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Background: There has been conflicting evidence on the association between multimorbidity and blood pressure (BP) control. This study aimed to investigate this associations in people with hypertension attending primary care in Canada, and to assess whether individual long-term conditions are associated with BP control. Methods: This was a cross-sectional study in people with hypertension attending primary care in Toronto between January 1, 2017 and December 31, 2019. Uncontrolled BP was defined as systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg. A list of 11 a priori selected chronic conditions was used to define multimorbidity. Multimorbidity was defined as having ≥1 long-term condition in addition to hypertension. Logistic regression models were used to estimate the association between multimorbidity (or individual long-term conditions) with uncontrolled BP. Results: A total of 67 385 patients with hypertension were included. They had a mean age of 70, 53.1% were female, 80.6% had multimorbidity, and 35.7% had uncontrolled BP. Patients with multimorbidity had lower odds of uncontrolled BP than those without multimorbidity (adjusted OR = 0.72, 95% CI 0.68-0.76). Among the long-term conditions, diabetes (aOR = 0.73, 95%CI 0.70-0.77), heart failure (aOR = 0.81, 95%CI 0.73-0.91), ischemic heart disease (aOR = 0.74, 95%CI 0.69-0.79), schizophrenia (aOR = 0.79, 95%CI 0.65-0.97), depression/anxiety (aOR = 0.91, 95%CI 0.86-0.95), dementia (aOR = 0.87, 95%CI 0.80-0.95), and osteoarthritis (aOR = 0.89, 95%CI 0.85-0.93) were associated with a lower likelihood of uncontrolled BP. Conclusion: We found that multimorbidity was associated with better BP control. Several conditions were associated with better control, including diabetes, heart failure, ischemic heart disease, schizophrenia, depression/anxiety, dementia, and osteoarthritis.

Growing technologies like virtualization and artificial intelligence have become more popular nowadays because they are more handy and accessible on mobile devices. But lack of resources for processing these applications at the user end and the limited energy of mobile devices are still significant hurdles. Collaborative edge and cloud computing are one of the solutions to this problem. An optimal offloading strategy is required to balance transmission latency for the cloud and limited resources at edge servers. We have proposed a multi-period deep deterministic policy gradient (MP-DDPG) algorithm to find an optimal offloading policy to the collaborative cloud network including the central cloud server, edge cloud servers, and mobile devices constrained by minimization of computation, transmission delay, and energy consumption. The novelty of this algorithm lies in partitioning the task to offload in multiple time slots and reusing cloud and edge resources in every slot, rather than taking a single offloading decision and running out of remote resources by offloading a single large task. Our results show that MP-DDPG achieves the minimum latency and energy consumption in the collaborative cloud network.

Quantum routing plays a key role in the development of the next-generation network system. In particular, an entangled routing path can be constructed with the help of quantum entanglement and swapping among particles (e.g., photons) associated with nodes in the network. From another side of computing, machine learning has achieved numerous breakthrough successes in various application domains, including networking. Despite its advantages and capabilities, machine learning is not as much utilized in quantum networking as in other areas. To bridge this gap, in this article, we propose a novel quantum routing model for quantum networks that employs machine learning architectures to construct the routing path for the maximum number of demands (source–destination pairs) within a time window. Specifically, we present a deep reinforcement routing scheme that is called Deep Quantum Routing Agent (DQRA). In short, DQRA utilizes an empirically designed deep neural network that observes the current network states to accommodate the network’s demands, which are then connected by a qubit-preserved shortest path algorithm. The training process of DQRA is guided by a reward function that aims toward maximizing the number of accommodated requests in each routing window. Our experiment study shows that, on average, DQRA is able to maintain a rate of successfully routed requests at above 80% in a qubit-limited grid network and approximately 60% in extreme conditions, i.e., each node can be repeater exactly once in a window. Furthermore, we show that the model complexity and the computational time of DQRA are polynomial in terms of the sizes of the quantum networks.

Abstract Background Pre‐clinical studies suggest that renin–angiotensin system blockade may improve muscle function. Clinical reports of the effect of angiotensin converting enzyme inhibitors (ACEIs) on physical functioning are inconsistent. There are no reports of the effect of angiotensin receptor blockers (ARBs) treatment in older adults. Methods We analysed data of 1268 participants in the Singapore Longitudinal Ageing Study (SLAS‐2) who provided information on the use of ACEI, ARB, and other antihypertensive drugs at baseline and follow‐up (mean 4.5 years later). Baseline and follow‐up outcome measures were cumulated deficits frailty index (CD‐FI), physical phenotype frailty index (PP‐FI), calf circumference (CC), knee extension strength, composite muscle mass and strength (MMS) z‐score, and gait speed (GS). In primary analyses, we compared the use and non‐use of an anti‐hypertensive drug class among participants with hypertensive and cardiac disease, and secondarily with participants having other chronic diseases, and those who reported no chronic diseases. Multi‐variable analyses adjusted for socioeconomic status, body mass index ≥30, ≥5 comorbidities, ≥5 drugs use, other non‐ARB or non‐ACEI drugs (calcium channel blockers, beta blockers, or hydrochlorothiazide), MMSE

Along with the development of Information Technology, Online Social Networks (OSN) are constantly developing and have become popular media in the world. Besides communication enhancement benefits, OSN have such limitations on rapid spread of false information as rumors, fake news, and contradictory news. False information spread is collectively referred to as misinformation which has significant on social communities. The more sources and topics of misinformation are, the greater the number of users are affected. Therefore, it is necessary to prevent the spread of misinformation with multiple topics within a given period of time. In this paper, we propose a Multiple Topics Linear Threshold model for misinformation diffusion, and define a misinformation blocking problem based on this model that takes account of multiple topics and budget constraint. The problem is to find a set of nodes that minimizes the impact of misinformation at an allowed cost when blocking them from the network. We prove that the problem is NP-hard and the time complexity of the objective function calculation is $\#P$ -hard. We also prove that the objective function is monotone and submodular. We propose an approximation algorithm with approximation ratio $(1-1/\sqrt {e})$ based on these attributes. For large networks, we propose an extended algorithm by using a tree data structure for quickly updating and calculating the objective function. Experiments conducted on real-world datasets show efficiency and effectiveness of our proposed algorithms in comparison with other state-of-the-art algorithms.

Fingerprint image enhancement is a key aspect of an automated fingerprint identification system. This paper describes an effective algorithm based on a novel lighting compensation scheme. The scheme involves the use of adaptive higher-order singular value decomposition on a tensor of wavelet subbands of a fingerprint (AHTWF) image to enhance the quality of the image. The algorithm consists of three stages. The first stage is the decomposition of an input fingerprint image of size 2M × 2N into four subbands at the first level by applying a two-dimensional discrete wavelet transform. In the second stage, we construct a tensor in ℝM×N×4 space. The tensor contains four wavelet subbands that serve as four frontal planes. Furthermore, the tensor is decomposed through higher-order singular value decomposition to separate the fingerprint's wavelet subbands into detailed individual components. In the third stage, a compensated image is produced by adaptively obtaining the compensation coefficient for each frontal plane of the tensor-based on the reference Gaussian template. The experimental results indicated that the quality of the AHTWF image was higher than that of the original image. The proposed algorithm not only improves the clarity and continuity of ridge structures but also removes the background and blurred regions of a fingerprint image. Therefore, this algorithm can achieve higher fingerprint classification accuracy than related methods can.

As a promising technique, power beacon provides ability of wireless energy transfer to relaying devices in Internet of Things (IoT) to serve far devices with respect to low latency and high spectrum efficiency manner. Mobile edge computing (MEC) enables smart devices to offload parts of their computation-workloads to the cellular base stations associated with edge servers. This paper introduces a promising multiple access technique, namely non-orthogonal multiple access (NOMA) to provide communication service between the base station associated with MEC and far IoT devices. In this paper, we indicate that the multiple power beacons (PBs) benefits to uplink of NOMA-MEC system with the wireless powered IoT. More antennas equipped at smart device and more PBs exhibit reasonable outage performance for the considered system. The simulation results reveal in two folds: (1) our proposed scheme can simultaneously achieve higher spectrum efficiency and ensure prolong lifetime of IoT devices; (2) the mobility of relay leads to select PB appropriately and hence the suitable scheme is realized as comparing two schemes related to ability of energy harvesting and acceptable outage behavior.

In this article, an unmanned aerial vehicle (UAV)-aided non-orthogonal multiple access (NOMA) network along with uplink (UL) and downlink (DL) transmissions is investigated. A group of sources intend to communicate with a group of destinations over Nakagami-m fading channels. Decode-and-Forward (DF) protocol is adopted at the relay (UAV plays the role of relay) while successive interference cancellation (SIC) is required at destinations (receivers) for signal detection, e.g., imperfect SIC (ipSIC) and perfect SIC (pSIC) are studied. The UAV relay benefits from the modes of full-duplex/half-duplex (FD/HD). We then derive analytical expressions of outage probability as main metric. Simulations are conducted to valid the analytical expressions. Moreover, the levels of the effectiveness of the FD mode and pSIC case are demonstrated through analysis and simulation and then compared with those of their counterparts. Numerical results are presented to validate the effectiveness of the proposed UAV-aided NOMA transmission strategies.

In this study, the performance of a secondary network in cognitive radio (CR) is studied in the context of vehicle-to-everything (V2X). The non-orthogonal multiple access (NOMA) is effectively applied in this new system model, namely CR-assisted NOMA-V2X, and it is beneficial to serve group of vehicles. In our proposed system, two schemes related to vehicle-to-vehicle (V2V) transmissions are further considered to enhance performance of the vehicle that needs higher quality of service (QoS). However, the degradation performance can be predicted by evaluating downlink under impacts from interference from the primary network, imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC). The outage performance gap among two vehicles exists since different power allocation factors were assigned to them. To validate the system performance, the outage probability is first derived in exact and approximate forms and then the throughput can be further achieved. The optimal throughput can be obtained by numerical simulations. Simulation results are provided to verify the correctness of the derived expressions and it exhibits advantages of the proposed CR-assisted NOMA-V2X system in terms of outage probability and the throughput.

Metal-organic frameworks have shown promise as nanoreactors, facilitating the synthesis of molecules that are otherwise difficult to isolate. Here, the authors design a framework featuring unobstructed adenine linkers to which thymine molecules can base-pair, allowing for thymine dimerization in the pores upon UV irradiation.

Abstract Background Frailty is an emerging issue in geriatrics and gerontology. The prevalence of frailty is increasing as the population ages. Like many developing countries, Vietnam has a rapidly ageing population. However, there have been no studies about frailty in older people in Vietnam. This study aims to investigate the prevalence of frailty and its associated factors in older hospitalised patients at the National Geriatric Hospital in Hanoi, Vietnam. Methods Prospective observational study in inpatients aged ≥60 years at the National Geriatric Hospital in Hanoi, Vietnam from 4/2015 to 10/2015. Frailty was assessed using the Reported Edmonton Frail Scale (REFS) and Fried frailty phenotype. Results A total of 461 patients were recruited (56.8% female, mean age 76.2 ± 8.9 years). The prevalence of frailty was 31.9% according to the REFS. Using the Fried frailty criteria, the percentages of non-frail, pre-frail and frail participants were 24.5, 40.1 and 35.4%, respectively. Factors associated with frailty defined by REFS were age (OR 1.05 per year, 95% CI 1.03–1.08), poor reported nutritional status (OR 4.51, 95% CI 2.15–9.44), and not finishing high school (OR 2.18, 95% CI 1.37–3.46). Factors associated with frailty defined by the Fried frailty criteria included age (OR 1.07 per year, 95% CI 1.05–1.10), poor reported nutritional status (OR 2.96, 95%CI 1.43–6.11), not finishing high school (OR 1.58, 95% CI 1.01–2.46) and cardiovascular disease (OR 1.76, 95% CI 1.16–2.67). Conclusions While further studies are needed to examine the impact of frailty on outcomes in Vietnam, the observed high prevalence of frailty in older inpatients is likely to have implications for health policy and planning for the ageing population in Vietnam.

We report the synthesis, crystal structures and magnetic properties of the giant heterometallic [Mn36Ni4]2−/0 (compounds 1, 2)/[Mn32Co8] (compound 3) “loops-of-loops-and-supertetrahedra” molecular aggregates and of a [Mn2Ni6]2+ compound (cation of 4) that is structurally related with the cation co-crystallizing with the anion of 1. In particular, after the initial preparation and characterization of compound [Mn2Ni6(μ4-O)2(μ3-OH)3(μ3-Cl)3(O2CCH3)6(py)8]2+[Mn36Ni4(μ4-O)8(μ3-O)4(μ3-Cl)8Cl4(O2CCH3)26(pd)24(py)4]2− (1) we targeted the isolation of (i) both the cationic and the anionic aggregates of 1 in a discrete form and (ii) the Mn/Co analog of [Mn36Ni4]2− aggregate. Our synthetic efforts toward these directions afforded the discrete [Mn36Ni4] “loops-of-loops-and-supertetrahedra” aggregate [Mn36Ni4(μ4-O)8(μ3-O)4(μ3-Cl)8Cl2(O2CCH3)26(pd)24(py)4(H2O)2] (2), the heterometallic Mn/Co analog [Mn32Co8(μ4-O)8(μ3-O)4(μ3-Cl)8Cl2(μ2-OCH2CH3)2(O2CCH3)28(pd)22(py)6] (3) and the discrete [Mn2Ni6]2+ cation [Mn2Ni6(μ4-O)2(μ3-OH)4(μ3-Cl)2(O2CCH3)6(py)8](ClO4)(OH) (4). The structure of 1 consists of a mixed valence [Mn28IIIMn8IINi4II]2− molecular aggregate that contains two Mn8IIINi2II loops separated by two Mn6IIIMn4II supertetrahedral units and a [Mn2IIINi6II]2+ cation based on two [MnIIINi3II(μ4-O)(μ3-OH)1.5(μ3-Cl)1.5]4+ cubane sub-units connected through both mono- and tri-atomic bridges provided by the μ4-O2− and carboxylate anions. The structures of 2–4 are related to those of the compounds co-crystallized in 1 exhibiting however some differences that shall be discussed in detail in the manuscript. Magnetism studies revealed the presence of dominant ferromagnetic interactions in 1–3 that lead to large ground state spin (ST) values for the “loops-of-loops-and-supertetrahedra” aggregates and antiferromagnetic exchange interactions in 4 that lead to a low (and possibly zero) ST value. In particular, dc and ac magnetic susceptibility studies revealed that the discrete [Mn36Ni4] aggregate exhibits a large ST value ~ 26 but is not a new SMM. The ac magnetic susceptibility studies of the [Mn32Co8] analog revealed an extremely weak beginning of an out-of-phase tail indicating the presence of a very small relaxation barrier assignable to the anisotropic Co2+ions and a resulting out-of-phase ac signal whose peak is at very low T.