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Improper use of conventional plastics poses challenges for sustainable energy and environmental protection. Algal derivatives have been considered as a potential renewable biomass source for bioplastic production. Algae derivatives include a multitude of valuable substances, especially starch from microalgae, short-chain length polyhydroxyalkanoates (PHAs) from cyanobacteria, polysaccharides from marine and freshwater macroalgae. The algae derivatives have the potential to be used as key ingredients for bioplastic production, such as starch and PHAs or only as an additive such as sulfated polysaccharides. The presence of distinctive functional groups in algae, such as carboxyl, hydroxyl, and sulfate, can be manipulated or tailored to provide desirable bioplastic quality, especially for food, pharmaceutical, and medical packaging. Standardizing strains, growing conditions, harvesting and extracting algae in an environmentally friendly manner would be a promising strategy for pollution control and bioplastic production.

BACKGROUND: Low bone density (BMD) and fractures commonly affect women with premature ovarian insufficiency (POI). However, bone microarchitecture and body composition data are lacking. OBJECTIVE: To assess and characterise musculoskeletal phenotype and effects of oestrogen replacement therapy (ERT) in women with POI. METHOD: Cross-sectional and longitudinal studies of 60 normal karyotype women with POI, aged 20-40 years, from 2005-2018. Dual x-ray absorptiometry (DXA)-derived spinal (LS) and femoral neck (FN) BMD, trabecular bone score (TBS), appendicular lean mass (ALM), total fat mass (TFM), and fracture prevalence were compared with 60 age-, and BMI-matched population-based controls. Longitudinal changes in bone and body composition variables and ERT effects were analysed using linear mixed models over a median duration of 6 years. RESULTS: Women with POI were subdivided into spontaneous (s)-POI (n=25) and iatrogenic (i)-POI (n=35). Median(range) age of POI diagnosis was 34 (10-40) years with baseline DXA performed at median 1(0-13) year post-diagnosis. ERT was used by 82% women (similar for both POI groups). FN-BMD were lowest in s-POI (p<0.002). Low TBS was more common in s-POI [(44%), p=0.03], versus other groups. LS-BMD and ALM were lower in both s-POI and i-POI groups than controls (p<0.05). Fracture prevalence was not significantly different: 20% (s-POI), 17% (i-POI), and 8% (controls) (p=0.26). Longitudinal analysis of 23 POI women showed regular ERT was associated with ALM increment of 127.05 g/year (p<0.001) and protected against bone loss. However, ERT interruption was associated with annual reductions in FN BMD and TBS of 0.020g/cm2 and 0.0070 (p<0.05), respectively. CONCLUSION: Deficits in BMD, trabecular microarchitecture, and lean mass were present in women with POI. However, regular ERT protected against declines in bone variables, with an increase in ALM. Assessment of skeletal and muscle health, and advocating ERT adherence, is essential in POI

In this paper, we propose a novel and adaptive flow rule placement system based on deep reinforcement learning, namely DeepPlace, in Software-Defined Internet of Things (SDIoT) networks. DeepPlace can provide a fine-grained traffic analysis capability while assuring QoS of traffic flows and proactively avoiding the flow-table overflow issue in the data plane. Specifically, we first investigate the traffic forwarding process in an SDIoT network, i.e., routing and flow rule placement tasks. We design a cost function for the routing to set up traffic flow paths in the data plane. Next, we propose an adaptive flow rule placement approach to maximize the number of match-fields in a flow rule at SDN switches. To deal with the dynamics of IoT traffic flows, we model the system operation by using the Markov decision process (MDP) with a continuous action space and formulate its optimization problem. Subsequently, we develop a deep deterministic policy gradient-based algorithm to help the system obtain the optimal policy. The evaluation results demonstrate that DeepPlace can efficiently maintain a significant number of match-fields in a flow rule, i.e., approximately 86% of the maximum level, while minimizing the QoS violation ratio of traffic flows, i.e., 6.7%, in a highly dynamic traffic scenario, which outperforms three other existing solutions, i.e., FlowMan, FlowStat, and DeepMatch.

In this paper, we propose a dynamic cyber-attack reaction system based on Q-learning, namely CARS, to effectively defeat cyber-attacks in Software-Defined Networks (SDN). In particular, we first examine a cyber-attack reaction system that operates at the SDN control plane. Then, we propose a dynamic cyber-attack reaction solution to maximize the attack defense performance while minimizing the negative influence on benign traffic forwarding in the data plane. Next, we model the cyber-attack reaction system based on a Markov decision process (MDP) and formulate its optimization problem. Afterward, we develop a Q-learning based cyber-attack reaction control algorithm to solve the optimization problem, obtaining the optimal cyber-attack reaction policy. As our case study on denial-of-service (DoS) attacks, the obtained results verify that CARS can effectively prevent malicious packets from reaching the victim server in all DoS attacks, i.e., approximately 80% of abnormal packets are dropped. In addition, by implementing the optimal cyber-attack reaction policy, CARS can significantly reduce the ratio of QoS (Quality-of-Service) violated traffic flows compared to two existing solutions, i.e., GATE (by approx. 66%) and GTAC-IRS (by approx. 75%).

Vision Meets Drone: Multiple Object Tracking (VisDrone-MOT2021) challenge - the forth annual activity organized by the VisDrone team - focuses on benchmarking UAV MOT algorithms in realistic challenging environments. It is held in conjunction with ICCV 2021. VisDrone-MOT2021 contains 96 video sequences in total, including 56 sequences (~24K frames) for training, 7 sequences (~3K frames) for validation and 33 sequences (~13K frames) for testing. Bounding-box annotations for novel object categories are provided every frame and temporally consistent instance IDs are also given. Additionally, occlusion ratio and truncation ratio are provided as extra useful annotations. The results of eight state-of-the-art MOT algorithms are reported and discussed. We hope that our VisDrone-MOT2021 challenge will facilitate future research and applications in the field of UAV vision. The website of our challenge can be found at http://www.aiskyeye.com/.

This paper studies the uplink (UL) transmission of a cell-free massive multiple-input multiple-output (massive MIMO) system in which multiple base stations (or access points), each equipped with a multiple-antenna array and connected to a central processing unit (CPU) over a backhaul network, simultaneously serve multiple users in a cell-free service area. The paper focuses on the non-orthogonal multiple access (NOMA) approach for sharing pilot sequences among users. Unlike the conventional cell-free massive MIMO-NOMA systems in which the UL signals from different access points are equally combined over the backhaul network, this paper develops an optimal backhaul combining (OBC) method to maximize the UL signal-to-interference-plus-noise ratio (SINR). With the proposed OBC method, a closed-form SINR expression is derived under Rayleigh fading and used to formulate a max-min quality-of-service (QoS) power control problem to further enhance the system performance. Numerical results corroborate the analysis and demonstrate that the proposed optimal backhaul combining method clearly outperforms equal-gain combining.

This paper proposes a novel successive interference cancellation method to enhance the ergodic spectral efficiency of a cell-free massive multiple-input multiple-output (MIMO) system with non-orthogonal multiple-access (NOMA). Unlike the majority of existing research works on performance evaluation of NOMA, which assume perfect channel state information and perfect data detection for successive interference cancellation, we take into account the effect of practical (hence imperfect) successive interference cancellation (SIC). We show that the received signal at the backhaul network of a cell-free massive MIMO-NOMA system can be effectively treated as a signal received over an AWGN channel. As a result, a discrete joint distribution between the interfering signal and its detected version can be analytically found, from which an adaptive SIC scheme is proposed to improve performance of interference cancellation.

Providing ultra reliable and low-latency communication (URLLC) is considered one of the major challenges for wireless communication networks. This article considers a downlink URLLC system in which a base station (BS) serves multiple single-antenna users in the short blocklength regime. With the objective of maximizing the users' minimum rate, three different optimization problems are considered: (i) joint design of bandwidth and power allocation for the case of a single-antenna BS; (ii) beamforming design for the case of a multiple-antenna BS; and (iii) design of power allocation with regularized zero-forcing beamforming for the case of a multiple-antenna BS. In the short blocklength regime, the achievable rate is a complicated function of bandwidth and power allocation coefficients or beamforming vectors, which makes these max-min rate optimization problems challenging to solve. This work develops path-following algorithms, which generate a sequence of improved feasible points and converge at least to a locally optimal solution, to solve these three optimization problems. Performance of the proposed algorithms is analyzed through extensive simulations under various settings of transmit power budget, number of users, total bandwidth, transmission time, and number of transmit antennas at the BS. Simulation results clearly demonstrate the merits of the proposed algorithms.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

© 1972-2012 IEEE. Recent studies of single-cell two-user networks have shown that a higher network throughput is achieved by using a common message to be decoded by both users and conveying partial information for both users, rather than using the common message to convey the entire information for one of the two users. The latter is essentially the conventional non-orthogonal multiple access (NOMA), which performs better than orthogonal multiple access (OMA) only under users' dissimilar channel conditions. Unlike NOMA, the former performs consistently better than OMA. This paper generalizes such a signaling strategy to a general multi-cell multiuser network, which leads to a new NOMA approach (called n-NOMA) in which each pair of users decodes a message that conveys partial information for one of them only. Unlike the conventional NOMA, whose performance is dependent on the users' pairing strategy, the proposed n-NOMA consistently outperforms both NOMA and OMA schemes. Both proper and improper Gaussian signaling is considered for all the concerned schemes and it is shown that the latter is clearly more advantageous than the former.

© 2014 IEEE. This paper proposes and investigates an overlay spectrum sharing system in conjunction with the simultaneous wireless information and power transfer to enable communications for the Internet of Things (IoT) applications. Considered is a cooperative cognitive radio network, where two IoT devices (IoDs) exchange their information and also provide relay assistance to a pair of primary users (PUs). Different from most existing works, in this paper, both IoDs can harvest energy from the radio-frequency signals received from the PUs. By utilizing the harvested energy, they provide relay cooperation to PUs and realize their own communications. For harvesting energy, a time-switching-based approach is adopted at both IoDs. With the proposed scheme, one round of bidirectional information exchange for both primary and IoT systems is performed in four phases, i.e., one energy harvesting phase and three information processing phases. Both IoDs rely on the decode-and-forward operation to facilitate relaying, whereas the PUs employ selection combining technique. For investigating the performance of the considered network, this paper first provides exact expressions of user outage probability (OP) for the primary and IoT systems under Nakagami-m fading. Then, by utilizing the expressions of user OP, the system throughput and energy efficiency are quantified together with the average end-to-end transmission time. Numerical and simulation results are provided to give useful insights into the system behavior and to highlight the impact of various system/channel parameters.

© 2002-2012 IEEE. Physical layer security (PLS) aims to protect end users who are equipped with low-complexity receivers for which implementing cryptographic algorithms for security purposes is not practical. This article presents a different approach to PLS and suggests natural and simple ways to achieve security in wireless networks. A practical assumption on the availability of channel state information (CSI) is considered for eavesdroppers (EVs) at the transmitter. Moreover, there is no restriction on EVs' placement, and as such EVs could be in better channel conditions when they are closer to the transmitter. The article describes how the interference channels can be exploited to simultaneously reduce the interference for the users' received signals and amplify the interference at the EV's received signal. It is also shown that when considering communication with energy-constrained nodes, the heterogeneous nature of the transmitted signals is an asset and can be exploited to confuse the eavesdropper. This is because information and energy signals are transmitted over different fractions of a time slot, and the EV can be confused since it does not know the time-fraction when information signal or energy signal is transmitted. Finally, the article also suggests how we can achieve secure information transmission under poor scattering environments, such as unmanned-aerial-vehicle-enabled communications.

© 2007-2012 IEEE. Improper Gaussian signaling (IGS) helps to improve the throughput of a wireless communication network by taking advantage of the additional degrees of freedom in signal processing at the transmitter. This paper exploits IGS in a general multiuser multi-cell network, which is subject to both intra-cell and inter-cell interference. With IGS under orthogonal multiple access (OMA) or non-orthogonal multiple access (NOMA), designs of transmit beamforming to maximize the users' minimum throughput subject to transmit power constraints are addressed. Such designs are mathematically formulated as nonconvex optimization problems of structured matrix variables, which cannot be solved by popular techniques such as weighted minimum mean square error or convex relaxation. By exploiting the lowest computational complexity of 2× 2 linear matrix inequalities, lower concave approximations are developed for throughput functions, which are the main ingredients for devising efficient algorithms for finding solution of these difficult optimization problems. Numerical results obtained under practical scenarios reveal that there is an almost two-fold gain in the throughput by employing IGS instead of the conventional proper Gaussian signaling under both OMA and NOMA; and NOMA-IGS offers better throughput compared to that achieved by OMA-IGS.

© 2018 Elsevier Ltd Soil displacement induced when installing controlled modulus columns (CMC) as ground reinforcement could affect the columns installed close by. Realising numerical analyses may provide useful insights, this paper describes a numerical approach to investigate how groups of CMC installed in different sequences could affect columns installed previously. Coupled consolidation analyses in large strain mode and incorporating soil-CMC interaction were carried out using the three-dimensional finite difference software package FLAC3D. The CMCs were modelled using advanced non-linear Hoek-Brown material with a tensile yield criterion while soils with a typical profile were characterised using the modified Cam Clay and the elastic-perfectly plastic material with a Mohr-Coulomb yield criterion. Where possible, the predicted responses of ground surrounding the CMCs were compared to a number of existing analytical methods. Predictions revealed that lateral soil movement and soil heave near existing CMCs induced by installing new CMCs towards the existing CMCs were approximately 15% and 25% greater than corresponding predictions when a reverse installation sequence was adopted. The maximum excess pore water pressures, induced near existing columns due to installing new columns towards the existing ones, were almost twice more than those caused by the reverse sequence of installation. Moreover, the predicted bending moments generated in the existing columns induced by installing new columns towards the existing CMCs were almost 22% greater than the corresponding values when the reverse installation sequence was adopted. This shows the importance of selecting an appropriate installation sequence in the CMC construction process as well as considering the initial stress field and bending moments in the surrounding soil and CMCs, respectively when designing embankments on improved soft soils.

Atypical femoral fractures (AFFs) are a rare association of anti-resorptive therapy for osteoporosis. Limited evidence-based management guidelines on their optimal treatment exist, with observational studies suggesting a role for teriparatide (TPTD) in AFF healing. We report a case of a 65-year-old woman with postmenopausal osteoporosis who sustained an AFF following long-term bisphosphonate therapy, and who subsequently developed a new contralateral AFF after completion of TPTD therapy and initiation of strontium ranelate (SR) treatment. The sequence of events in this case report showed that TPTD and SR did not prevent the development of a new AFF, and questions the optimal treatment of these stress fractures.

© 1991-2012 IEEE. This paper considers the optimal design of training sequences for channel estimation in large-scale multiple-input multiple-output orthogonal frequency-division multiplexing systems. The application scenario of interest is when the number of transmit antennas for the downlink (or the number of receive antennas for the uplink) is large, but not large enough to benefit the asymptotical optimality of using equipower training sequences (e.g., due to practical constraints on deployment costs, space, and antenna size). Under the criterion of minimizing the mean square error of the channel estimate, the optimal design of training sequences for such systems poses a truly large-scale optimization problem, to which existing optimization solvers are not applicable. We develop a fast convex programming (FCP) procedure to find its global optimal solution. In each iteration of the proposed FCP procedure, a solution is found in a scalable and closed form. The singularity and ill-conditionedness of the channel correlation matrices are also exploited to improve the computation efficiency. Furthermore, we also examine the design of reduced-length training sequences and develop a successive quadratic programming procedure to find the solutions. Intensive simulation results are provided to illustrate the performance of our methods.

© 1972-2012 IEEE. It is known that superposition signaling in Gaussian interference networks is capable of improving the achievable rate region. However, the problem of maximizing the rate gain offered by superposition signaling is computationally prohibitive, even in the simplest case of two-user single-input single-output interference networks. This paper examines superposition signaling for the general multiple-input multiple-output broadcast Gaussian interference networks. The problem of maximizing either the sum rate or the minimal user's rate under superposition signaling and dirty paper coding is solved by a computationally efficient path-following procedure, which requires only a convex quadratic program for each iteration but ensures convergence at least to a locally optimal solution. Numerical results demonstrate the substantial performance advantage of the proposed approach.

© 2017 IEEE. Obtaining channel state information is very crucial for realizing high-performance high-rate wireless communications. For an orthogonal frequency-division multiplexing (OFDM) system operating in a high-mobility environment such as in high-speed trains, a sequence of pilot samples is inserted in each OFDM symbol to track the fast-varying channel responses. For such a high-mobility environment, the design of pilot sequence to minimize the mean squared error (MSE) of the channel estimate under a linear minimum mean squared error (LMMSE) estimator poses a difficult polynomial fractional optimization problem. In this paper, we develop a path-following optimization procedure, which improves the MSE in every iteration and quickly converges at least to its locally-optimal solution. Each iterative solution is given in a closed form with very low computational complexity. The developed path-following procedure can also be adapted to design pilot sequences for the least-square and maximum-likelihood estimators. Extensive simulation results demonstrate the effectiveness and superior performance of the proposed solutions and algorithms when compared to the state-of-The-Art algorithms in the literature.