Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization

Bayesian optimization (BO) is widely used for black-box optimization problems, and have been shown to perform well in various real-world tasks. However, most of the existing BO methods aim to learn the optimal solution, which may become infeasible when the parameter space is extremely large or the problem is time-sensitive. In these contexts, switching to a satisficing solution that requires less information can result in better performance. In this work, we focus on time-sensitive black-box optimization problems and propose satisficing Thompson sampling-based parallel Bayesian optimization (STS-PBO) approaches, including synchronous and asynchronous versions. We shift the target from an optimal solution to a satisficing solution that is easier to learn. The rate-distortion theory is introduced to construct a loss function that balances the amount of information that needs to be learned with sub-optimality, and the Blahut-Arimoto algorithm is adopted to compute the target solution that reaches the minimum information rate under the distortion limit at each step. Both discounted and undiscounted Bayesian cumulative regret bounds are theoretically derived for the proposed STS-PBO approaches. The effectiveness of the proposed methods is demonstrated on a fast-charging design problem of Lithium-ion batteries. The results are accordant with theoretical analyses, and show that our STS-PBO methods outperform both sequential counterparts and parallel BO with traditional Thompson sampling in both synchronous and asynchronous settings

Comparison of different momentum control variables on assimilating radar observations for the forecasts of a dispersive convective event

In this study, the effects of background error covariance (BE) using the stream function ψ and unbalanced velocity potential χu as momentum control variables (CV5 scheme) and BE using the velocity U and V as momentum control variables (CV7 scheme) on assimilating radar radial velocity and reflectivity data for short-term forecasts of dispersive convection in a weak environmental field are explored based on the weather research and forecasting model (WRF) model and its 3DVAR assimilation system. The 4 km resolution forecast samples are generated to formulate the CV5 and CV7 BE by the National Meteorological Center (NMC) method. The single-observation experiments reveal that the differences between the two BE statistics are mainly reflected on the momentum control variables. The increment of wind field from CV7 shows more small-scale local characteristics. Comparing with control experiment, real radar observation assimilation tests of CV5 and CV7 both improve the reflectivity and precipitation forecasts. But the CV7 scheme improves the forecasting of strong convective systems in weak environmental fields better than CV5. First, the CV7 scheme improves both reflectivity and dispersive precipitation forecasts and significantly suppresses the spurious precipitation forecasts when compared with the CV5 scheme. In addition, CV7 also significantly reduces the forecast errors of surface variables and the wind analysis from CV7 is more local. Further analysis shows that the CV7 improves the water vapor convergence conditions compared to the CV5 scheme, which may be the reason for its better performance in the subsequent forecasts

Inhibition of lactose crystallisation in the presence of galacto-oligosaccharide

peer-reviewedThe stabilization of lactose in the form of amorphous (i.e. non-crystalline form) is the basic requirement to maintain the quality of relevant food and pharmaceutical products. The physiochemical properties of amorphous lactose mixed with galacto-oligosaccharide (GOS) were investigated. Water sorption, glass transition temperature, and crystallisation behaviour of lactose in the present of GOS (1:1 w/w) were measured at various water activity (0.11–0.75 aw, 25 °C) and lactose mutarotation was also evaluated. All of them were compared with the physiochemical properties of trehalose-lactose (1:1 w/w). The addition of GOS to lactose increased the hygroscopicity of the mixture, as well as slightly increased the glass transition temperature compared to lactose alone. The critical water activity (at 0.68 aw) of lactose crystallisation was increased by the addition of GOS as compared to that of trehalose-lactose (1:1 w/w) (at 0.58 aw) or lactose alone (at 0.44 aw). The dramatical inhibition of lactose crystallisation with a lower crystallisation kinetic constant and the alternation of lactose crystal forms in the presence of GOS was observed as compared to the crystallisation behaviour of trehalose-lactose (1:1 w/w) and pure lactose at 0.68 and 0.75 aw, 25 °C. Without affecting its Tg, the significantly delayed crystallisation of lactose in GOS-lactose mixture (1:1 w/w) was more likely due to the change of lactose mutarotation. As comparing to trehalose that is an effective inhibitor, GOS has a stronger ability to prevent lactose from crystallisation in hydrous matrices

Microcirculatory changes identified by photoacoustic microscopy in patients with complex regional pain syndrome type I after stellate ganglion blocks

Complex regional pain syndrome (CRPS) is a chronic pain syndrome that causes intractable pain, disability, and poor quality of life for patients. The etiology and pathophysiology of CRPS are still poorly understood. Due to a lack of proper diagnostic tools, the prognosis of CRPS is primarily based on clinical observation. The objective of this work is to evaluate a new imaging modality, photoacoustic microscopy (PAM), for assisting diagnoses and monitoring the progress and treatment outcome of CRPS. Blood vasculature and oxygen saturation (sO_2) were imaged by PAM from eight adult patients with CRPS-1. Patients’ hands and cuticles were imaged both before and after stellate ganglion block (SGB) for comparison. For all patients, both vascular structure and sO_2 could be assessed by PAM. In addition, more vessels and stronger signals were observed after SGB. The results show that PAM can help diagnose and monitor CRPS

The mechanisms and diagnostic potential of lncRNAs, miRNAs, and their related signaling pathways in cervical cancer

Cervical cancer (CC), the fourth most prevalent type of cancer among women worldwide, is associated with high rates of morbidity and mortality. Due to the long period of latency in CC, most patients are already in the middle to late stages when initially diagnosed, which greatly reduces the clinical cure rate and quality of survival, thus resulting in poor outcomes. In recent years, with continuous exploration in the fields of bioinformatics and molecules, it has been found that ncRNAs, including miRNAs and lncRNAs, without the ability to translate proteins are capable of activating or inhibiting certain signaling pathways by targeting and modulating the level of expression of proteins involved in these signaling pathways. ncRNAs play important roles in assisting with diagnosis, drug administration, and prediction of prognosis during CC progression. As an entry point, the mechanisms of interaction between miRNAs, lncRNAs, and signaling pathways have long been a focus in basic research relating to CC, and numerous experimental studies have confirmed the close relationship of miRNAs, lncRNAs, and signaling pathways with CC development. Against this background, we summarize the latest advances in the involvement of lncRNA- and miRNA-related signaling pathways in the development of CC to provide guidance for CC treatment