Randomised clinical study: inulin short-chain fatty acid esters for targeted delivery of short-chain fatty acids to the human colon

Summary Background Short-chain fatty acids (SCFA) produced through fermentation of nondigestible carbohydrates by the gut microbiota are associated with positive metabolic effects. However, well-controlled trials are limited in humans. Aims To develop a methodology to deliver SCFA directly to the colon, and to optimise colonic propionate delivery in humans, to determine its role in appetite regulation and food intake. Methods Inulin SCFA esters were developed and tested as site-specific delivery vehicles for SCFA to the proximal colon. Inulin propionate esters containing 0–61 wt% (IPE-0–IPE-61) propionate were assessed in vitro using batch faecal fermentations. In a randomised, controlled, crossover study, with inulin as control, ad libitum food intake (kcal) was compared after 7 days on IPE-27 or IPE-54 (10 g/day all treatments). Propionate release was determined using 13C-labelled IPE variants. Results In vitro, IPE-27–IPE-54 wt% propionate resulted in a sevenfold increase in propionate production compared with inulin (P < 0.05). In vivo, IPE-27 led to greater 13C recovery in breath CO2 than IPE-54 (64.9 vs. 24.9%, P = 0.001). IPE-27 also led to a reduction in energy intake during the ad libitum test meal compared with both inulin (439.5 vs. 703.9 kcal, P = 0.025) and IPE-54 (439.5 vs. 659.3 kcal, P = 0.025), whereas IPE-54 was not significantly different from inulin control. Conclusions IPE-27 significantly reduced food intake suggesting colonic propionate plays a role in appetite regulation. Inulin short-chain fatty acid esters provide a novel tool for probing the diet–gut microbiome–host metabolism axis in human

Second trimester inflammatory and metabolic markers in women delivering preterm with and without preeclampsia.

ObjectiveInflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia.Study designA sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios.ResultsHigher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia.ConclusionsAmong women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth

Non-Diversifiable Volatility Risk and Risk Premiums at Earnings Announcements

This study seeks to determine whether earnings announcements pose non-diversifiable volatility risk that commands a risk premium. We find that investors anticipate some earnings announcements to convey news that increases market return volatility and pay a premium to hedge this non-diversifiable risk. In particular, we find evidence of risk premiums embedded in prices of firms' traded options that are significantly positively associated with the extent to which the firms' earnings announcements pose non-diversifiable volatility risk. In addition, we find that volatility risk premiums are concentrated among bellwether firms and result in predictable variation in option straddle returns around earnings announcements. Taken together, our findings show that some earnings announcements pose non-diversifiable volatility risk that commands a risk premium

Joint Sparsity and Low-Rank Minimization for Reconfigurable Intelligent Surface-Assisted Channel Estimation

Reconfigurable intelligent surfaces (RISs) have attracted extensive attention in millimeter wave (mmWave) systems because of the capability of configuring the wireless propagation environment. However, due to the existence of a RIS between the transmitter and receiver, a large number of channel coefficients need to be estimated, resulting in more pilot overhead. In this paper, we propose a joint sparse and low-rank based two-stage channel estimation scheme for RIS-assisted mmWave systems. Specifically, we first establish a low-rank approximation model against the noisy channel, fitting in with the precondition of the compressed sensing theory for perfect signal recovery. To overcome the difficulty of solving the low-rank problem, we propose a trace operator to replace the traditional nuclear norm operator, which can better approximate the rank of a matrix. Furthermore, by utilizing the sparse characteristics of the mmWave channel, sparse recovery is carried out to estimate the RIS-assisted channel in the second stage. Simulation results show that the proposed scheme achieves significant performance gain in terms of estimation accuracy compared to the benchmark schemes

Throughput Maximization for RIS-assisted UAV-enabled WPCN

This paper investigates a reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN). In the system, a UAV acts as a hybrid access point (HAP) to charge users in the downlink (DL) and receive messages in the uplink (UL). In particular, the RIS is exploited to significantly enhance the efficiency of both the DL and UL transmission. Our objective is to enhance the minimum throughput among all ground users by jointly optimizing the horizontal location of UAVs, the transmit power of users, transmission time allocation, and passive beamforming vectors at the RIS. To address this problem, we present an alternating optimization-based algorithm with low complexity to decompose the problem into four subproblems and solve them sequentially. In particular, we derive a lower bound of the composite channel gain to tighten the constraints and employ successive convex approximation (SCA) to optimize the horizontal location of the UAV. The transmit power closed-form optimum solutions are then obtained, and the problem of time allocation is reformulated as a linear programming problem. Finally, we optimize the passive beamforming vectors by adopting semi-definite relaxation (SDR). The effectiveness of the algorithm is supported by numerical results, which also demonstrate that the RIS-assisted UAV-enabled WPCN outperforms the traditional WPCN in terms of the minimum throughput

Energy Efficiency Optimization for a Multiuser IRS-aided MISO System with SWIPT

Combining simultaneous wireless information and power transfer (SWIPT) and an intelligent reflecting surface (IRS) is a feasible scheme to enhance energy efficiency (EE) performance. In this paper, we investigate a multiuser IRS-aided multiple-input single-output (MISO) system with SWIPT. For the purpose of maximizing the EE of the system, we jointly optimize the base station (BS) transmit beamforming vectors, the IRS reflective beamforming vector, and the power splitting (PS) ratios, while considering the maximum transmit power budget, the IRS reflection constraints, and the quality of service (QoS) requirements containing the minimum data rate and the minimum harvested energy of each user. The formulated EE maximization problem is non-convex and extremely complex. To tackle it, we develop an efficient alternating optimization (AO) algorithm by decoupling the original nonconvex problem into three subproblems, which are solved iteratively by using the Dinkelbach method. In particular, we apply the successive convex approximation (SCA) as well as the semi-definite relaxation (SDR) techniques to solve the non-convex transmit beamforming and reflective beamforming optimization subproblems. Simulation results verify the effectiveness of the AO algorithm as well as the benefit of deploying IRS for enhancing the EE performance compared with the benchmark schemes

Reconfigurable Intelligent Surface-Assisted B5G/6G Wireless Communications: Challenges, Solution and Future Opportunities

The power consumption and hardware cost are two of the main challenges for realizing beyond fifth-generation (B5G) and sixth-generation (6G) wireless communications. Recently, the emerging reconfigurable intelligent surface (RIS) have been recognized as a promising tool for enhancing the propagation environment and improving the spectral efficiency of wireless communications by controlling low-cost passive reflecting elements. However, current cellular communication were designed on the basis of conventional communication theories, significantly restrict the development of RIS-assisted B5G/6G technologies and lead to severe limitations. In this article, we discuss RIS-assisted channel estimation issues involved in B5G/6G communications including channel state information (CSI) acquisition, imperfect cascade CSI for beamforming design and co-channel interference coordination, and develop a few possible solutions or visionary technologies to promote the development of B5G/6G. Finally, potential research opportunities are discussed

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Reconfigurable-Intelligent-Surface-Assisted B5G/6G Wireless Communications: Challenges, Solution, and Future Opportunities

Power consumption and hardware cost are two of the main challenges for realizing beyond fifth generation (B5G) and sixth generation (6G) wireless communications. Recently, the emerging reconfigurable intelligent surface (RIS) has been recognized as a promising tool for enhancing the propagation environment and improving the spectral efficiency of wireless communications by controlling low-cost passive reflecting elements. However, current cellular communications were designed on the basis of conventional communication theories, significantly restricting the development of RIS-assisted B5G/6G technologies and leading to severe limitations. In this article, we discuss RIS-assisted channel estimation issues involved in B5G/6G communications including channel state information (CSI) acquisition, imperfect cascade CSI for beamforming design, and co-channel interference coordination, and develop a few possible solutions or visionary technologies to promote the development of B5G/6G. Finally, potential research opportunities are discussed