No abstract

Prolonged mechanical ventilation (PMV) is associated with poor outcomes and a high economic cost. The association between protein intake and PMV has rarely been investigated in previous studies. This study aimed to investigate the impact of protein intake on weaning from mechanical ventilation. Patients with the PMV (mechanical ventilation ≥6 h/day for ≥21 days) at our hospital between December 2020 and April 2022 were included in this study. Demographic data, nutrition records, laboratory data, weaning conditions, and survival data were retrieved from the patient’s electronic medical records. A total of 172 patients were eligible for analysis. The patients were divided into two groups: weaning success (n = 109) and weaning failure (n = 63). Patients with daily protein intake greater than 1.2 g/kg/day had significant shorter median days of ventilator use than those with less daily protein intake (36.5 vs. 114 days, respectively, p < 0.0001). Daily protein intake ≥1.065 g/kg/day (odds ratio: 4.97, p = 0.033), daily protein intake ≥1.2 g/kg/day (odds ratio: 89.07, p = 0.001), improvement of serum albumin (odds ratio: 3.68, p = 0.027), and BMI (odds ratio: 1.235, p = 0.014) were independent predictor for successful weaning. The serum creatinine level in the 4th week remained similar in patients with daily protein intake either >1.065 g/kg/day or >1.2 g/kg/day (p = 0.5219 and p = 0.7796, respectively). Higher protein intake may have benefits in weaning in patients with PMV and had no negative impact on renal function.

Information dissemination dynamics is an important performance index for characterizing the speed and scope of information dissemination in a network. Several analytical models have been proposed to estimate the information dissemination dynamics for social networks adopting a susceptible-infected information propagation model and having a constant informed rate. This letter extends existing model to analyze the social networks adopting either a susceptible-infected or an independentcascade information propagation model and having a timevarying informed rate. Validated by simulations, our model demonstrates its flexibility and applicability to approximate the complicated propagation behaviors of advertisement-like or malware-like information.

A human centric communication network (HCCN) is a communication network offering human centric (or, socialnetwork-based) mobile Internet services. This paper proposes a three-layer network architecture to model the relationship among users, their social groups, and the serving radio access networks for HCCN. Based on this model, several advertising techniques in HCCN are investigated. Simulation results showed the effectiveness of four algorithms in different application scenarios.

One way of fully exploiting the channel capacity in multiple input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is to deploy precoding vectors derived from SVD to form parallel data pipes. Optimal precoding requires accurate channel state information for each OFDM subcarrier. This paper proposes a limited channel decomposition architecture by using an interpolation method to reduce the computation cost of precoding. In this scheme, only on the pilot subcarriers the estimated channel information is used to get SVD decomposition results, and precoding vectors on other subcarriers are obtained by an orthogonal interpolation method. The interpolation relies on an important assumption that the singular modes on adjacent subcarriers change approximately in a linear way. Numerical simulations suggests that with appropriate settings, e.g., proper FFT size and interpolation gap etc., the proposed scheme can reduce computation efficiently while only sacrifice little performance.