Pair Of Users Research Articles

Comparison of incident hypertension between SGLT2 inhibitors vs. DPP4 inhibitors

Although several randomized clinical trials have reported the potential benefit of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in reducing blood pressure (BP), whether SGLT2i can reduce incident hypertension is unknown. We analyzed individuals with diabetes who were newly prescribed SGLT2i or dipeptidyl peptidase 4 inhibitors (DPP4i) in a large-scale epidemiological database. The primary outcome was the incidence of hypertension. A propensity score matching algorithm was employed to compare the subsequent development of hypertension between the SGLT2i and DPP4i groups. After propensity score matching, 5708 well-balanced pairs of SGLT2i and DPP4i users were identified. SGLT2i administration was associated with a reduced risk of hypertension (HR 0.91, 95% CI: 0.84–0.97). The advantage of SGLT2i use over DPP4i use for incident hypertension was generally consistent in several sensitivity analyses, and subgroup analyses showed that SGLT2i use was significantly associated with a lower risk of hypertension in men, patients with baseline HbA1c of <7.5%, and baseline systolic blood pressure ≥127 mmHg. Our investigation using nationwide real-world data demonstrated the potential advantage of SGLT2i over DPP4i in reducing the development of hypertension in individuals with diabetes.

Collaborative Meta-Path Modeling for Explainable Recommendation

Although recommender systems have achieved considerable success, sometimes it is difficult to convince users due to the failure to explain the recommendation results. For this reason, explainable recommender systems have drawn a lot of attention in recent years. Among explainable recommendation models, the meta-path-based model plays a significant role because it can reason over the path connecting a user–item pair to achieve explainability. However, it is difficult for the meta-path-based model to achieve such a common explanation in collaborative filtering as “a user similar to you has purchased item <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$A$</tex-math> </inline-formula> ” because there is no such meta-path. In this article, we contribute a new model named collaborative meta-path modeling for explainable recommendation (COMPER). It models the similarity of user pairs and item pairs through rating information and constructs collaborative meta-paths for explainability. In addition, we design an attention mechanism to aggregate different paths connecting the target user and the target item. Moreover, the information of the subgraph composed of all paths connecting the target user and the target item is integrated for rating prediction. Extensive experiments on five real-world datasets demonstrate that COMPER achieves good performance in a variety of scenarios, achieving improvements over several baselines.

Adherence to GLP1-RA and SGLT2-I affects clinical outcomes and costs in patients with type 2 diabetes.

To evaluate the impact of adherence to glucagon like peptide-1 receptor agonists (GLP1-RA) and sodium-glucose transporter two inhibitors (SGLT2-I) on clinical outcomes and costs in patients with type 2 diabetes mellitus (T2DM). The 121,115 residents of the Lombardy Region (Italy) aged ≥40years newly treated with metformin during 2007-2015 were followed to identify those who started therapy with GLP1-RA or SGLT2-I. Adherence to drug therapy over the first year was defined as the proportion of days covered >80%. Within each drug class, for each adherent patient, one non-adherent patient was matched for age, sex, duration, adherence to metformin treatment and propensity score. The primary clinical outcome was a composite of insulin initiation, hospitalisation for micro- and macrovascular complications and all-cause mortality after the first year of drug treatment. Costs were evaluated based on reimbursements from the national healthcare system. After matching, 1182 pairs of adherent and non-adherent GLP1-RA users and 1126 pairs of adherent and non-adherent SGLT2-I users were included. In both groups, adherent patients experienced a significantly lower incidence of the primary outcome (HR: 0.85, 95% CI 0.72-0.98 for GLP1-RA and HR: 0.69, 95% CI 0.55-0.87 for SGLT2-I). A significant reduction in hospitalizations was found for adherent patients in the GLP1-RA group but not for the SGLT2-I group. Results were consistent when analyses were stratified by age and sex. While higher drug-related costs in the adherent group were counterbalanced by decreased hospitalisation costs in SGLT2-I treated patients, this was not the case for GLP1-RA. Higher adherence to drug treatment with GLP1-RA and SGLT2-I during the first year of the drug intake is associated with a lower incidence of adverse clinical outcomes in a real-world setting.

Large-scale quantum key distribution network simulator

The wide range of supported services in modern telecommunication networks has increased the demand for highly secure means of communication. Common security frameworks based on the computational security model are expected to become insecure due to significant advances in quantum computing. Quantum key distribution (QKD), a new secret key agreement primitive, enables long-anticipated practical information-theoretical security (ITS). Over the past two decades, academic and industrial communities have devoted their time and resources to developing QKD-based networks that can distribute and serve ITS keys to remote parties. However, because the availability of QKD network testbeds to the larger research community is limited and the deployment of such systems is costly and difficult, progress in this area is noticeably slow. To address this problem and spur future development and education, we provide a valuable, unique tool for simulating a QKD network. The tool is essential to testing novel network management methodologies applied to large-scale QKD networks. The simulator model contained in the tool was validated by simulating a network with six nodes and three pairs of users. The results indicate that the designed functional elements operate correctly.

JORA: Weakly Supervised User Identity Linkage via Jointly Learning to Represent and Align.

The user identity linkage that establishes correspondence between users across networks is a fundamental issue in various social network applications. Efforts have recently been devoted to introducing network embedding techniques that map the different network users into the common representation space, thereby inferring user correspondence based on the similarities of their representations. However, existing studies that separately train the network embedding and space alignment in two stages may lead to conflict between the objectives of the two stages. Besides, the similarities between unlabeled cross-network user pairs are difficult to define and largely impact the result. Moreover, many previous methods still need plenty of labeled aligned user pairs to ensure performance, which may not be available. To address the above problems, we propose to solve the weakly-supervised user identity linkage problem via JOintly learning to Represent and Align, i.e., the JORA model. The architecture of JORA adopts the inductive graph convolutional network (GCN) that learns representations for each network. The model is jointly optimized by the representation learning component and alignment learning component. The former one aims to preserve the similarities between intranetwork users. The latter one aligns the different spaces by a projection function and aims to preserve the similarities between cross-network users. A specific attention mechanism is proposed to learn self-adaptive similarities for unlabeled user pairs during alignment learning and it reduces the error propagation caused by predefined similarities. The joint optimization helps perceive network characteristics during alignment and reduces the number of labeled users required. Experiments conducted on real social networks show that the proposed model achieves significantly better performance than the state-of-the-art methods.

Performance evaluation for multi-antenna UWOC-RF NOMA systems with imperfect CSI and SIC

Information transmission is easily affected by obstacles or other factors, which makes it challenging to achieve perfect channel state information (CSI) and successive interference cancellation (SIC) in practical applications. Therefore, in this paper, a dual-hop underwater wireless optical communication-radio frequency (UWOC-RF) system with non-orthogonal multiple access (NOMA) in the presence of both imprecise CSI and imperfect SIC is investigated. In particular, the underwater source sends a superimposed optical NOMA signal to a pair of land-based users via a decode-and-forward relay on the surface, which decodes the received signal and encodes it into the RF one before broadcasting it to the terrestrial users. Considering a scenario that both the land-based users are equipped with multiple antennas and adopt a maximal-ratio combining technique to deal with those multiple copies of received signals, we first format the expressions of probability density function, cumulative distribution function, and the p-th moment of the imperfect channel gain in the UWOC link. And then the analytical and asymptotic expressions for outage probability as well as the closed-form expression for average achievable rate of each user are obtained by utilizing the Meijer's-G and the Fox's-H functions. Finally, Monte-Carlo simulations are performed to validate the accuracy of those analytical expressions.

Metformin and the risks of cellulitis, foot infections, and amputation in patients with type 2 diabetes.

Patients with diabetes tend to have cellulitis, foot infections, and amputation. We conducted this research to compare the risks of cellulitis, foot infections, and amputation between metformin no-use and use in persons with type 2 diabetes. Using propensity score matching, we identified 23 234 pairs of metformin nonusers and users from the National Health Insurance Research Database of Taiwan, since January 1, 2000, to December 31, 2017. Cox proportional hazards models were adopted to examine the risks of incident cellulitis, recurrent cellulitis, foot infections, and amputation between metformin use and no-use. The mean follow-up period of metformin use and no-use was 6.31 (3.93) and 5.54 (3.97) years, respectively. Compared with metformin no-use, the adjusted hazard ratio and 95% confidence interval for metformin use in cellulitis development, recurrent cellulitis, foot infections, and amputation were 1.08 (1.04-1.12), 1.33 (1.14-1.55), 1.91 (1.75-2.09), and 1.88 (1.35-2.62), respectively. The longer cumulative duration of metformin usage had association with higher risks of these outcomes than metformin no-use. This population-based cohort study revealed that metformin use had association with significantly higher risks of incident cellulitis, recurrent cellulitis, foot infections, and amputation than metformin no-use in patients with type 2 diabetes.

Performance Analysis of Power Allocation and User-Pairing Techniques for MIMO-NOMA in VLC Systems

In this paper, we evaluate the performance of multiple-input multiple-output (MIMO) communication systems applied with a non-orthogonal multiple access (NOMA)-based indoor visible light communication (VLC). We present two efficient user-pairing algorithms for NOMA in VLC, aiming to enhance achievable data rates effectively. Our investigation involves the application of three low-complexity power allocation techniques. Comparative analysis reveals performance enhancements when employing the proposed schemes, especially when contrasted with NOMA without user pairing and orthogonal frequency division multiple access (OFDMA). Additionally, we explore the performance of both algorithms in scenarios with both even and odd numbers of users. Simulation results demonstrate the superiority of NOMA in comparison to OFDMA.

Real-World Risk of Gastrointestinal Bleeding for Direct Oral Anticoagulants and Warfarin Users: A Distributed Network Analysis Using a Common Data Model.

Early studies on direct oral anticoagulants (DOACs) reported a higher risk of gastrointestinal bleeding (GIB) compared with warfarin; however, recent studies have reported a reduced risk. Therefore, this study was designed to evaluate the risk of GIB in users of DOAC and warfarin. Using a common data model, we investigated the comparative risk of GIB in subjects from eight hospitals who were newly prescribed DOACs or warfarin. We excluded subjects who had a prior history of GIB or had been prescribed both medications. After propensity score matching, we analyzed 3,347 matched pairs of new DOAC and new warfarin users. The risk of GIB in new DOAC users was comparable to that in new warfarin users (hazard ratio [HR], 0.95; 95% confidence interval [CI], 0.65 to 1.40; p=0.808). New DOAC users had a similar risk of GIB to new warfarin users among older patients >65 years (HR, 1.00; 95% CI, 0.69 to 1.52; p=0.997) and in older patients >75 years (HR, 1.21; 95% CI, 0.68 to 2.10; p=0.509). In addition, the risk of GIB was not significantly different between two groups according to sex. We also found that the risk of GIB in DOAC users was 26% lower in edoxaban or apixaban subgroups compared to rivaroxaban or dabigatran subgroups (HR, 0.74; 95% CI, 0.69 to 1.00; p=0.049). In real-world practice, the risk of GIB in new DOAC users is comparable to that in new warfarin users. In DOAC users, the risk of GIB was lower in edoxaban or apixaban subgroups than rivaroxaban or dabigatran subgroups.

Effective capacity of rate-splitting multiple access with channel estimation errors

In view of its advantages to adeptly reduce interference and low complexity, rate-splitting multiple access (RSMA) is emerging as an innovative framework for the next generation of the wireless communication networks. In this paper, we conduct the performance analysis of a two user RSMA network under delay constrains, taking channel estimation errors into account as well. Utilizing the effective capacity (EC) as our metric, we investigate the effects of delay on a pair of RSMA users. Specifically, we derive analytical expressions for the EC concerning both the near user (SRn) and the far user (SRf). Additionally, we offer asymptotic results under high signal-to-noise ratio (SNR) conditions. From our analysis, several noteworthy conclusions can be drawn and outlined below: (1) The effective capacities (ECs) of SRn and SRf exhibit improvement with SNR increasing, while at high SNR, the ECs of SRn and SRf converge to the constants. (2) Compared to the non-orthogonal multiple access, the considered RSMA network exhibits superior EC performance due to its inherent advantages in interference management. (3) The presence of channel estimation errors adversely affects EC performance of RSMA networks, with this impact being more pronounced in the high SNR regime.

Making sense of radiomics: insights on human–AI collaboration in medical interaction from an observational user study

Technologies based on “artificial intelligence” (AI) are transforming every part of our society, including healthcare and medical institutions. An example of this trend is the novel field in oncology and radiology called radiomics, which is the extracting and mining of large-scale quantitative features from medical imaging by machine-learning (ML) algorithms. This paper explores situated work with a radiomics software platform, QuantImage (v2), and interaction around it, in educationally framed hands-on trial sessions where pairs of novice users (physicians and medical radiology technicians) work on a radiomics task consisting of developing a predictive ML model with a co-present tutor. Informed by ethnomethodology and conversation analysis (EM/CA), the results show that learning about radiomics more generally and learning how to use this platform specifically are deeply intertwined. Common-sense knowledge (e.g., about meanings of colors) can interfere with the visual representation standards established in the professional domain. Participants' skills in using the platform and knowledge of radiomics are routinely displayed in the assessment of performance measures of the resulting ML models, in the monitoring of the platform's pace of operation for possible problems, and in the ascribing of independent actions (e.g., related to algorithms) to the platform. The findings are relevant to current discussions about the explainability of AI in medicine as well as issues of machinic agency.

Privacy Protection for Marginal-Sensitive Community Individuals Against Adversarial Community Detection Attacks

Social networks especially the social communities facilitate the rapid and rich social activities of all individuals in the world. However, advanced community detection brings serious privacy disclosure (e.g., whether two important and sensitive individuals belong to the same community?) to us. For instance, online plainclothes policemen can be regarded as marginal community users who are often in the same community initially and in need of penetrating into as many as possible different communities to collect illegal evidence of network criminals, but adversarial community inference which can maliciously disclose the sensitive user relationships within a target community will expose their privacy and lead to task failure. Thus, privacy protection for the marginal community users becomes an urgent issue which is still open so far. In this work, we aim to study the community privacy protection for target marginal individuals of a community against multiple adversarial community detection (ACD) attacks. First, we define the marginal community user hiding problem and propose a marginal user pair selection strategy. Second, to enhance the privacy effectiveness of conventional methods, we propose a deep graph learning approach to maximally find the minimum link perturbation cost. Finally, we conduct various community detection attacks on many real social graphs, and the experimental results show that our method can more effectively hide the marginal-sensitive user pairs than baselines.

On the Application of Quasi-Degradation to Network NOMA in Downlink CoMP Systems

The application of network non-orthogonal multiple access (N-NOMA) technique to coordinated multi-point (CoMP) systems has attracted significant attention due to its superior capability to improve connectivity and maintain reliable transmission for CoMP users simultaneously. Based on the concept of quasi-degraded channel for N-NOMA, this paper studies the precoding design for downlink N-NOMA scenarios with two base stations (BSs) equipped with multiple antennas. In specific, under quasi-degraded channels, simple linear precoding based N-NOMA can achieve the same minimal total transmission power as theoretically optimal but complicated dirty paper coding (DPC) scheme, when the users’ target rates and minimal transmission power of each BS are given. In this paper, the channel quasi-degradation (QD) condition is first rigorously derived for the scenario with single CoMP user and two NOMA users. The closed-form optimal precoders for N-NOMA under quasi-degraded channels are also provided. Then, based on QD condition, a novel hybrid N-NOMA (H-N-NOMA) scheme is proposed, which is a mixture of N-NOMA and conventional zero-forcing beamforming (ZFBF) scheme. Further, for the scenarios with more users, a low-complexity QD based user pairing (QDUP) algorithm is proposed, which is then combined with H-N-NOMA to make a novel scheme termed H-N-NOMA/QDUP into being. Numerical results are presented to reveal the impact factors on QD channels, and also demonstrate the superior performance of the proposed H-N-NOMA/QDUP scheme. It is shown that the proposed H-N-NOMA/QDUP scheme can effectively exploit the benefit of multi user diversity.

A clustering‐based user pairing scheme for downlink 3D non‐orthogonal multiple access‐based visible light communication systems

SummaryNon‐orthogonal multiple access (NOMA) has proven to be a very effective multiple access scheme to be employed in visible light communication (VLC) systems. NOMA scheme is capable of enhancing the spectral efficiency, sum rate performance, and various other performance parameters in VLC systems as compared to traditional orthogonal multiple access schemes. However, it is not practical to apply the concept of NOMA to all the users jointly. Therefore, the concept of user pairing has been introduced in literature to implement NOMA effectively so as to reduce the decoding order of successive interference cancellation (SIC) mechanism and complexity. In this paper, we have proposed a user pairing scheme based on clustering for downlink 3D NOMA‐based VLC systems. In this user pairing scheme, clustering is performed prior user pairing. The number of clusters are selected using K‐means algorithm and Elbow method, and the user allocation in a particular cluster is validated using artificial bee colony (ABC) optimization. In order to achieve high throughput, inter‐cluster user pairing is performed by forming pairs of two or three users with maximum channel gain difference in between them. The simulation results show that, for given values of signal‐to‐noise ratio (SNR), the proposed user pairing scheme offers higher average user data rates (AUDRs) as compared to the existing user pairing schemes for downlink NOMA‐based VLC systems. The energy efficiency (EE) and the bit error rate (BER) performance of the proposed user pairing scheme have also been studied.

Secure User Pairing and Power Allocation for Downlink Non-Orthogonal Multiple Access against External Eavesdropping.

We propose a secure user pairing (UP) and power allocation (PA) strategy for a downlink Non-Orthogonal Multiple Access (NOMA) system when there exists an external eavesdropper. The secure transmission of data through the downlink is constructed to optimize both UP and PA. This optimization aims to maximize the achievable sum secrecy rate (ASSR) while adhering to a limit on the rate for each user. However, this poses a challenge as it involves a mixed integer nonlinear programming (MINLP) problem, which cannot be efficiently solved through direct search methods due to its complexity. To handle this gracefully, we first divide the original problem into two smaller issues, i.e., an optimal PA problem for two paired users and an optimal UP problem. Next, we obtain the closed-form optimal solution for PA between two users and UP in a simplified NOMA system involving four users. Finally, the result is extended to a general 2K-user NOMA system. The proposed UP and PA method satisfies the minimum rate constraints with an optimal ASSR as shown theoretically and as validated by numerical simulations. According to the results, the proposed method outperforms random UP and that in a standard OMA system in terms of the ASSR and the average ASSR. It is also interesting to find that increasing the number of user pairs will bring more performance gain in terms of the average ASSR.

Effects of glucagon-like peptide-1 receptor agonists on liver-related and cardiovascular mortality in patients with type 2 diabetes

BackgroundPatients with type 2 diabetes (T2D) tend to have nonalcoholic fatty liver disease (NAFLD) with poorer prognosis. We performed this research to compare the risks of cardiovascular diseases, cirrhosis, liver-related mortality, and cardiovascular mortality between glucagon-like peptide-1 receptor agonist (GLP-1 RA) use and no-use in patients with T2D without viral hepatitis.MethodsFrom January 1, 2008, to December 31, 2018, we used propensity-score matching to identify 31,183 pairs of GLP-1 RA users and nonusers from Taiwan’s National Health Insurance Research Database. Multivariable-adjusted Cox proportional hazards models were used to examine the outcomes between the study and control groups.ResultsThe median (Q1, Q3) follow-up time for GLP-1 RA users and nonusers were 2.19 (1.35, 3.52) and 2.14 (1.19, 3.68) years, respectively. The all-cause mortality incidence rate was 5.67 and 13.06 per 1000 person-years for GLP-1 RA users and nonusers, respectively. Multivariable-adjusted analysis showed that GLP-1 RA use had significantly lower risks of all-cause mortality (aHR 0.48, 95%CI 0.43–0.53), cardiovascular events (aHR 0.92, 95%CI 0.86–0.99), cardiovascular death (aHR 0.57, 95%CI 0.45–0.72), and liver-related death (aHR 0.32, 95%CI 0.13–0.75). However, there was no significant difference in the risk of liver cirrhosis development, hepatic failure, and hepatocellular carcinoma compared to GLP-1 RA no-use.ConclusionsThis nationwide cohort study showed that GLP-1 RA use was associated with a significantly lower risk of all-cause mortality, cardiovascular events, and cardiovascular death in patients with T2D among Taiwan population. More prospective studies are warranted to verify our results.

ANALYSIS OF THE USER PAIRING NOMA SYSTEM OVER THE NAKAGAMI-M FADING CHANNEL CONDITIONS

The potential of non-orthogonal multiple access (NOMA) as a multiple access strategy for 5G and LTE upgrades has attracted much attention. In this study, we examine user pairing in NOMA strategy for multiple-input multiple-output (MIMO) users. The simulation results for near-near (N-N) and near-far (N-F) user pairing shames have been provided. The channel becomes time-selective after considering the node mobility situation. Furthermore, simulation curves demonstrate that adopting the user pairing approach reduces computing cost. The network's sum rate performance was further tested utilizing selection combining (SC) NOMA and time division for multiple access (TDMA). It is shown that when a user nearest to the base station is linked with the farthest user from the base station, the total sum rate dramatically increases. When the channel conditions between the two users are varied, the NOMA performs significantly better. The NOMA still surpasses TDMA in terms of sum rate when N-N and far-far (F-F) pairings are used, but the difference isn't significant. The SC-NOMA has a low performance when compared to TDMA. It was discovered that when the shape parameter is adjusted to two, the outage probability (OP) performance of three NOMA mobile users and a standard orthogonal multiple access (OMA) mobile user improved (multipath propagation scenario).

Lower Atrial Fibrillation Risk With Sodium-Glucose Cotransporter 2 Inhibitors Than With Dipeptidyl Peptidase-4 Inhibitors in Individuals With Type 2 Diabetes: A Nationwide Cohort Study.

Accumulating evidence shows that sodium-glucose cotransporter 2 inhibitors (SGLT2is) reduce adverse cardiovascular outcomes. However, whether SGLT2i, compared with other antidiabetic drugs, reduce the new development of atrial fibrillation (AF) is unclear. In this study, we compared SGLT2i with dipeptidyl peptidase-4 inhibitors (DPP-4is) in terms of reduction in the risk of AF in individuals with type 2 diabetes. We included 42,786 propensity score-matched pairs of SGLT2i and DPP-4i users without previous AF diagnosis using the Korean National Health Insurance Service database between May 1, 2016, and December 31, 2018. During a median follow-up of 1.3 years, SGLT2i users had a lower incidence of AF than DPP-4i users (1.95 vs. 2.65 per 1,000 person-years; hazard ratio [HR], 0.73; 95% confidence interval [CI], 0.55-0.97; p=0.028]). In individuals without heart failure, SGLT2i users was associated with a decreased risk of AF incidence (HR, 0.70; 95% CI, 0.52-0.94; p=0.019) compared to DPP-4i users. However, individuals with heart failure, SGLT2i users was not significantly associated with a change in risk (HR, 1.04; 95% CI, 0.44-2.44; p=0.936). In this nationwide cohort study of individuals with type 2 diabetes, treatment with SGLT2i was associated with a lower risk of AF compared with treatment with DPP-4i.

Joint user association and pairing in multi-uav-assisted noma networks: a decaying-epsilon thompson sampling framework

Joint user association and pairing in multi-uav-assisted noma networks: a decaying-epsilon thompson sampling framework

RIS-Assisted Cooperative Time-Division Multiple Access.

Reconfigurable intelligent surface-aided communication systems have been intensively investigated to improve capacity, coverage, and energy efficiency via optimal controlling of phase shifts for passive reflecting elements. However, there are few studies on cooperative transmission incorporating RIS in TDMA systems, because RIS reflects all the incident signals, and it inadvertently leads to a boost in interference signals. In this paper, we propose RIS-assisted cooperative time-division multiple access, in which the required SINR of all users is guaranteed as much as possible by opportunistic use of RIS for cooperative transmission. The proposed scheme's primary function is that some time slots, i.e., cooperative time slots, serve a pair of users, i.e., a strong- and a weak-channel-conditioned user, using RIS. To support this functionality, we propose scheduling for non-cooperative and cooperative time slots, user pairing for scheduled cooperative time slots, and transmit beamforming vector design for the pair of UEs in each cooperative time slot. The simulation and numerical results demonstrate that the proposed scheme guarantees QoS for all UE as much as possible and minimizes the remaining required capacity indicating the amount of capacity that was not achieved compared with the required capacity.