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A joint optimization scheme of both time allocation and mode selection is proposed for defending smart jammer in internet of things (IoT). Specifically, we employ multiple modes to deal with the potential eavesdropping and jamming attacks in wireless sensor networks (WSN), respectively as wireless-powered relaying (WPR), ambient backscatter relaying (ABR), friendly jamming (FJ) modes. Assuming a specific frame structure, time allocation between energy harvesting and transmission duration is firstly optimized for three modes based on transmission and security data maximization. In addition, considering that a single mode may fail to guarantee the performance demand due to the uncertainty of network conditions and adversary attacks, mode selection is carried out for adapting characteristics of different modes. Moreover, according to the available knowledge of jamming detection, for enhancing the robustness in secure transmission, the process of mode selection is further divided into two phases. Specifically, game theory is also utilized to achieve the Nash equilibrium for mode selection. Finally, numerical results verify the effects and exhibit the advantages of the proposed scheme.

Frostbite in Southwestern China has been overlooked due to its low incidence, relatively mild temperature and lack of literature published before. However, it needs to be further studied for religious diversity and distinct geomorphology. In this article, we reported an 18-year-old Tibetan girl who suffered from blizzard attack during pilgrimage. Her feet and several fingers showed mummified gangrene upon physical examination with poor movement. She was diagnosed with 3rd to 4th degree of frostbite. The girl was given oral ibuprofen, debridement and other regular treatment daily, but she was eventually amputated due to insufficient thrombolytic management in primary hospital, delayed informing consent in the referral hospital and ethnic conflict between religion and guidelines. This case enriched the experience of managing complex frostbite in Tibetan population and alarms that efforts should be integrated to protect pilgrims and mountaineers in the Tibetan region.

In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple single-antenna source terminal (ST)-DT pairs in two-hop networks is investigated. Different from the previous studies on IRS that merely focused on tuning the reflection coefficient of all the reflection elements at IRS, in this paper, we consider the true reflection resource management. Specifically, the true reflection resource management can be realized via trigger module selection based on our proposed IRS architecture that all the reflection elements are partially controlled by multiple parallel switches of controller. As the number of reflection elements increases, the true reflection resource management will become urgently needed in this context, which is due to the non-ignorable energy consumption. Moreover, the proposed modular architecture of IRS is designed to make the reflection elements part independent and controllable. As such, our goal is to maximize the minimum signal-to-interference-plus-noise ratio (SINR) at DTs via a joint trigger module subset selection, transmit power allocation of STs, and the corresponding passive beamforming of the trigger modules, subject to per ST power budgets and module size constraint. Whereas this problem is NP-hard due to the module size constraint, to deal with it, we transform the hard module size constraint into the group sparse constraint by introducing the mixed row block norm, which yields a suitable semidefinite relaxation. Additionally, the parallel alternating direction method of multipliers (PADMM) is proposed to identify the trigger module subset, and then subsequently the transmit power allocation and passive beamforming can be obtained by solving the original minimum SINR maximization problem without the group sparse constraint via partial linearization for generalized fractional programs., Comment: Please feel free to contact us for questions or remarks

In the past years, network meta-analysis (NMA) has been widely used among clinicians, guideline makers, and health technology assessment agencies and has played an important role in clinical decision-making and guideline development. To inform further development of NMAs, we conducted a bibliometric analysis to assess the current status of published NMA methodological studies, summarized the methodological progress of seven types of NMAs, and discussed the current challenges of NMAs.

Digital signature is a major component of transactions on Blockchain platforms, especially in enterprise Blockchain platforms, where multiple signatures from a set of peers need to be produced to endorse a transaction. However, such process is often complex and time-consuming. Multi-signature, which can improve transaction efficiency by having a set of signers cooperate to produce a joint signature, has attracted extensive attentions. In this work, we propose two multi-signature schemes, GMS and AGMS, which are proved to be more secure and efficient than state-of-the-art multi-signature schemes. Besides, we implement the proposed schemes in a real Enterprise Blockchain platform, Fabric. Experiment results show that the proposed AGMS scheme helps achieve the goal of high transaction efficiency, low storage complexity, as well as high robustness against rogue-key attacks and $k$ -sum problem attacks.

Background Acute myocardial infarction (AMI) during pregnancy is rare, especially in twin pregnancy, and it can endanger the lives of the mother and children. Except for conventional cardiovascular risk factors, pregnancy and assisted reproduction can increase the risk of AMI during pregnancy. AMI develops secondary to different etiologies, such as coronary spasm and spontaneous coronary artery dissection. Case summary A 33-year-old woman, with twin pregnancy in the 31st week of gestation, presented to the hospital with intermittent chest tightness for 12 wk, aggravation for 1 wk, and chest pain for 4 h. Combined with the electrocardiogram and hypersensitive troponin results, she was diagnosed with acute ST-elevation myocardial infarction. Although the patient had no related medical history, she presented several risk factors, such as age greater than 30 years, assisted reproduction, and hyperlipidemia. After diagnosis, the patient received antiplatelet and anticoagulant treatment. Cesarean section and coronary angiography performed 7 d later showed stenosis and thrombus shadow of the right coronary artery. After receiving medication, the patient was in good condition. Conclusion This case suggests that, with the widespread use of assisted reproductive technology, more attention should be paid to perinatal healthcare, especially when chest pain occurs, to facilitate early diagnosis and intervention of AMI, and the etiology of AMI in pregnancy needs to be differentiated, especially between coronary spasm and spontaneous coronary artery dissection.

This research has produced foamed glass-ceramics from coal fired power station furnace bottom ash (FBA) and soda-lime-silica glass. The as-received FBA was wet milled with different additions of glass. The resultant slurry was dried and formed into a powder. The powder was pressed and sintered at a range of temperatures with additions of a fluxing agent (sodium tetraborate decahydrate), a bubble stabilising additive (tri-sodium phosphate) and a bloating agent (calcium carbonate) and this produced foamed FBA-glass-ceramics. The effect of glass content and sintering temperature on the properties of the sintered ceramic foams are reported. A range of potential applications including thermal insulation and biological filters for water and wastewater treatment are discussed. The research demonstrates that it is possible to engineer the properties of FBA derived glass-ceramic foams by careful control of the composition and processing conditions in order to transform a problematic waste into commercially interesting materials.

To analyze the clinical presentations of female inguinal hernia and discuss the appropriate surgical approach for hernia repair. A retrospective analysis of female children who received hernia repair for unilateral or bilateral inguinal hernia between 2007 and 2019 was held. A total of 2256 hernia repairs, 1498 (66.3%) open hernia repair (OH), and 758 (33.7%) laparoscopic hernia repair (LH) were performed. There were 1693 (75.0%) unilateral, 889 (39.4%) right, 801 (35.5%) left, 3 (0.1%) unrecorded, and 563 (25.0%) bilateral patients. One hundred seven (14.1%) laparoscopic contralateral explorations led to simultaneous contralateral high ligation. Among LH patients, 3 (0.4%) received repeat LH for ipsilateral recurrent hernia (IRH). Among OH patients, 19 (1.3%) underwent another OH for metachronous contralateral hernia (MCH). There was no significant difference between OH and LH for IRH (P = 0.015), unlike for MCH (P < 0.010). There was a higher percentage of unilateral inguinal hernia than bilateral, with a right-side bias. Despite the associated learning curve, this study advocates for LH as it is a safe procedure that allows for efficient and effective contralateral exploration without increasing total anesthesia time. We also advocate for simultaneous contralateral hernia repair as it would potentially reduce the need for a second surgery and the financial and emotional burden that parents experience with surgery.

Recently, reconfigurable intelligent surface (RIS), which operates with the aim to manipulate multi-path signals, has been widely considered for wireless communications. In this letter, we extend the employment of RIS to indoor positioning, with the aid of ultra-wideband (UWB) technique. Moreover, the Cramer-Rao lower bound of the developed positioning scheme is quantified. Both theoretical analysis and simulation results demonstrate that RIS has the potential to realize accurate positioning with a single access point, due to its ability to mark the channel and replace traditional active positioning anchors. Moreover, it is also depicted that when the number of receive antennas is limited, time-of-arrival based positioning has a higher accuracy than that based on angle-of-arrival, due to the high multipath resolution of UWB signals.

Novel communication technology based on large intelligent surface (LIS) [1] has arisen recently, with the aim to enhance the signal quality at the receiver. In this paper, a practical structure of LIS-based spatial modulation (LIS-SM) is proposed, in order to utilize both transmit and receive antenna indices. Meanwhile, the theoretical average bit error rate (ABER) performance bound of the developed LIS-SM scheme is investigated. For the sake of achieving further spatial diversity gain, we extend its employment to the antenna selection (AS) scenario, and a low-complexity selection algorithm is designed on the basis of minimum squared Euclidian distance and signal-to-leakage-and-noise ratio as well as the idea of greedy elimination algorithm. Performance analysis shows that AS-aided LIS-SM is more robust in terms of ABER compared with conventional LIS-SM. Moreover, complexity analysis also depicts that the proposed fast selection algorithm achieves much lower complexity yet a comparable ABER performance, compared to the traditional exhaustive search.

In this letter, we propose a new convert information embedded spatial modulation (SM) system for secure communications, in which the transmitter tries to send covert information to the specific receiver while keeping the unintended receiver unaware of the transmission. In the proposed system, the covert information bits are conveyed via the activated antenna index while the common information bits are via the modulation symbols. Specifically, the convert information modulation is achieved by carefully designing the space-time mapping principle so that it is disguised as a conventional SM antenna index. Furthermore, an efficient detection scheme is designed for the proposed system. The simulation results show that the proposed scheme with the developed receiver can offer nearly the same performance gain as conventional SM, whereas the unintended receiver can hardly detect the information correctly. Moreover, the average bit error rate (BER) is analyzed, which also validates our simulation results.

Additive manufacturing (AM) process is an ideal way to rapidly prototype freeform optics. We present a new precision additive freeform optics manufacturing (AFOM) method using pulsed infrared laser...

With the rapid development of wireless communications, the signals may be transmitted in different media, such as visible light and millimeter-wave along the communication path. In this case, there will be different devices working in different media, which cannot directly communicate to each other. For alleviating this problem, we first conceive a cross-media communication scenario where two devices for different media could communicate with the aid of a relay working in both media. Furthermore, we derive the average outage probability of the uplink and downlink communications. Finally, aiming at minimizing the derived average outage probability, the optimal power allocation (PA) scheme at the relay side is also derived and verified by simulation results.

Background Traumatic coagulopathy (TC) arises primarily from coagulation system failure to maintain adequate hemostasis after serious blood loss or trauma. Circulatory homeostasis restoration is the mainstay of the therapeutic approach to TC, but the effects are significantly inhibited by coagulopathy. Objective To identify the therapeutic effects and underlying mechanism of compound amino acid (CAA) combined with high-dosage of vitamin B6 (VB6) on TC. Methods Rabbit traumatic model and cellular model were used to evaluate the effect of CAA combined with high-dosage of VB6 in TC. Blood concentrations of AST and ALT were measured using the Vitros 250 device while blood APTT, PT and TT concentrations were measured using commercial diagnostics kits. Furthermore, qRT-PCR, ELISA and Western blotting were used to determine the expression of clotting factor (II, VII, IX, X and XI), inflammatory factors (TNF-α, IL-6 and IL-1β) and HMGB1/TLR4/NF-κB signaling-related proteins, respectively. Results In the rabbit traumatic model, CAA combined with high-dosage of VB6 therapy inhibited the high expression of AST and ALT, but increased the expression of coagulation factors. Additionally, in both the rabbit trauma model and cellular injury model, CAA combined with high-dosage of VB6 inhibited the expression of inflammatory factors (IL-6, TNF-α and IL-1β) and proteins (HMGB1, TLR4 and p-p65) in HMGB1/TLR4/NF-κB pathway. Most importantly, over-expression of HMGB1 reversed the effect of CAA and VB6 in HUVECs and EA.hy926 cells injury model. Conclusion CAA combined with high-dosage of VB6 alleviated TC and inhibited the expression and secretion of inflammatory factors by inhibiting HMGB1-mediated TLR4/NF-κB pathway.

Probiotics administered orally endure one of two fates: some merely pass through, but others colonize the gut permanently. Although probiotics that can stably engraft in the gut are believed to exert beneficial effects on the host in terms of increasing the efficiency of metabolic activity and enabling durable modulation of the indigenous microbiota, the strains of long-term gut colonizers are poorly delineated. This review summarizes the gut colonization modes of Lactobacillus and Bifidobacterium in the context of their natural niches and engraftment metadata in an attempt to identify organisms with long-term gut colonization potential. Advances in colonization evaluation methods are identified, and the effects of dietary components and metabolic interactions among ingested strains on bacterial colonization are discussed.

Pelvic floor disorders (PFDs) represent a group of common and frequently-occurring diseases that seriously affect the life quality of women, generally including stress urinary incontinence and pelvic organ prolapse. Surgery has been used as a treatment for PFD, but almost 30% of patients require subsequent surgery due to a high incidence of postoperative complications and high recurrence rates. Therefore, investigations of new therapeutic strategies are urgently needed. Stem cells possess strong multi-differentiation, self-renewal, immunomodulation, and angiogenesis abilities and they are able to differentiate into various cell types of pelvic floor tissues and thus provide a potential therapeutic approach for PFD. Recently, various studies using different autologous stem cells have achieved promising results by improving the pelvic ligament and muscle regeneration and conferring the tissue elasticity and strength to the damaged tissue in PFD, as well as reduced inflammatory reactions, collagen deposition, and foreign body reaction. However, with relatively high rates of complications such as bladder stone formation and wound infections, further studies are necessary to investigate the role of stem cells as maintainers of tissue homeostasis and modulators in early interventions including therapies using new stem cell sources, exosomes, and tissue-engineering combined with stem cell-based implants, among others. This review describes the types of stem cells and the possible interaction mechanisms in PFD treatment, with the hope of providing more promising stem cell treatment strategies for PFD in the future.

This article investigates the security issue based on the proactive channel hopping scheme in wireless networked control systems (WNCS), where the sensor sends the measurement data to the controller through multiple channels attacked by a periodic denial-of-service jammer. For a jammer with the limited energy, the number of attacks, which denotes the amount of time expended in launching the attack, increases with the decline in the channel number attacked at each time, which has an effect on the success of receiving the data. On the basis of this, the problem of making an optimal tradeoff between the channel number attacked at each time and the attack number to degrade the WNCS performance maximally is investigated. We formulate this problem as an integer programming problem based on the linear quadratic Gaussian control cost function. Then, a necessary condition of the optimal solution without integrality constraints for this optimization problem is given for the scenario where the sensor utilizes one channel at each time to perform the data transmission. We further investigate this problem for the case where the sensor can select several channels at each time to transmit the measurement data. Moreover, for both cases the corresponding algorithms are presented to approximate optimal schedules. Finally, the theoretical results and the validity of the algorithm proposed are verified via the numerical results.

We propose an indoor lightwave downlink wireless communication network with the non-orthogonal multiple access (NOMA) technology, that consists of one visible light communication (VLC) access point (AP) and a pair of randomly located users. Although both users can directly receive information from the AP, the performance of the far user is degraded compared to the near one due to the asymmetrical channel gains. Thus, the user cooperation strategy is proposed to improve the performance of the far user by using mixed VLC/RF relaying technique in parallel with the wireless optical direct link. To efficiently exploit the available heterogeneous links, the concept of cross-band selection combining (CBSC) is introduced, according to which the far user is continuously served by either the mixed VLC/RF or the direct VLC link. Meanwhile, the performance of the proposed scheme is thoroughly investigated and compared to appropriate baselines. To this end, we derive closed-form expressions for the outage probability of each user as well as the system sum throughput. Finally, simulation results are provided to verify the effectiveness of the proposed scheme and the accuracy of the corresponding analysis.

Background: Previous studies on the pneumonia outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have focused on the general population and pregnant women, while little is known about the effects of SARS-CoV-2 on retardation during and after pregnancy. The purpose of this study was to evaluate the potential influence of SARS-CoV-2 on infant neurobehavioral development.Methods: A case-control study was conducted in Maternal and Child Health Hospital of Hubei Province. Nine pregnant women with SARS-CoV-2 infection and 9 controls matched by maternal age, parity, and status of chronic disease were included. Infantile neurobehavioral development was assessed through the Ages and Stages Questionnaires Edition 3 (ASQ-3).Results: The majority of pregnant women with SARS-CoV-2 experienced cesarean section (7 of 9), which was higher than the control group (5 of 9). The throat swabs of all newborn were negative. We found that compared with the control group, neonates of mothers with SARS-CoV-2 infection during pregnancy had lower scores in communication, gross movement, fine movement, problem solving, and personal-social domains; but only fine movement domain yielded statistical significance (P = 0.031).Conclusion: Infection with SARS-CoV-2 during pregnancy may have a certain impact on infant neurobehavioral development. Further studies with larger sample size are warranted for validation.

Journal of traffic and transportation engineering : JTTE 8(6), 815-999 (2021). doi:10.1016/j.jtte.2021.10.001, Published by Periodical Offices of Chang��an University, [S.I.]

Background: Multimorbidity is defined as the existence of two or more chronic health conditions in the same individual. While patients with tuberculosis commonly have multiple conditions at diagnosis, such as HIV, diabetes, and depression, to the authors' knowledge, there is limited information on the patterns of multimorbidity, and how the types and combinations of conditions could impact the healthcare utilization, expenditure, and TB outcomes.Methods: An observational cohort study of adult patients diagnosed with tuberculosis was conducted using the Chinese Center for Disease Control and Prevention (CDC)'s National TB Information System (NTBIS) linked to the Ningbo Regional Health Care Database (NRHCD) (2015–2020). Latent class analysis was used to identify comorbidity groups among the subset with ≥2 conditions including TB. Group-level health care use, expenditure, and treatment outcomes were compared with patients without chronic conditions using multivariate regression models.Results: A total of 9,651 patients with TB were identified, of whom approximately 61.4% had no chronic conditions, 17.4% had 1 chronic condition, and 21.3% had ≥2 chronic conditions. Among those with ≥1 chronic condition other than TB, 4 groups emerged: (1) general morbidity (54.4%); (2) cardiovascular morbidity without complications (34.7%); (3) cardiovascular morbidity with complications (5.0%); (4) respiratory morbidity (5.9%). The respiratory morbidity group experienced the highest expenditures, at 16,360 CNY more overall (95% CI, CNY 12,615–21,215) after adjustment compared with TB patients without chronic conditions. The respiratory morbidity and cardiovascular morbidity with complications group also had the lowest odds of favorable TB outcomes [adjusted odds ratio (aOR), 0.68; 95% CI, 0.49–0.93] and (aOR 0.59, 95% CI 0.42–0.83), respectively. The cardiovascular morbidity without complications group had the highest odds of successful TB treatment (aOR, 1.40; 95% CI, 1.15–1.71).Conclusions: Multimorbidity is common among patients with TB. The current study identified four distinct comorbidity subgroups, all of which experienced high, yet differential, rates of health care use. These findings highlight the need for urgent reforms to transform current fragmented TB care delivery and improve access to other specialists and financial assistance.

Persistent infection with human papillomavirus (HPV) and immune surveillance failure may be the initiating factors for the carcinogenesis of cervical squamous cell carcinoma (CSCC). HPV infection might affect the innate immune pathway of cervical epithelial cells that constitute the “microenvironment” for tumor cells. Programmed death-ligand 1 (PD-L1) has been reported to be an immunosuppressor that helps cancer cells escape the actions of T cells. In the present study, CXCL10 was substantially upregulated both in cervical tissues of HPV infected patients with cervical intraepithelial neoplasia (CIN) or CSCC, as well as in HPV16 E6/E7 transgenic murine cervix. The HPV-positive (HPV+) cervical cancer cell lines SiHa and Caski secreted increased levels of CXCL10 compared to human foreskin fibroblasts (HFF-1), and its receptor CXCR3 was overexpressed in HFF-1. After co-culture with SiHa or Caski, the JAK-STAT signaling pathway and exosomal PD-L1 expression were both upregulated in HFF-1. Recombinant human CXCL10 induced JAK-STAT and PD-L1, while the CXCL10-CXCR3 and JAK-STAT inhibitors AMG487 or ruxolitinib reduced the expression of PD-L1 in HFF-1 cells. Furthermore, the upregulated expression of PD-L1 was verified in HPV+ but not HPV-negative (HPV-) patients with cervical cancers by analysis of tissue microarray cores in 25 cervical lesion patients (P < 0.05). The results indicate that HPV infection can induce cervical cancer cells to secrete CXCL10, which binds to CXCR3 in the surrounding fibroblast cells,leading to JAK-STAT pathway activation and the subsequent upregulated expression of exosomal PD-L1. These mechanisms may help HPV to escape immune response attack, leading to carcinogenesis.

In this paper, we consider unmanned aerial vehicle (UAV)-enabled two-way relaying communications between two robot swarms in the absence of communication infrastructures in remote areas or post-disaster rescues. To be more specific, UAV is employed as the relay to expand the communication range between two disconnected ground robot swarms, due to its high maneuverability and flexible deployment. Meanwhile, the two-way relaying mode adopted can improve the transmission performance in terms of delay and throughput in comparison to the conventional one-way relaying, owing to the ability of allowing devices to exchange information simultaneously. In addition, the UAV’s trajectory and power allocation are jointly optimized to maximize the sum-rate of the uplink and downlink, where the joint optimization problem is decoupled into two sub-problems to address the non-convexity. Limited to the non-convex formation of the objective function for the trajectory optimization sub-problem, we firstly handle the non-convexity based on successive convex approximation method, and then alternating optimization framework is carried out to obtain the joint suboptimal solution. Numerical results exhibit significant throughput gains of the proposed scheme as compared to other benchmark schemes.

Flexible perovskite solar cells (F-PSCs) are attracting tremendous research interest due to their light weight and flexibility. However, the poor quality of perovskite films caused by deformation of flexible substrates during a general heat treatment process hinders the fabrication of high efficiency flexible cells. Here, a simple gradient heat treatment (GHT) process is developed to effectively improve the crystal quality of perovskite films and the efficiency of F-PSCs. The results show that a smaller temperature fall-off gradient will be beneficial to the further growth of perovskite films, which helps to further enhance the crystalline quality. Compared with the conventional method, the power conversion efficiency (PCE) of F-PSCs fabricated by a GHT process with a relatively small gradient significantly improved by 31%, and the maximum PCE increased to 17.37%. This work provides a new idea for ameliorating the quality of perovskite films and enhancing the performances of F-PSCs.

Advanced wireless communications to support high vehicular speeds in the scenario of intelligent mobility have attracted considerable research attentions in both academia and industry. Multi-dimensional index modulation, which exploits transmission media resources for combining the concept of index modulation to achieve higher throughput with lower energy consumption, is regarded as a potential candidate for addressing the challenges in intelligent mobility communications. However, for the multi-dimensional index modulation system used in the mobile environment, the inter-carrier-interference (ICI) imposes a significant adverse impact on the system, especially in the context of multicarrier transmission. Therefore, by focusing on the two-dimensional index modulation system, the ICI impact on space-frequency index modulation is studied in this paper. Thanks to the grouping strategies and the Gaussian approximation to model the ICI, the approximate theoretical bounds for the error performance of the two dimensional systems are derived. Moreover, a novel robust space-frequency index modulation scheme is also developed. Finally, simulation results are presented to validate the system performances and the theoretical derivations.

In this paper, the security issue of cyber-physical systems is investigated, where the observation data is transmitted from a sensor to an estimator through wireless channels disturbed by an attacker. The failure of this data transmission occurs, when the sensor accesses the channel that happens to be attacked by the jammer. Since the system performance measured by the estimation error depends on whether the data transmission is a success, the problem of selecting the channel to alleviate the attack effect is studied. Moreover, the state of each channel is time-variant due to various factors, such as path loss and shadowing. Motivated by energy conservation, the problem of selecting the channel with the best state is also considered. With the help of cognitive radio technique, the sensor has the ability of selecting a sequence of channels dynamically. Based on this, the problem of selecting the channel is resolved by means of reinforcement learning to jointly avoid the attack and enjoy the channel with the best state. A corresponding algorithm is presented to obtain the sequence of channels for the sensor, and its effectiveness is proved analytically. Numerical simulations further verify the derived results.

As one of the key enabling technologies of emerging smart societies and industries (i.e., industry 4.0), the Internet of Things (IoT) has evolved significantly in both the technologies and applications. It is estimated that more than 25 billion devices will be connected by wireless IoT networks by 2020. In addition to ubiquitous connectivity, many envisioned applications of the IoT, such as industrial automation, vehicle-to-everything (V2X) networks, smart grids, and remote surgery, will have stringent transmission latency and reliability requirements, which may not be supported by the existing systems. Thus, there is an urgent need for rethinking the entire communication protocol stack for wireless IoT networks.

In this paper, we propose a novel framework of low-cost link adaptation for spatial modulation multiple-input multiple-output (SM-MIMO) systems-based upon the machine learning paradigm. Specifically, we first convert the problems of transmit antenna selection (TAS) and power allocation (PA) in SM-MIMO to ones-based upon data-driven prediction rather than conventional optimization-driven decisions. Then, supervised-learning classifiers (SLC), such as the K -nearest neighbors (KNN) and support vector machine (SVM) algorithms, are developed to obtain their statistically-consistent solutions. Moreover, for further comparison we integrate deep neural networks (DNN) with these adaptive SM-MIMO schemes, and propose a novel DNN-based multi-label classifier for TAS and PA parameter evaluation. Furthermore, we investigate the design of feature vectors for the SLC and DNN approaches and propose a novel feature vector generator to match the specific transmission mode of SM. As a further advance, our proposed approaches are extended to other adaptive index modulation (IM) schemes, e.g., adaptive modulation (AM) aided orthogonal frequency division multiplexing with IM (OFDM-IM). Our simulation results show that the SLC and DNN-based adaptive SM-MIMO systems outperform many conventional optimization-driven designs and are capable of achieving a near-optimal performance with a significantly lower complexity. This work was supported in part by the National Science Foundation of China under Grant 61876033 and Grant 61671131, in part by the Foundation Project of National Key Laboratory of Science and Technology on Communications under Grant 9140C020108140C02005, and in part by the Fundamental Research Funds for the Central Universities under Grant ZYGX2015KYQD003.The work of M. Xiao was supported in part by the SSF project “High-Reliable Low-Latency Industrial Wireless Communications” and in part by EU Marie Sklodowska-Curie Actions Project “High-Reliability Low-Latency Communications With Network Coding,” and ERA-NET, “SMART-MLA.”

A key enabler for the intelligent information society of 2030, 6G networks are expected to provide performance superior to 5G and satisfy emerging services and applications. In this article, we present our vision of what 6G will be and describe usage scenarios and requirements for multi-terabyte per second (Tb/s) and intelligent 6G networks. We present a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks to provide ubiquitous and unlimited wireless connectivity. We also discuss artificial intelligence (AI) and machine learning [1], [2] for autonomous networks and innovative air-interface design. Finally, we identify several promising technologies for the 6G ecosystem, including terahertz (THz) communications, very-large-scale antenna arrays [i.e., supermassive (SM) multiple-input, multiple-output (MIMO)], large intelligent surfaces (LISs) and holographic beamforming (HBF), orbital angular momentum (OAM) multiplexing, laser and visible-light communications (VLC), blockchain-based spectrum sharing, quantum communications and computing, molecular communications, and the Internet of Nano-Things.

With the fast development of smart terminals and emerging new applications (e.g., real-time and interactive services), wireless data traffic has drastically increased, and current cellular networks (even the forthcoming 5G) cannot completely match the quickly rising technical requirements. To meet the coming challenges, the sixth generation (6G) mobile network is expected to cast the high technical standard of new spectrum and energy-efficient transmission techniques. In this article, we sketch the potential requirements and present an overview of the latest research on the promising techniques evolving to 6G, which have recently attracted considerable attention. Moreover, we outline a number of key technical challenges as well as the potential solutions associated with 6G, including physical-layer transmission techniques, network designs, security approaches, and testbed developments.

Interleukin 33 (IL33) has been found to be cardioprotective on various cardiovascular pathologies. However, it is not clear whether IL33 may inhibit myocardial infarction-related ventricular remodeling through inducing macrophage polarization. The objective of present study is to assess whether IL33 can improve ventricular remodeling after myocardial infarction by inducing macrophage polarization. In this study, the direct influence of IL33 on the polarization of macrophages and its mechanism in vitro were investigated. The potential protective effects of IL33 on acute and chronic myocardial infarction (MI) in vivo as well as its underlying mechanism through macrophage polarization were also determined. We found that IL33 significantly enhanced M2 macrophage and decreased the proportion of M1 macrophage. Importantly, IL33 induced M2 macrophage polarization by activating the JAK/STAT signaling pathway. In vivo, IL33 weaken the inflammatory level and myocardial apoptosis after MI and improved the systolic and diastolic function of the heart. Furthermore, IL33 significantly reduced infarct area and prevented the progression of fibrosis by inducing M2 macrophage polarization. The protective effects of IL33 were suppressed by JAK/STAT signaling pathway inhibitor. Our findings highlighted that IL33 not only reduced the early inflammatory response and inhibited myocardial apoptosis, but also increased the number of M2 macrophage in the infarcted area, significantly reduced infarct area and prevented the progression of fibrosis by activating JAK/STAT pathway. Therefore, IL33 may be a novel cardiac protective cytokine for myocardial infarction.

Educational facilities are valued highly by citizens and play an important part in improving housing prices. Most existing studies applied the hedonic price model to obtain the average effects of educational facilities on housing prices. However, these effects may be heterogeneous in different conditional quantiles of housing prices. Aside from the average effects, scholars are also interested in the different behaviors of high-, medium-, and low-priced homebuyers, behaviors that cannot be simply explained by ordinary least-squares estimation without sample truncation. To fill this gap, this study utilizes quantile and spatial quantile regression models to obtain a complete description of the entire distribution. On the basis of 2015 housing transaction data in Hangzhou, substantial differences are identified in the effects of educational facilities on housing price across the conditional distribution. In particular, primary and secondary schools considerably improve housing prices over the entire conditional distribution, whereas kindergartens are only valued by homebuyers of lower- and higher-priced housing. Furthermore, only households of high-priced housing are willing to pay a premium for the accessibility of senior high schools and universities. The effect of spatial dependence on higher-priced housing is more pronounced than that on lower-priced housing, and the consideration of spatial attributes improves the explanatory ability. Empirical results indicate that the average effects of educational facilities on housing prices obtained by existing studies that used the traditional hedonic price model is far from adequate in shedding light on this real-world phenomenon. In particular, the quantile effect should be further revealed to obtain an in-depth understanding.

Sodium (±)‐5‐bromo‐2‐(a‐hydroxypentyl) benzoate (generic name: brozopine, BZP) has been reported to protect against stroke‐induced brain injury and was approved for Phase II clinical trials for treatment of stroke‐related brain damage by the China Food and Drug Administration (CFDA). However, the role of BZP in cardiac diseases, especially in pressure overload‐induced cardiac hypertrophy and heart failure, remains to be investigated. In the present study, angiotensin II stimulation and transverse aortic constriction were employed to induce cardiomyocyte hypertrophy in vitro and in vivo, respectively, prior to the assessment of myocardial cell autophagy. We observed that BZP administration ameliorated cardiomyocyte hypertrophy and excessive autophagic activity. Further results indicated that AMP‐activated protein kinase (AMPK)‐mediated activation of the mammalian target of rapamycin (mTOR) pathway likely played a role in regulation of autophagy by BZP after Ang II stimulation. The activation of AMPK with metformin reversed the BZP‐induced suppression of autophagy. Finally, for the first time, we demonstrated that BZP could protect the heart from pressure overload‐induced hypertrophy and dysfunction, and this effect is associated with its inhibition of maladaptive cardiomyocyte autophagy through the AMPK‐mTOR signalling pathway. These findings indicated that BZP may serve as a promising compound for treatment of pressure overload‐induced cardiac remodelling and heart failure.

In this paper, a novel multi-user multiple-input multiple-output (MIMO) transmission scheme, called non-orthogonal multiple access (NOMA) aided precoded spatial modulation (PSM) (NOMA-PSM) is proposed for overloaded downlink transmissions. NOMA-PSM beneficially amalgamates the concept of index modulation (IM) and NOMA techniques, and therefore it inherits both the merits of IM with low-complexity transceiver and the advantages of NOMA with high bandwidth efficiency. For the proposed scheme, we develop a pair of low-complexity yet effective detection algorithms by combining the spatial index demodulation and successive interference cancelation. The spectral efficiency (SE), implementation cost, and multi-user interference of NOMA-PSM are evaluated and compared with conventional designs. Furthermore, we derive the mutual information (MI) of the proposed NOMA-PSM to characterize its achievable SE and also obtain a lower bound for simplifying the measurement of MI. Our simulation results show that the proposed NOMA-PSM scheme is capable of achieving considerable performance gains over conventional orthogonal multiple access aid PSM and antenna-grouping-based PSM in wireless MIMO fading channels.

In this paper, we investigate the optimal dynamic social-aware peer selection with spectrum-power trading to maximize the average sum energy efficiency (EE) of cellular users (CUs) for uplink transmission for an orthogonal frequency division multiple access cellular network with device-to-device (D2D) communications. Different from the previous studies, which mostly focus on how to exploit social ties in human social networks to construct the permutation of all the feasible peers, we consider dynamic peer selection with social awareness-aided spectrum-power trading in D2D overlaying communications. Specifically, the amount of transmit power from the D2D transmitters to relay the CUs for uplink transmission is determined by their social trust levels. Likewise, the D2D transmitters can gain the corresponding amount of spectrum from the CUs for D2D pair link communications, which can be regarded as the compensation of the power consumption for relaying CUs. We formulate the dynamic peer selection problems with social awareness-aided spectrum-power trading in cooperative D2D communications into the infinite-horizon time-average renewal-reward problems subject to time average constraints on a collection of penalty processes. And the Lyapunov optimization concepts-based drift-plus-penalty algorithms are proposed to solve them. The simulation results demonstrate the effectiveness of the proposed dynamic peer selection algorithms. And further performance comparison indicates that the proposed dynamic peer selection algorithms not only maximize the average EE of CUs but also guarantee higher privacy protection.

We investigate the energy-efficient power allocation for downlink transmission in orthogonal frequency division multiple access-based long term evolution systems. Aiming at realizing on-demand power allocation in cellular networks, we explore the available coordination between the base station and multiple users, and propose a new performance merit, namely, the demand side coordination energy efficiency (DSC-EE), which captures the system normalized EE and the demand side information. The proposed DSC-EE is designed to exploit individual disparities from both the entire system and the individual own expected utility perspectives. Our goal is to maximize the DSC-EE of the system via power allocation with a constraint on the maximum transmit power. Specifically, the objective function of DSC-EE maximization problem in a fractional form can be transformed into a subtractive form that is more tractable based on the fractional programming theory. The convergence property of the proposed algorithms and the meaningfulness of the proposed performance merit related to the EE are demonstrated by simulations. The comparison of four EE metrics, the EE and the rate fairness, global-EE, Sum-EE, and DSC-EE, shows that the DSC-EE maximization tends to achieve high implementation level of on-demand power allocation while ensuring the EE of the system. In addition, when the minimum rate replaces the expected rate in the DSC-EE, further performance comparison indicates the necessity and impact of the expected rate in the tolerable quality of service bias function.

This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR), which is termed as the PR aided Transmission Antenna Selection MIMO (PR-TAS aided MIMO). As the conventional TAS algorithms need to search all possible legitimate antenna subsets, they may impose some redundant calculations. In order to avoid this problem, we employ some pattern recognition methods to carry out the TAS algorithm in this paper. To be specific, two PR algorithms, namely the K-Nearest Neighbor (KNN) algorithm and the Support Vector Machine (SVM) algorithm, are introduced and redesigned to obtain a TAS with lower complexity but higher efficiency. Moreover, in order to improve the performance of the SVM, we propose a new feature extraction of channel matrix for the TAS. Our simulation results show that the proposed KNN and SVM based PR-TAS algorithms are capable of striking a flexible tradeoff between the complexity and the Bit Error Rate (BER), and the new feature can effectively improve the BER performance compared with the conventional feature extraction method. Keywords: Antenna selection, K-nearest neighbors, Multiple-input multiple-output, Pattern recognition, Support vector machine

This paper proposes a new fuzzy-logic-inspired multi-contrast-agent strategy (MCAS) for optimal tumor classification. The proposed strategy accounts for the competitive and symbiotic relationships among multiple contrast agents through a sequential logic circuit analysis. Furthermore, the strategy enables an intuitive yet systematic way to analyze the tumor classification vagueness and ambiguous uncertainties and optimize the utilization of multiple agents through a fuzzy comprehensive evaluation. A numerical example is used to demonstrate how the classification performance in terms of decision-making fuzziness is significantly improved with an optimal “cocktail recipe” methodology using the proposed MCAS.

Abusive language detection serves to ensure a compelling user experience via high-quality content. Different sub-categories of abusive language are closely related, with most aggressive comments containing personal attacks and toxic content and vice versa. We set a multi-task learning framework to detect different types of abusive content in a mental health forum to address this feature. Each classification task is treated as a subclass in a multi-class classification problem, with shared knowledge used for three related tasks: attack, aggression, and toxicity. Experimental results on three sub-types of Wikipedia abusive language datasets show that our framework can improve the net F1-score by 7.1%, 5.6%, and 2.7% in the attack, aggressive, and toxicity detection. Our experiments identified multi tasking framework act as an effective method in abusive language detection.

BACKGROUND A body shape index (ABSI) is an emerging anthropometric indicator, challenging two traditional parameters: body mass index (BMI) and waist circumference (WC). We aimed to systematically compare and validate the capability of anthropometric indicators for determining pediatric high blood pressure (HBP). METHODS A total of 3150 participants aged 7-17 years were enrolled from Suzhou, China. Areas under the receiver operating characteristic curve (AUC) were obtained to evaluate the performance of anthropometric indicators in detecting HBP. DeLong's test was used to examine whether the AUCs of anthropometric indicators in contrast to BMI or original ABSI were statistically different. Furthermore, a meta-analysis was performed to combine results from this study and five similar articles from databases. RESULTS In Suzhou population, BMI exhibited the largest AUC (AUC = 0.705), followed by WC (AUC = 0.669) and original ABSI (AUC = 0.514). Modified ABSI (AUC: 0.537-0.681), although had slightly better performance than original ABSI, was still less valuable than BMI (P

Federated learning-based navigation has received much attention in vehicular IoT. The intention is to employ a big number of end-users for data collection along different trajectories and perform local training of a global learning model to substitute the global positioning system (GPS) in urban areas. The prerequisites for its commercialization, however, lie in the location-dependent input data trustworthiness and participants’ privacy preservation. In this paper, we propose a privacy-preserving proof-of-location mechanism using blockchain to meet these conditions. Specifically, the proposed scheme utilizes a Threshold Identity-Based Encryption (TIBE) system for the generation of secret shares, such that each anonymous location proof can only be verified with at least a threshold number of participants. In addition, the proposed scheme exploits a cuckoo filter for the secure and efficient maintenance and dissemination of location proofs. Systematic security analysis is conducted to demonstrate the fulfillment of harsh security requirements. Performance evaluations are carried out to validate the computation efficiency in comparison with an oblivious transfer (OT) protocol, which has been widely adopted for secure data acquisition.

Nanoporous thin films have been extensively studied for their potential applications such as thermoelectrics and thermal management. Different from the popular cylindrical through-film pores, a novel nanoslot pattern design is investigated in this work to achieve better performance in thermal insulation, in-plane thermal anisotropy, and thermoelectrics. In this nanoslot pattern, rectangular pores, or "nanoslots", are patterned in periodic rows with a narrow neck width between adjacent nanoslots within the same row. Such a narrow neck is the geometric constriction for the phonon transport, resulting in a largely reduced lattice thermal conductivity along the direction perpendicular to the nanoslot rows. In addition, the adjacent rows of nanoslots can also be arranged in an offset manner to further reduce the in-plane thermal conductivity along the same direction, eventually achieving a very high in-plane thermal conductivity anisotropy. Along another line, although the thermal transport is severely suppressed by the nanoslot pattern, the bulk-like electron transport can be largely intact due to the much shorter electron mean free paths compared with the neck width. As a result, the thermoelectric performance can be improved. In this work, frequency-dependent phonon Monte Carlo simulations are utilized to investigate the in-plane thermal conductivity anisotropy of the nanoslot patterns with a maximum room-temperature anisotropy of 37.5 among investigated patterns. Analytical models are also derived to easily predict thermal conductivity and thermoelectric performances. With a neck width reduced to 5 nm, the computed thermoelectric figure of merit can be improved to 0.58 at 1100 K. Potential applications of such nanoslot patterns, such as thermal insulations are heat guides, will also be discussed.

Background In 2017, the American College of Cardiology/ American Heart Association (ACC/AHA) guidelines redefined the threshold of high blood pressure (BP) for non-pregnant adults. Several studies aimed to determine whether lowering these thresholds should be considered for pregnancies to prevent poor neonatal outcomes, but the results were inconclusive. Methods We perform a systematic review and meta-analysis to evaluate the association between BP groups defined by the 2017 ACC/AHA guidelines and pregnancy outcomes. Relevant literature was searched in PubMed, Google Scholar, Embase, and Web of Science up to 18 May 2021. Results Sixteen eligible studies from twelve articles with a total of 303,131 pregnancies were identified, encompassing 233,084, 20,859, 39,379 individuals with normal BP, elevated BP, and stage 1 hypertension, respectively. When compared with normal BP, the combined odds ratio (95% confidence interval) of elevated BP for adverse pregnancy outcomes was not significant; whereas, that of stage 1 hypertension were 1.25 (1.13–1.39), 1.16 (1.03–1.31), 1.50 (1.28–1.77) and 1.12 (1.00–1.25) for preterm delivery, small for gestational age, low birth weight, and early-term delivery, respectively. Conclusion Our results indicated that stage 1 hypertension increased the risk of poor neonatal outcomes, highlighting the importance of recognition of stage 1 hypertension as a risk indicator for poor pregnancy outcomes.

Setting: Programmatic management of drug-resistant tuberculosis in Ningbo, China.Objective: To assess whether data-driven genetic determinants of drug resistance patterns could outperform phenotypic drug susceptibility testing in predicting clinical meaningful outcomes among patients with multidrug-resistant tuberculosis (MDR-TB).Design: We conducted a prospective cohort study of 104 MDR-TB patients. All MDR-TB isolates underwent drug susceptibility testing and genotyping for mutations that could cause drug resistance. Study outcomes were time to sputum smear conversion and probability of treatment success, as well as time to culture conversion within 6 months. Data were analyzed using latent class analysis, Kaplan–Meier curves, and Cox regression models.Results: We report that latent class analysis of data identified two latent classes that predicted sputum smear conversion with P = 0.001 and area under receiver-operating characteristic curve of 0.73. The predicted latent class memberships were associated with superior capability in predicting sputum culture conversion at 6 months and overall treatment success compared to phenotypic drug susceptibility profiling using boosted logistic regression models.Conclusion: These results suggest that genetic determinants of drug resistance in combination with phenotypic drug-resistant tests could serve as useful biomarkers in predicting treatment prognosis in MDR-TB.

Because of the complex etiology, the treatment of gastric cancer is a formidable challenge for contemporary medical. The current treatment method focuses on traditional surgical procedures, supplemented by other treatments. Among these other treatments, Traditional Chinese Medicine (TCM) plays an important role. Here, we used the systems pharmacology approach to reveal the potential molecular mechanism of PRGRC on gastric cancer which composes of Pinellia ternata(Thunb.) Breit., Rheum palmatumL., Gentiana scabraBunge, Radix Aucklandiae and Citrus aurantium L. This approach combines pharmacokinetics analysis with pharmacodynamics evaluation for the active compounds screening, targets prediction and pathways assessing. Firstly, through pharmacokinetic evaluation and target prediction models, 83 potential compounds and 184 gastric cancer-related targets were screened out. Then, the results of network analysis suggested that the targets of PRGRC were mainly involved two aspects: apoptosis and inflammation. Finally, we verified the reliability of the above analysis at the cellular level by using naringenin and luteolin with good pharmacokinetic activity as representative compounds. Overall, we found that PRGRC could influence the development of gastric cancer from a multi-scale perspective. This study provided a new direction for analyzing the mechanism of TCM.

In this paper, we propose a novel intelligent successive interference cancellation (SIC) detection algorithm, namely I-SIC, for the uplink non-orthogonal multiple access (NOMA) system. Compared with some traditional SIC detection algorithms based on channel state information (CSI) and quality of service (QoS), the proposed I-SIC can learn the implied characteristics in the received signal, channel state information and power information through deep neural network (DNN), so as to more intelligently provide sorting scheme for SIC detection algorithm and further improve the detection performance of the system. Experimental results show that compared with the traditional SIC detection algorithm based on CSI (CSI-SIC), this algorithm can significantly improve the detection performance of the system(up to 6 dB for three-user scenario with QPSK modulation).