Improving Community Healthcare: A Qualitative Evaluation Of The Neighborhood Team Model In West Essex

A qualitative study was conducted to evaluate the Neighbourhood Team Model of the National Health Service in West Essex. The West Essex Clinical Commissioning Group (CCG) initiated the community healthcare-based neighbourhood teams in West Essex in October 2015. A neighbourhood team consists of all levels of health and social care providers but is concentrated on a smaller, local population. The proposed Neighbourhood Team Model was developed to allow providers to better deliver efficient patient-centred healthcare. For the past six months, the West Essex CCG encountered challenges in implementing the model to seven local areas within West Essex. To evaluate the progress of this initiative, 24 participants were purposely selected for interviews to assess the challenges and potential for the Neighbourhood Team Model. Participants consisted of key stakeholders from the West Essex CCG, primary care, the voluntary sector, social care, and one of the main health centres in West Essex, Princess Alexandra Hospital. Ten major themes, 30 sub-themes, and over 30 practical suggestions for the implementation of the model were identified through the interview transcripts

Deep Joint Source-Channel Coding for Wireless Image Transmission with Entropy-Aware Adaptive Rate Control

Adaptive rate control for deep joint source and channel coding (JSCC) is considered as an effective approach to transmit sufficient information in scenarios with limited communication resources. We propose a deep JSCC scheme for wireless image transmission with entropy-aware adaptive rate control, using a single deep neural network to support multiple rates and automatically adjust the rate based on the feature maps of the input image and their entropy, as well as the channel conditions. In particular, we maximize the entropy of the feature maps to increase the average information carried by each transmitted symbol during the training. We further decide which feature maps should be activated based on their entropy, which improves the efficiency of the transmitted symbols. We also propose a pruning module to remove less important pixels in the activated feature maps in order to further improve transmission efficiency. The experimental results demonstrate that our proposed scheme learns an effective rate control strategy that reduces the required channel bandwidth while preserving the quality of the reconstructed images

Microfiber-based polarization beam splitter and its application for passively mode-locked all-fiber laser

Nonlinear polarization evolution based on polarization beam splitter (PBS) is a classical technique for passive mode-locking of fiber lasers. Different from commonly used bulky PBS, in this paper all-fiber PBSs composed of two parallel coupled microfibers have been proposed and fabricated under the condition of appropriate microfiber diameter and coupling length. Using our fabricated microfiber PBSs, passively mode-locked all-fiber lasers have also been demonstrated. The results indicate that the microfiber-based PBS has advantages of simple fabrication, compact size, and most importantly, variable polarization extinction ratio and operation bandwidth. The all-fiber mode-locked lasers with the microfiber PBSs generating stable pulses at both 1.0 μm and 1.5 μm wavelength bands have comparable performance with their counterparts based on bulky PBSs. It may be a step towards true all-fiber mode-locked laser and other all-fiber systems

BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR

The recently proposed serialized output training (SOT) simplifies multi-talker automatic speech recognition (ASR) by generating speaker transcriptions separated by a special token. However, frequent speaker changes can make speaker change prediction difficult. To address this, we propose boundary-aware serialized output training (BA-SOT), which explicitly incorporates boundary knowledge into the decoder via a speaker change detection task and boundary constraint loss. We also introduce a two-stage connectionist temporal classification (CTC) strategy that incorporates token-level SOT CTC to restore temporal context information. Besides typical character error rate (CER), we introduce utterance-dependent character error rate (UD-CER) to further measure the precision of speaker change prediction. Compared to original SOT, BA-SOT reduces CER/UD-CER by 5.1%/14.0%, and leveraging a pre-trained ASR model for BA-SOT model initialization further reduces CER/UD-CER by 8.4%/19.9%.Comment: Accepted by INTERSPEECH 202

Ultrathin MgB2 films fabricated on Al2O3 substrate by hybrid physical-chemical vapor deposition with high Tc and Jc

Ultrathin MgB2 superconducting films with a thickness down to 7.5 nm are epitaxially grown on (0001) Al2O3 substrate by hybrid physical-chemical vapor deposition method. The films are phase-pure, oxidation-free and continuous. The 7.5 nm thin film shows a Tc(0) of 34 K, which is so far the highest Tc(0) reported in MgB2 with the same thickness. The critical current density of ultrathin MgB2 films below 10 nm is demonstrated for the first time as Jc ~ 10^6 A cm^{-2} for the above 7.5 nm sample at 16 K. Our results reveal the excellent superconducting properties of ultrathin MgB2 films with thicknesses between 7.5 and 40 nm on Al2O3 substrate.Comment: 7 pages, 4 figures, 2 table

Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound

3D ultrasound (US) is widely used due to its rich diagnostic information, portability and low cost. Automated standard plane (SP) localization in US volume not only improves efficiency and reduces user-dependence, but also boosts 3D US interpretation. In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously. Our contribution is two-fold. First, we equip the MARL with a one-shot neural architecture search (NAS) module to obtain the optimal agent for each plane. Specifically, Gradient-based search using Differentiable Architecture Sampler (GDAS) is employed to accelerate and stabilize the training process. Second, we propose a novel collaborative strategy to strengthen agents' communication. Our strategy uses recurrent neural network (RNN) to learn the spatial relationship among SPs effectively. Extensively validated on a large dataset, our approach achieves the accuracy of 7.05 degree/2.21mm, 8.62 degree/2.36mm and 5.93 degree/0.89mm for the mid-sagittal, transverse and coronal plane localization, respectively. The proposed MARL framework can significantly increase the plane localization accuracy and reduce the computational cost and model size.Comment: Early accepted by MICCAI 202

Dynamic immune status analysis of peripheral blood mononuclear cells in patients with Klebsiella pneumoniae bloodstream infection sepsis using single-cell RNA sequencing

BackgroundKlebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied.MethodsA total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages.ResultsDuring K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1β, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease’s stages, and the expression of IFN-γ gene was upregulated.ConclusionThe proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment

Bi-directional Mendelian randomization analysis provides evidence for the causal involvement of dysregulation of CXCL9, CCL11 and CASP8 in the pathogenesis of ulcerative colitis

Background and Aims Systemic inflammation is well recognised to be associated with ulcerative colitis [UC], but whether these effects are causal or consequential remains unclear. We aimed to define potential causal relationship of cytokine dysregulation with different tiers of evidence. Methods We first synthesised serum proteomic profiling data from two multicentred observational studies, in which a panel of systemic inflammatory proteins was analysed to examine their associations with UC risk. To further dissect observed associations, we then performed a bidirectional two-sample Mendelian randomisation [TSMR] analysis from both forward and reverse directions using five genome-wide association study [GWAS] summary level data for serum proteomic profiles and the largest GWAS of 28 738 European-ancestry individuals for UC risk. Results Pooled analysis of serum proteomic data identified 14 proteins to be associated with the risk of UC. Forward MR analysis using only cis-acting protein quantitative trait loci [cis-pQTLs] or trans-pQTLs further validated causal associations of two chemokines and the increased risk of UC: C-X-C motif chemokine ligand 9 [CXCL9] [OR 1.45, 95% CI 1.08, 1.95, p = 0.012] and C-C motif chemokine ligand 11 [CCL11] [OR 1.14, 95% CI 1.09, 1.18, p = 3.89 x 10(-10)]. Using both cis- and trans-acting pQTLs, an association of caspase-8 [CASP8] [OR 1.04, 95% CI 1.03, 1.05, p = 7.63 x 10(-19)] was additionally identified. Reverse MR did not find any influence of genetic predisposition to UC on any of these three inflammation proteins. Conclusion Pre-existing elevated levels of CXCL9, CCL11 and CASP8 may play a role in the pathogenesis of UC