Prevalence And Genetic Determinants Of Vancomycin Resistance Of Clostridioides Difficile Isolates In Connecticut

AbstractIntroduction: The emergence of vancomycin-resistant strains of C. difficile has become a growing concern, as it can lead to treatment failure and increased morbidity and mortality. In this study, we aimed to investigate the prevalence and mechanisms of vancomycin resistance in C. difficile isolates in Connecticut from patients with confirmed C. difficile infection at Yale New Haven Hospital. Methods: We collected 89 stool samples from patients with confirmed C. difficile infection, isolated C. difficile, and performed susceptibility testing on the isolates using the E-strip test method. Isolates with an MIC value below 4 μg/ml were classified as susceptible and isolates with an MIC value above 4 μg/ml were classified as resistant. Whole-genome sequencing (WGS) and gene analysis was performed on 19 isolates and the samples were screened for the presence of vancomycin resistance genes. Results: Antimicrobial susceptibility results showed that the majority of isolates (80/89) are vancomycin susceptible (MIC \u3c 4 μg/ml). Of the remaining 9 vancomycin-resistant isolates, only one had extreme high-level resistance (\u3e256 µg/mL), while the other 8 isolates had low-level resistance. However, we found that only two of the 8 low-level resistant isolates were C. difficile, while the other 6 were either mixed cultures or mis-identified, primarily Enterococcus faecalis (5 isolates). Conclusion: The majority of C. difficile strains are susceptible to vancomycin. The apparent high prevalence of high-level vancomycin-resistant C. difficile may have resulted due to isolation techniques that mis-identify C. difficile. Our study highlights the need for improved methods of isolating C. difficile from stool samples and the importance of implementing proper antimicrobial stewardship practices and surveillance to combat the growing threat of antibiotic resistance in C. difficile infections

Novel data association methods for online multiple human tracking

PhD ThesisVideo-based multiple human tracking has played a crucial role in many applications such as intelligent video surveillance, human behavior analysis, and health-care systems. The detection based tracking framework has become the dominant paradigm in this research eld, and the major task is to accurately perform the data association between detections across the frames. However, online multiple human tracking, which merely relies on the detections given up to the present time for the data association, becomes more challenging with noisy detections, missed detections, and occlusions. To address these challenging problems, there are three novel data association methods for online multiple human tracking are presented in this thesis, which are online group-structured dictionary learning, enhanced detection reliability and multi-level cooperative fusion. The rst proposed method aims to address the noisy detections and occlusions. In this method, sequential Monte Carlo probability hypothesis density (SMC-PHD) ltering is the core element for accomplishing the tracking task, where the measurements are produced by the detection based tracking framework. To enhance the measurement model, a novel adaptive gating strategy is developed to aid the classi cation of measurements. In addition, online group-structured dictionary learning with a maximum voting method is proposed to estimate robustly the target birth intensity. It enables the new-born targets in the tracking process to be accurately initialized from noisy sensor measurements. To improve the adaptability of the group-structured dictionary to target appearance changes, the simultaneous codeword optimization (SimCO) algorithm is employed for the dictionary update. The second proposed method relates to accurate measurement selection of detections, which is further to re ne the noisy detections prior to the tracking pipeline. In order to achieve more reliable measurements in the Gaussian mixture (GM)-PHD ltering process, a global-to-local enhanced con dence rescoring strategy is proposed by exploiting the classi cation power of a mask region-convolutional neural network (R-CNN). Then, an improved pruning algorithm namely soft-aggregated non-maximal suppression (Soft-ANMS) is devised to further enhance the selection step. In addition, to avoid the misuse of ambiguous measurements in the tracking process, person re-identi cation (ReID) features driven by convolutional neural networks (CNNs) are integrated to model the target appearances. The third proposed method focuses on addressing the issues of missed detections and occlusions. This method integrates two human detectors with di erent characteristics (full-body and body-parts) in the GM-PHD lter, and investigates their complementary bene ts for tracking multiple targets. For each detector domain, a novel discriminative correlation matching (DCM) model for integration in the feature-level fusion is proposed, and together with spatio-temporal information is used to reduce the ambiguous identity associations in the GM-PHD lter. Moreover, a robust fusion center is proposed within the decision-level fusion to mitigate the sensitivity of missed detections in the fusion process, thereby improving the fusion performance and tracking consistency. The e ectiveness of these proposed methods are investigated using the MOTChallenge benchmark, which is a framework for the standardized evaluation of multiple object tracking methods. Detailed evaluations on challenging video datasets, as well as comparisons with recent state-of-the-art techniques, con rm the improved multiple human tracking performance

Cross-Task Representation Learning for Anatomical Landmark Detection

Recently, there is an increasing demand for automatically detecting anatomical landmarks which provide rich structural information to facilitate subsequent medical image analysis. Current methods related to this task often leverage the power of deep neural networks, while a major challenge in fine tuning such models in medical applications arises from insufficient number of labeled samples. To address this, we propose to regularize the knowledge transfer across source and target tasks through cross-task representation learning. The proposed method is demonstrated for extracting facial anatomical landmarks which facilitate the diagnosis of fetal alcohol syndrome. The source and target tasks in this work are face recognition and landmark detection, respectively. The main idea of the proposed method is to retain the feature representations of the source model on the target task data, and to leverage them as an additional source of supervisory signals for regularizing the target model learning, thereby improving its performance under limited training samples. Concretely, we present two approaches for the proposed representation learning by constraining either final or intermediate model features on the target model. Experimental results on a clinical face image dataset demonstrate that the proposed approach works well with few labeled data, and outperforms other compared approaches.Comment: MICCAI-MLMI 202

CluCDD:Contrastive Dialogue Disentanglement via Clustering

A huge number of multi-participant dialogues happen online every day, which leads to difficulty in understanding the nature of dialogue dynamics for both humans and machines. Dialogue disentanglement aims at separating an entangled dialogue into detached sessions, thus increasing the readability of long disordered dialogue. Previous studies mainly focus on message-pair classification and clustering in two-step methods, which cannot guarantee the whole clustering performance in a dialogue. To address this challenge, we propose a simple yet effective model named CluCDD, which aggregates utterances by contrastive learning. More specifically, our model pulls utterances in the same session together and pushes away utterances in different ones. Then a clustering method is adopted to generate predicted clustering labels. Comprehensive experiments conducted on the Movie Dialogue dataset and IRC dataset demonstrate that our model achieves a new state-of-the-art result.Comment: 5 page

3D-Hog Embedding Frameworks for Single and Multi-Viewpoints Action Recognition Based on Human Silhouettes

This paper has been presented at : 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)Given the high demand for automated systems for human action recognition, great efforts have been undertaken in recent decades to progress the field. In this paper, we present frameworks for single and multi-viewpoints action recognition based on Space-Time Volume (STV) of human silhouettes and 3D-Histogram of Oriented Gradient (3D-HOG) embedding. We exploit fast-computational approaches involving Principal Component Analysis (PCA) over the local feature spaces for compactly describing actions as combinations of local gestures and L 2 -Regularized Logistic Regression (L 2 -RLR) for learning the action model from local features. Outperforming results on Weizmann and i3DPost datasets confirm efficacy of the proposed approaches as compared to the baseline method and other works, in terms of accuracy and robustness to appearance changes

An experimental investigation on the effect of ferrofluids on the efficiency of novel parabolic trough solar collector under laminar flow conditions

The paper is related to the use of magnetic nanofluids (ferrofluids) in a direct absorption solar parabolic trough collectors enhances thermal efficiency compared to conventional solar collectors. By applying the right magnetic intensity and magnetic field direction, the thermal conductivity of the fluid increased higher than typical nanofluids. Moreover, the ferrofluids exhibit excellent optical properties. The external magnetic source is installed to alter the thermos-physical properties of the fluid, and the absorber tube does not have selective surface allowing ferrofluids to absorb the incoming solar irradiance directly. In this paper, an experimental investigation of the performance of direct absorption solar collector using ferrofluids as an absorber. Various nanoparticle concentrations 0% to 1vol% at the operational temperatures between 19°C and 40°C were used in the current study. The results show that using ferrofluids as a heat transfer fluid increases the efficiency of solar collectors. In the presence of the external magnetic field, the solar collector efficiency increases to the maximum, 25% higher than the conventional parabolic trough. At higher temperatures, the ferrofluids show much better efficiency than conventional heat transfer fluid. The study indicated that nanofluids, even of low-content, have good absorption of solar radiation, and can improve the outlet temperatures and system efficiencies

The treatment practices for anterior urethral strictures in China: A case-based survey

ObjectiveTo investigate the treatment concept of Chinese urologists for anterior urethral strictures based on actual cases.MethodsA self-designed case-based questionnaire was distributed to the members of Official WeChat account of Learning Union from March 19, 2020, to April 10, 2020. Questionnaires requested respondents' demographic information and responses to five cases of anterior urethral stricture: short obliterative bulbar urethral stricture caused by straddle injury (Case 1), idiopathic bulbar urethral stricture after failure of multiple endoscopic therapy (Case 2), iatrogenic long penile urethral stricture (Case 3), lichen sclerosis-related urethral stricture (Case 4), and anterior urethral stricture in indwelling catheter after multiple failure of endoscopic surgery (Case 5). Data was described by frequency and percentage.ResultsA total of 1,267 valid anonymous questionnaires were received. Urethroplasty was recommended more frequently than endoscopic surgery (Case 1: 47.8% vs. 32.8%,Case 2: 42.5% vs. 33.8%, Case 3: 36.1% vs. 26.7%). Referrals patients to other urologists engaged in urethral repair and reconstruction account for a high portion of the treatment (Case 1:18.4%, Case 2:23.1%, Case 3:36.5%, Case 4:27.7%,Case 5:9.3%). Excision and primary anastomosis urethroplasty (EPA) was preferred for treatment of Case 1 (42.5%). For Case 2, the most popular choice was EPA (30.6%). Although the patient has a history of failure in endoscopic surgery, 33.8% of urologists continue to choose endoscopic surgery. For Case 3, 20.0% of urologists would perform oral mucosal urethroplasty. Surprisingly, 5.9% chose EPA. For Case 4, 37.3% of urologists selected meatotomy, 30.4% suggested that glans and urethral biopsies should be performed. 21.0% chose to use steroid ointment after surgery. For Case 5, 26.3% of the respondents believed that urethrography should be performed after removing catheter more than one week, if the urine is obstructed during the period, performing cystostomy firstly.ConclusionsIn China, the concept of urethroplasty is more widely accepted than endoscopic surgery for the treatment of anterior urethral strictures. The concept of referral has been widely formed among Chinese urologists. Better understanding of the comprehensive treatment of lichen sclerosis related anterior urethral stricture and the principle of urethral rest should be strengthened

Manipulating single excess electrons in monolayer transition metal dihalide

Polarons are entities of excess electrons dressed with local response of lattices, whose atomic-scale characterization is essential for understanding the many body physics arising from the electron-lattice entanglement, but yet difficult to achieve. Here, using scanning tunneling microscopy and spectroscopy (STM/STS), we show the visualization and manipulation of single polarons with different origin, i.e., electronic and conventional polarons, in monolayer CoCl2, that are grown on HOPG substrate via molecular beam epitaxy. Four types of polarons are identified, all inducing upward local band bending, but exhibiting distinct appearances, lattice occupations, polaronic states and local lattice distortions. First principles calculations unveil three types of polarons are stabilized by electron-electron interaction. The type-4 polaron, however, are driven by conventional lattice distortions. All the four types of polarons can be created, moved, erased, and moreover interconverted individually by the STM tip, allowing precise control of single polarons unprecedently. This finding identifies the rich category of polarons and their feasibility of manipulation in CoCl2, which can be generalized to other transition metal halides.Comment: 23 pages, 5 figure