-off between time and frequency resolution, thus maintaining high time resolution. Both simulations and measurements are used to evaluate the proposed method versus conventional techniques.

We studied the ferrimagnet La_{5}Mo_{4}O_{16} with Mo ions on quasisquare lattices both experimentally and theoretically. We found that in addition to the antiferromagnetic ordering at T_{N}=200 K, a magnetic phase transition into a ferrimagnetic phase occurs at T_{s1}=60 K, which is caused by the orbital ordering of the Mo 4d states. We also found that the relatively small size of ferrimagnetic domains despite the large Ising anisotropy of the Mo spins are formed below T_{s1}, which are responsible for the relaxation behavior and the memory effect in the magnetization. Nonvolatile positive magnetoresistance observed in this compound below T_{s1} can be attributed to the fact that such magnetic domains and the electrical conduction along the domain walls disappear with the applied magnetic field.

In recent years, train passengers have been transferring increasing amounts of data using mobile devices. Wireless networks with mobile relay nodes support broadband wireless communications for passengers of such vehicles using backhaul links. However, the mobility management entity reuses the handover of existing user equipment, resulting in the handover of the Long-Term Evolution network being unsuitable for user equipment within the cabins of vehicles traveling at high speed. In this paper, we propose a self-optimizing handover hysteresis scheme with dual mobile relay nodes for wireless networks in high-speed mobile environments. The proposed mechanism tunes the hysteresis and cell individual offset handover parameters based on the velocity of the vehicle and the handover performance indicator, which affects the handover triggering decision and performance. The results of simulations conducted in which the performance of the proposed scheme was compared to that of an existing scheme show that the proposed scheme can reduce the number of radio link failures and service interruptions during handover procedures.

This paper proposes a theoretical study to characterize the transmission of optical code division multiple access (CDMA) systems deploying polarization shift keying (PolSK) over a free space optical (FSO) link under the impact of atmospheric turbulence. In our analysis, a novel transceiver architecture for atmospheric OCDMA FSO systems based on polarization modulation with direct detection is proposed and discussed. A detailed analytical model for PolSK-OCDMA systems over a turbulent FSO link is provided. Further, we derive a closed-form bit error ratio (BER) and outage probability expressions, taking into account the multiple-access interference (MAI), optical noise and the atmospheric turbulence effect on the FSO link modeled by the Gamma-Gamma distribution. Finally, the results of this study show the most significant parameters that degrade the transmission performance of the PolSK-OCDMA signal over FSO links and indicate that the proposed approach offers improved bit error ratio (BER) performances compared to the on-off-keying (OOK) modulation scheme in the presence of turbulence.

By considering the definitions and properties from the field of linguistics regarding place specification, a questionnaire that can be used to improve naming in networks is obtained. The questionnaire helps introduce the idea of place specification from linguistics and the concept of metric spaces into network naming schemes. The questionnaire results are used to improve the basic Information-Centric Networking (ICN) architecture’s notoriously lax network naming structure. The improvements are realized by leveraging components from the Named-Node Network Architecture, a minor ICN design, to supply the resulting network architecture with the properties the questionnaire highlights. Evaluation results from experiments demonstrate that modifying the network architecture so that the proposed questionnaire is satisfied results in achieving high mobility performance. Specifically, the proposed system can obtain mean application goodput at above 88 % of the ideal result, with a delay below 0.104 s and with the network time-out Interest ratio below 0.082 for the proposed single mobile push producer, single mobile consumer scenario, even when the nodes reach the maximum tested speed of 14 m/s.

Single-sideband (SSB) modulation through Hilbert transformation has successfully transmitted data using only half the bandwidth of the traditional scheme for the same amount of contained information. Toward this end, the four single-sideband (4-SSB) approach for high order modulation is a promising approach for the next-generation communications by applying soft-input soft-output (SISO) equalizer algorithms over orthogonal frequency division multiplexing (OFDM). However, OFDM is challenging for realizing the feasible 5G communications, compared to the emerging techniques, e.g., non-orthogonal multiple access (NOMA), orthogonal multiple access (OMA) or multiple-input multiple-output (MIMO). Since the 4-SSB is an orthogonal modulation which was successfully applied over the traditional OFDM, in this article, we propose a novel 4-SSB modulation scheme over OFDM Guard Interval (GI) and massive MIMO. Besides the carrier signal, from the receiver side, we also apply the shadow equalizer algorithm in the uncoded and coded environment using turbo codes to achieve the 4-SSB with high efficiency from low complexity and energy consumption for 5G. The evaluation results validate that our system consumes lower energy due to low complexity gained from same number of iterations without the heavy decoding as of the 4-SSB SISO based on the turbo equalizer. In addition, the 4-SSB over the OFDM GI achieves the best performance among the relevant approaches conducted in 4-SSB. The proposal then acts as a practical communication system designed to solve the inter-symbol interference (ISI) induced by additional Hilbert transform in the wireless environment toward fifth generation (5G), given that turbo code is considered as a potential channel coding scheme for 5G radio specification.

Cellular vehicle-to-everything (C-V2X) communication facilitates the improved safety, comfort, and efficiency of vehicles and mobility by exchanging information between vehicles and other entities. In general, only the macrocell or only the femtocell is the communication infrastructure for C-V2X. Currently, a macro-femtocell network is used as the new C-V2X networking architecture. However, there are two unresolved problems for C-V2X in macro-femtocell networks. Firstly, vehicle mobility requires the frequent switching of connections between different base stations; invalid switching results in worse communication quality. Secondly, unintelligent base station selections cause network congestion and network-load imbalance. To address the above challenges, this paper proposes a base station selection strategy based on a Markov decision policy for a vehicle in a macro-femtocell system. Firstly, we present a mechanism to predict received signal strength (RSS) for base station selection. Secondly, a comparing Markov decision policy algorithm is presented in C-V2X. To the best of our knowledge, this is the first attempt to achieve predicted RSS based on a Markov decision policy in C-V2X technology. To validate the proposed mechanism, we simulated the traditional base station selection and our proposal when the vehicle moved at different speeds. This demonstrates that the effectiveness of a traditional base station selection policy is obvious only at high speeds, and this weakness can be resolved by our proposal. Then, we compare our solution with the traditional base station selection policy. The simulation results show that our solution is effective at switching connections between base stations, and it can effectively prevent the overloading of network resources.

This article proposes a novel chunk-based caching scheme known as the Progressive Popularity-Aware Caching Scheme (PPCS) to improve content availability and eliminate the cache redundancy issue of Information-Centric Networking (ICN). Particularly, the proposal considers both entire-object caching and partial-progressive caching for popular and non-popular content objects, respectively. In the case that the content is not popular enough, PPCS first caches initial chunks of the content at the edge node and then progressively continues caching subsequent chunks at upstream Content Nodes (CNs) along the delivery path over time, according to the content popularity and each CN position. Therefore, PPCS efficiently avoids wasting cache space for storing on-path content duplicates and improves cache diversity by allowing no more than one replica of a specified content to be cached. To enable a complete ICN caching solution for communication networks, we also propose an autonomous replacement policy to optimize the cache utilization by maximizing the utility of each CN from caching content items. By simulation, we show that PPCS, utilizing edge-computing for the joint optimization of caching decision and replacement policies, considerably outperforms relevant existing ICN caching strategies in terms of latency (number of hops), cache redundancy, and content availability (hit rate), especially when the CN’s cache size is small.

Range-free localization algorithm continues to be an important and challenging research topic in anisotropic Wireless Sensor Networks (WSNs). Designing range-free localization algorithms without considering obstacles or holes inside the network area does not reflect the real world conditions. In this paper, we have proposed Detour Path Angular Information (DPAI) based sensor localization algorithm to accurately estimate the distance between an anchor node and a sensor node. We utilized the Euclidean distance and transmission path distance among anchor nodes to calculate the angle of the transmission path between them one by one. Then the estimated hop distance is adjusted by the angle between the anchor pairs. Based on the angle of the detoured path (which is the key factor for accuracy), our algorithm determines whether the path is straight or detoured by anisotropic factors. Our proposed algorithm does not require any global knowledge of network topology to tolerate the network anisotropy nor require high sensor node density for satisfactory localization accuracy. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis. DPAI achieved average sensor localization accuracy better than 0.3r in isotropic network and 0.35r in anisotropic network when the sensor density is above 8.

Many sensor applications are aimed for mobile objects, where conventional routing approaches of data delivery might fail. Such applications are habitat monitoring, human probes or vehicular sensing systems. This paper targets such applications and proposes lightweight proactive distributed data collection scheme for Mobile Sensor Networks (MSN) based on the theory of thermal fields. By proper mapping, we create distribution function which allows considering characteristics of a sensor node. We show the functionality of our proposed forwarding method when adapted to the energy of sensor node. We also propose enhancement in order to maximize lifetime of the sensor nodes. We thoroughly evaluate proposed solution and discuss the tradeoffs.

Information-Centric Networking (ICN) is a new Internet architecture design, which is considered as the global-scale Future Internet (FI) paradigm. Though ICN offers considerable benefits over the existing IP-based Internet architecture, its practical deployment in real life still has many challenges, especially in the case of high congestion and limited power in a sensor enabled-network for the Internet of Things (IoT) era. In this paper, we propose a smart congestion control mechanism to diminish the network congestion rate, reduce sensor power consumptions, and enhance the network performance of ICN at the same time to realize a complete green and efficient ICN-based sensor networking model. The proposed network system uses the chunk-by-chunk aggregated packets according to the content popularity to diminish the number of exchanged packets needed for data transmission. We also design the sensor power-based cache management strategy, and an adaptive Markov-based sensor scheduling policy with selective sensing algorithm to further maximize power savings for the sensors. The evaluation results using ndnSIM (a widely-used ICN simulator) show that the proposed model can provide higher network performance efficiency with lower energy consumption for the future Internet by achieving higher throughput with higher cache hit rate and lower Interest packet drop rate as we increase the number of IoT sensors in ICN.

This research proposes an intelligent classification framework for quality of service (QoS) performance improvement in information-centric networking (ICN). The proposal works towards keyword classification techniques to obtain the most valuable information via suitable content prefixes in ICN. In this study, we have achieved the intelligent function using Artificial Intelligence (AI) implementation. Particularly, to find the most suitable and promising intelligent approach for maintaining QoS matrices, we have evaluated various AI algorithms, including evolutionary algorithms (EA), swarm intelligence (SI), and machine learning (ML) by using the cost function to assess their classification performances. With the goal of enabling a complete ICN prefix classification solution, we also propose a hybrid implementation to optimize classification performances by integration of relevant AI algorithms. This hybrid mechanism searches for a final minimum structure to prevent the local optima from happening. By simulation, the evaluation results show that the proposal outperforms EA and ML in terms of network resource utilization and response delay for QoS performance optimization.

The existing IEEE and 3GPP standards have laid the foundation for integrating cellular and WiFi network to deliver a seamless experience for the end-users when roaming across multiple access networks. However, in recent studies, the issue of making roaming decision and intelligently selecting the most preferable Point of Service to optimize network resource and improve end user’s experience has not been considered properly. In this paper, we propose a novel cellular and WiFi roaming decision and AP selection scheme based on state of the art, 3GPP TS24.312 and IEEE 802.11u, k standards. Our proposed scheme assists the mobile nodes to decide the right timing to make roaming decision and select preferable point of service based on the operator’s policies and real-time network condition. We also introduce our simulation model of a heterogeneous network with cellular and WiFi interworking as well as 3GPP ANDSF, TS24.312. It is a complete end-to-end system model from application to physical layer with considering user’s mobility and realistic traffic model. The proposed scheme outperformed the conventional WiFi selection scheme in terms of dynamically steering mobile node’s data traffic from macrocell to available Access Points. The proposed scheme increased the utilization and balanced the traffic load of access points and improved user’s experienced throughput.

Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.

In this paper, we propose an average connectivity degree cluster (ACDC) scheme gossip algorithm to improve the convergence speed and the accuracy of the consensus, when a common decision is needed for a certain phenomenon in a distributed network. We analyze the effects of the initial value, the network topology (regular and irregular), and the number of clusters on the algorithm convergence rate as well as the accuracy of the value when reaching consensus. A utility function is developed based on two parameters, iteration and relative error, to help the network designers make an optimal decision based on their requirements. An irregular sensor model which is based on the degree of irregular (DOI) radius is introduced to evaluate the robustness of the algorithm. The simulation results demonstrate that for any initial value and network topology, the proposed ACDC gossip algorithm can yield results that are 50% closer to the real average value than the referenced standard gossip and grid cluster gossip algorithms. With different DOI values, our ACDC gossip algorithm can still reach lower relative error compared with other gossip algorithms, which demonstrates that our algorithm is robust enough to be executed in the network.