A new interference management strategy is proposed to enhance the overall capacity of cellular networks (CNs) and device-to-device (D2D) systems. We consider M out of K cellular user equipments ...(CUEs) and one D2D pair exploiting the same resources in the uplink (UL) period under the assumption of M multiple antennas at the base station (BS). First, we use the conventional mechanism which limits the maximum transmit power of the D2D transmitter so as not to generate harmful interference from D2D systems to CNs. Second, we propose a δ D -interference limited area (ILA) control scheme to manage interference from CNs to D2D systems. The method does not allow the coexistence (i.e., use of the same resources) of CUEs and a D2D pair if the CUEs are located in the δ D -ILA defined as the area in which the interference to signal ratio (ISR) at the D2D receiver is greater than the predetermined threshold, δ D . Next, we analyze the coverage of the δ D -ILA and derive the lower bound of the ergodic capacity as a closed form. Numerical results show that the δ D -ILA based D2D gain is much greater than the conventional D2D gain, whereas the capacity loss to the CNs caused by using the δ D -ILA is negligibly small.
We consider energy harvesting cognitive radio networks in which a secondary transmitter harvests energy from ambient sources or wireless power transfer systems while opportunistically accessing the ...spectrum licensed to the primary network. The primary traffic is modeled as a time-homogeneous discrete Markov process, and the secondary transmitter may not be able to operate continuously due to sporadic and unstable energy sources. At the beginning of each time slot, the secondary transmitter thus needs to determine whether to remain idle so as to conserve energy, or to execute spectrum sensing to acquire knowledge of the current spectrum occupancy state. It also needs to configure the spectrum sensor detection threshold to achieve an effective tradeoff between false alarms and misdetections. This sequential decision-making, done to maximize the expected total throughput, requires the joint design of a spectrum sensing policy and a detection threshold under the energy causality and collision constraints. We formulate this stochastic optimization problem as a constrained partially observable Markov decision process (POMDP), and then convert it to a computationally tractable unconstrained POMDP. Numerical results show that the proposed approach enables efficient usage of the harvested energy by exploiting the temporal correlation of the primary traffic.
We consider a cognitive radio network with an energy-harvesting secondary transmitter to improve both energy efficiency and spectral efficiency. The goal of this paper is to determine an optimal ...spectrum sensing policy that maximizes the expected total throughput subject to an energy causality constraint and a collision constraint. The energy causality constraint comes from the fact that the total consumed energy should be equal to or less than the total harvested energy, while the collision constraint is required to protect the primary user. We first show that the system can be divided into a spectrum-limited regime and an energy-limited regime depending on where the detection threshold for the spectrum sensor lies. Assuming infinite battery capacity, we derive the optimal detection threshold that maximizes the expected total throughput subject to the energy causality constraint and the collision constraint. Analytical and numerical results show that the system is energy-limited if the energy arrival rate is lower than the expected energy consumption for a single spectrum access. They also show that a decreasing probability of accessing the occupied spectrum does not always result in decreased probability of accessing the idle spectrum in the energy-limited regime.
We consider energy harvesting cognitive radio networks to improve both energy efficiency and spectral efficiency. The goal of this paper is to analyze the theoretically achievable throughput of the ...secondary transmitter, which harvests energy from ambient sources or wireless power transfer systems while opportunistically accessing the spectrum licensed to the primary network. By modeling the temporal correlation of the primary traffic according to a time-homogeneous discrete Markov process, we derive the upper bound on the achievable throughput as a function of the energy arrival rate, the temporal correlation of the primary traffic, and the detection threshold for a spectrum sensor. The optimal detection threshold is then derived to maximize the upper bound on the achievable throughput under an energy causality constraint and a collision constraint. The energy causality constraint mandates that the total consumed energy should not exceed the total harvested energy, while the collision constraint is required to protect the primary network from secondary transmission. Analytical results show the temporal correlation of the primary traffic to enable efficient usage of the harvested energy by preventing the secondary transmitter from accessing the spectrum that may be occupied by the primary network.
•The MT-DTI deep learning model was used to identify potent drugs for SARS-CoV-2.•Atazanavir, remdesivir, and Kaletra were predicted to inhibit SARS-CoV-2.•Rapamycin and tiotropium bromide may also ...be effective for SARS-CoV-2.
The infection of a novel coronavirus found in Wuhan of China (SARS-CoV-2) is rapidly spreading, and the incidence rate is increasing worldwide. Due to the lack of effective treatment options for SARS-CoV-2, various strategies are being tested in China, including drug repurposing. In this study, we used our pre-trained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of SARS-CoV-2. The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, showing an inhibitory potency with Kd of 94.94 nM against the SARS-CoV-2 3C-like proteinase, followed by remdesivir (113.13 nM), efavirenz (199.17 nM), ritonavir (204.05 nM), and dolutegravir (336.91 nM). Interestingly, lopinavir, ritonavir, and darunavir are all designed to target viral proteinases. However, in our prediction, they may also bind to the replication complex components of SARS-CoV-2 with an inhibitory potency with Kd < 1000 nM. In addition, we also found that several antiviral agents, such as Kaletra (lopinavir/ritonavir), could be used for the treatment of SARS-CoV-2. Overall, we suggest that the list of antiviral drugs identified by the MT-DTI model should be considered, when establishing effective treatment strategies for SARS-CoV-2.
We consider an energy-harvesting cognitive radio system where the secondary transmitter harvests energy. This system operates under an energy causality constraint mandating that the average energy ...consumption must not exceed the average harvested energy, and a collision constraint mandating the protection of the primary system. The purpose of this paper is to identify the optimal pairing of the sensing duration and the energy detector's sensing threshold in order to maximize the average throughput of the secondary network. Since the sensing duration and sensing threshold are intertwined with the energy causality constraint, they need to be redesigned with the purpose of conserving energy in mind. Hence, the sensing duration must be shorter while still satisfying the collision constraint. The numerical results show that the optimal sensing duration is determined based on which constraint, collision or energy causality, needs to have priority. In addition, the simulation results show a pairing of the optimal sensing duration and sensing threshold provided by the coordination between the two constraints, which gives insight into how to design them.
Bidirectional communication systems based on full-duplex transmission have been proposed as a way to increase the ergodic capacity of multiantenna two-way networks. This type of system enables ...simultaneous exchange of data between two nodes via bidirectional use of spatial resources. However, when channel estimation error is present, each node experiences both desired-channel interference (DI) and echo-channel interference (EI). This paper investigates the effect of channel estimation errors on the ergodic capacities for bidirectional full-duplex transmission (BFD) using one of two combining schemes: maximal-ratio combining (MRC) or optimum combining (OC). We derive the ergodic capacities as closed-form expressions and quantify the effect of channel estimation errors on ergodic capacities for BFD with MRC (BFD-MRC) or OC (BFD-OC). Numerical results demonstrate that full-duplex transmission in two-way networks is an attractive option when channel estimation error is present.
We conducted a systematic review and meta-analysis of studies to quantify the association between body mass index (BMI) and the risks of all-cause and cardiovascular mortality in patients with type 2 ...diabetes.
We included studies assessing the impact of BMI on all-cause and cardiovascular mortality in patients with type 2 diabetes. Data were combined using a random-effects dose-response model.
Sixteen cohort studies on all-cause mortality (n = 445,125) and two studies on cardiovascular mortality (n = 92,841) were evaluated in the meta-analysis. A non-linear association was observed between BMI and all-cause mortality among patients with type 2 diabetes. With a BMI nadir of 28-30 kg/m2, the risk of all-cause mortality displayed a U-shaped increase. With a BMI nadir of 29-31 kg/m2, the risk of cardiovascular mortality exhibited a gradual non-linear increase for BMI > 31 kg/m2. Subgroup analyses suggested that study location, diabetes duration, and smoking history may have contributed to heterogeneity among the studies.
An obesity paradox exists for patients with type 2 diabetes with respect to all-cause and cardiovascular mortality. Study location, diabetes duration, and smoking history might contribute to heterogeneity among obesity paradox studies of patients with type 2 diabetes.
To compare short-term surgical outcomes including financial cost of robotic and laparoscopic gastrectomy.
Despite a lack of supporting evidence, robotic surgery has been increasingly adopted as a ...minimally invasive modality for the treatment of gastric cancer because of its assumed technical superiority over conventional laparoscopy.
A prospective, multicenter comparative study was conducted. Patients were matched according to the surgeon, extent of gastric resection, and sex. The primary endpoint was morbidity and mortality. Outcomes were analyzed on an intention-to-treat and per-protocol basis.
A total of 434 patients were enrolled for treatment with either robotic (n = 223) or laparoscopic (n = 211) gastrectomy for intention-to-treat analysis, and a total of 370 patients (n = 185 per treatment) were compared in per-protocol analysis. Results were similar between both analyses. In per-protocol analysis, both groups showed similar overall complication rates (robotic = 11.9% vs laparoscopic = 10.3%) and major complication rates (robotic = 1.1% vs laparoscopic = 1.1%) with no operative mortality in either group. Patients treated with robotic surgery showed significantly longer operative time (robotic = 221 minutes vs laparoscopic = 178 minutes; P < 0.001) and significantly higher total costs (robotic = US$13,432 vs laparoscopic = US$8090; P < 0.001), compared with those who underwent laparoscopic gastrectomy. No significant differences between groups were noted in estimated blood loss, rates of open conversion, diet build-up, or length of hospital stay.
The use of robotic systems is assumed to provide a technically superior operative environment for minimally invasive surgery. However, our analysis of perioperative surgical outcomes indicated that robotic gastrectomy is not superior to laparoscopic gastrectomy. Clinical trials identification: NCT01309256.
Although proximal gastrectomy (PG) provides superior nutritional outcomes over total gastrectomy (TG) in upper-third early gastric cancer (EGC), surgeons are reluctant to perform PG due to the high ...rate of postoperative reflux. This meta-analysis aimed to comprehensively compare operative outcomes, nutritional outcomes, and quality of life-related complications between TG and PG performed with esophagogastrostomy (EG), jejunal interposition, or double-tract reconstruction (DTR) to reduce reflux after PG. After searching PubMed, Embase, Medline, and Web of Science databases, 25 studies comparing PG with TG in upper-third EGC published up to October 2020 were identified. PG with DTR was similar to TG regarding operative outcomes. Patients who underwent PG with DTR had less weight reduction (weighted mean difference WMD 4.29; 95% confidence interval 0.51-8.07), reduced hemoglobin loss (WMD 5.74; 2.56-8.93), and reduced vitamin B
supplementation requirement (odds ratio OR 0.06; 0.00-0.89) compared to patients who underwent TG. PG with EG caused more reflux (OR 5.18; 2.03-13.24) and anastomotic stenosis (OR 3.94; 2.40-6.46) than TG. However, PG with DTR was similar to TG regarding quality of life-related complications including reflux, anastomotic stenosis, and leakage. Hence, PG with DTR can be recommended for patients with upper-third EGC considering its superior postoperative nutritional outcomes.
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