Mover design and characteristics analysis of 2DoFDDIM

Two degree-of-freedom direct drive induction motor (2DoFDDIM), capable of rotary, linear and helical motion, has widespread application. A new mover structure is proposed, which is made from a hollow cylinder with copper cast in the axial slots and the circumferential slots on its surface. Then, three-dimensional finite element models of 2DoFDDIM are used to determine the performances of rotary, linear and helical motion developed by the motor. The results show that the new mover has a great improvement on the motor performances of all modes of motions compared with the initial mover. The researches on mover structure and characteristics of 2DoFDDIM present a new path of optimisation on 2DoFIM

In-context Autoencoder for Context Compression in a Large Language Model

We propose the In-context Autoencoder (ICAE) for context compression in a large language model (LLM). The ICAE has two modules: a learnable encoder adapted with LoRA from an LLM for compressing a long context into a limited number of memory slots, and a fixed decoder which is the target LLM that can condition on the memory slots for various purposes. We first pretrain the ICAE using both autoencoding and language modeling objectives on massive text data, enabling it to generate memory slots that accurately and comprehensively represent the original context. Then, we fine-tune the pretrained ICAE on a small amount of instruct data to enhance its interaction with various prompts for producing desirable responses. Our experimental results demonstrate that the ICAE learned with our proposed pretraining and fine-tuning paradigm can effectively produce memory slots with $4\times$ context compression, which can be well conditioned on by the target LLM to respond to various prompts. The promising results demonstrate significant implications of the ICAE for its novel approach to the long context problem and its potential to reduce computation and memory overheads for LLM inference in practice, suggesting further research effort in context management for an LLM. Our code and data will be released shortly.Comment: Work in progres

Cost-effectiveness of the Da Qing Diabetes Prevention program : a modelling study

Objective The Da Qing Diabetes Prevention program (DQDP) was a randomized lifestyle modification intervention conducted in 1986 for the prevention and control of type 2 diabetes in individuals with impaired glucose tolerance. The current study estimated long-term cost-effectiveness of the program based on the health utilities from the Chinese population. Methods A Markov Monte Carlo model was developed to estimate the impact of the intervention from the healthcare system perspective. The analysis was run over 30-year and lifetime periods and costs were estimated respectively as health management service costs. Baseline characteristics and intervention effects were assessed from the DQDP. Utilities and costs were generated from relevant literature. The outcome measures were program cost per quality-adjusted life-years (QALYs) gained and incremental cost-effectiveness ratio (ICER) of the intervention. Sensitivity analyses and threshold analyses were performed. Results Using a 30-year horizon, the intervention strategy was cost-saving and was associated with better health outcomes (increase of 0.74 QALYs per intervention participant). Using a lifetime horizon, the intervention strategy was cost-saving and was associated with additional 1.44 QALYs. Sensitivity analyses showed that the overall ICER was most strongly influenced by the hazard ratio of cardiovascular disease event. Conclusions The Da Qing lifestyle intervention in a Chinese population with impaired glucose tolerance is likely to translate into substantial economic value. It is cost-saving over a 30-year time and lifetime frame

A comparison study of geostatistical simulation for predicting soil texture

Non-Peer Reviewe

Circulating microRNA-92a and microRNA-21 as novel minimally invasive biomarkers for primary breast cancer

PURPOSE: MicroRNAs (miRNAs) play an essential role in breast malignant tumor development and progression. The development of clinically validated biomarkers for primary breast cancer (BC) has remained an insurmountable task despite other advances in the field of cancer molecular biology. The objective of this study is to investigate the differential expression of miRNAs and the potential of circulating microRNAs as novel primary breast cancer biomarkers. METHODS: Our analyses were performed on 48 tissue and 100 serum samples of patients with primary BC and a set of 20 control samples of healthy women, respectively. The relative expression of ten candidate miRNAs (miR-106b, miR-125b, miR-17, miR-185, miR-21, miR-558, miR-625, miR-665, miR-92a, and miR-93) from the results of four bioinformatics approaches and literature curation was measured by real-time quantitative reverse transcription PCR (qRT-PCR). RESULTS: The level of miR-92a was significantly lower, while miR-21 was higher, as previous reports, in tissue and serum samples of BC than that of healthy controls (p < 0.001). Logistic regression and receiver operating characteristic curve analyses revealed the significant and independent value (p < 0.001) of the miR-92a and miR-21 expression quantification in serums. Moreover, the comparison with the clinicopathologic data of the BC patients showed that decreased levels of miR-92a and increased levels of miR-21 were associated with tumor size and a positive lymph node status (p < 0.001). CONCLUSIONS: These findings suggest that many miRNAs expressions are altered in BC, whose expression profiling may provide a useful clue for the pathophysiological research. Circulating miR-92a has potential use as novel breast cancer biomarker, which is comparable to miR-21

The influence of nitrogen doping of the acceptor in orange–red thermally activated delayed fluorescence emitters and OLEDs

Funding: C. Si thanks the China Scholarship Council (201806890001). D.S acknowledges support from the Royal Academy of Engineering Enterprise Fellowship (EF2122-13106). The St Andrews team thanks EPSRC for financial support (EP/P010482/1). X.-H. Zhang acknowledges support from the National Natural Science Foundation of China (Grant Nos. 52130304, 51821002), Suzhou Key Laboratory of Functional Nano & Soft Materials, Collaborative Innovation Center of Suzhou Nano Science & Technology, the 111 Project.Nitrogen-containing polycyclic aromatic hydrocarbons (N-PAH) have been widely used as deep lowest unoccupied molecular orbital (LUMO) acceptors in donor-acceptor (D-A) red thermally activated delayed fluorescent (TADF) emitters and their use in organic light-emitting diodes. However, most of the studies have focused disparately on donor/acceptor combinations to yield efficient emitters, while it is rare that there is a methodological study to investigate the influence of the nitrogen (N) doping ratios on the ground and excited states of PAH acceptors. Here, we report a family of four different N-PAH acceptors containing different numbers of nitrogen atoms within the N-PAH and their use in D-A TADF emitters, DMACBP, DMACPyBP, DMACBPN and DMACPyBPN, when coupled to the same donor, 9,9-dimethyl-9,10-dihydroacridine (DMAC). As the nitrogen content in the acceptor increases the LUMO becomes progressively more stabilized while the singlet-triplet energy gap (ΔEST) decreases and the rate constant for reverse intersystem crossing (kRISC) increases. In particular, introducing nitrogen at the 10-position of the dibenzo[a,c]phenazine (BP) leads to a more than ten-fold enhancement in kRISC in DMACPyBP and DMACPyBPN compared to DMACBP and DMACBPN. Among the OLEDs with all four emitters that with DMACBPN demonstrates the highest EQEmax of 19.4% at an emission peak of 588 nm. while the deepest red emitting device employed DMACPyBPN (λEL = 640 nm) with an EQEmax of 5.4%.Publisher PDFPeer reviewe