Constructing Invariant Representation of Sound Using Optimal Features And Sound Statistics Adaptation

The ability to convey information using sound is critical for the survival of many vocal species, including humans. These communication sounds (vocalizations or calls) are often comprised of complex spectrotemporal features that require accurate detection to prevent mis-categorization. This task is made difficult by two factors: 1) the inherent variability in vocalization production, and 2) competing sounds from the environment. The auditory system must generalize across these variabilities while maintaining sufficient sensitivity to detect subtle differences in fine acoustic structures. While several studies have described vocalization-selective and noise invariant neural responses in the auditory pathway at a phenomenological level, the algorithmic and mechanistic principles behind these observations remain speculative. In this thesis, we first adopted a theoretical approach to develop biologically plausible computational algorithms to categorize vocalizations while generalizing over sound production and environment variability. From an initial set of randomly chosen vocalization features, we used a greedy search algorithm to select most informative features that maximized vocalization categorization performance and minimized redundancy between features. High classification performance could be achieved using only 10–20 features per vocalization category. The optimal features tended to be of intermediate complexity, offering an optimal compromise between fine and tolerant feature tuning. Predictions of tuning properties of putative feature-selective neurons matched some observed auditory cortical responses. While this algorithm performed well in quiet listening conditions, it failed in noisy conditions. To address this shortcoming, we implemented biologically plausible algorithms to improve model performance in noisy conditions. We explored two model elements to aid adaption to sound statistics: 1. De-noising of noisy inputs by thresholding based on wide-band energy, and 2. Adjusting feature detection parameters to offset noise-masking effects. These processes were consistent with physiological observations of gain control mechanisms and principles of efficient encoding in the brain. With these additions, our model was able to achieve near-physiological levels of performance. Our results suggest that invariant representation of sound can be achieved based on task-dependent features with adaptation to input sound statistics

MMPL-Net: Multi-modal prototype learning for one-shot RGB-D segmentation

For one-shot segmentation, prototype learning is extensively used. However, using only one RGB prototype to represent all information in the support image may lead to ambiguities. To this end, we propose a one-shot segmentation network based on multi-modal prototype learning that uses depth information to complement RGB information. Specifically, we propose a multi-modal fusion and refinement block (MFRB) and multi-modal prototype learning block (MPLB). MFRB fuses RGB and depth features to generate multi-modal features and refined depth features, which are used by MPLB, to generate multi-modal information prototypes, depth information prototypes, and global information prototypes. Furthermore, we introduce self-attention to capture global context information in RGB and depth images. By integrating self-attention, MFRB, and MPLB, we propose the multi-modal prototype learning network (MMPL-Net), which adapts to the ambiguity of visual information in the scene. Finally, we construct a one-shot RGB-D segmentation dataset called OSS-RGB-D-5i. Experiments using OSS-RGB-D-5i show that our proposed method outperforms several state-of-the-art techniques with fewer labeled images and generalizes well to previously unseen objects.</p

Modulation of Excited State Property Based on Benzo[a, c]phenazine Acceptor: Three Typical Excited States and Electroluminescence Performance

Throwing light upon the structure-property relationship of the excited state properties for next-generation fluorescent materials is crucial for the organic light emitting diode (OLED) field. Herein, we designed and synthesized three donor-acceptor (D-A) structure compounds based on a strong spin orbit coupling (SOC) acceptor benzo[a, c]phenazine (DPPZ) to research on the three typical types of excited states, namely, the locally-excited (LE) dominated excited state (CZP-DPPZ), the hybridized local and charge-transfer (HLCT) state (TPA-DPPZ), and the charge-transfer (CT) dominated state with TADF characteristics (PXZ-DPPZ). A theoretical combined experimental research was adopted for the excited state properties and their regulation methods of the three compounds. Benefiting from the HLCT character, TPA-DPPZ achieves the best non-doped device performance with maximum brightness of 61,951 cd m−2 and maximum external quantum efficiency of 3.42%, with both high photoluminescence quantum efficiency of 40.2% and high exciton utilization of 42.8%. Additionally, for the doped OLED, PXZ-DPPZ can achieve a max EQE of 9.35%, due to a suppressed triplet quenching and an enhanced SOC

Temporal Factors and Missed Doses of Tuberculosis Treatment: A Causal Associations Approach to Analyses of Digital Adherence Data

Rationale: Tuberculosis treatment lasts for 6 months or more. Treatment adherence is critical; regimen length, among other factors, makes this challenging. Globally, analyses mapping common types of nonadherence are lacking. For example, is there a greater challenge resulting from early treatment cessation (discontinuation) or intermittent missed doses (suboptimal dosing implementation)? This is essential knowledge for the development of effective interventions and more "forgiving" regimens, as well as to direct national tuberculosis programs.Objectives: To granularly describe how patients take their tuberculosis medication and the temporal factors associated with missed doses.Methods: The present study included patients with pulmonary tuberculosis enrolled in the control arm of a pragmatic, cluster-randomized trial in China of electronic reminders to improve treatment adherence. Treatment was the standard 6-month course (180 d), dosed every other day (90 doses). Medication monitor boxes recorded adherence (box opening) without prompting reminders. Patterns of adherence were visualized and described. Mixed-effects logistic regression models examined the temporal factors associated with per-dose suboptimal dosing implementation, adjusting for clustering within a participant. Cox regression models were used to examine the association between early suboptimal dosing implementation and permanent discontinuation.Results: Across 780 patients, 16,794 (23.9%) of 70,200 doses were missed, 9,487 of which were from suboptimal dosing implementation (56.5%). By 60 days, 5.1% of participants had discontinued, and 14.4% had discontinued by 120 days. Most participants (95.9%) missed at least one dose. The majority of gaps were of a single dose (71.4%), although 22.6% of participants had at least one gap of 2 weeks or more. In adjusted models, the initiation-continuation phase transition (odds ratio, 3.07 [95% confidence interval, 2.68-3.51]) and national holidays (1.52 [1.39-1.65]) were associated with increased odds of suboptimal dosing implementation. Early-stage suboptimal dosing implementation was associated with increased discontinuation rates.Conclusions: Digital tools provide an unprecedented step change in describing and addressing nonadherence. In our setting, nonadherence was common; patients displayed a complex range of patterns. Dividing nonadherence into suboptimal dosing implementation and discontinuation, we found that both increased over time. Discontinuation was associated with early suboptimal dosing implementation. These apparent causal associations between temporal factors and nonadherence present opportunities for targeted interventions.Clinical trial registered with the ISRCTN Registry (ISRCTN46846388)

Acupuncture for Chronic Urinary Retention due to Spinal Cord Injury: A Systematic Review

No systematic review has been published on the use of acupuncture for the treatment of chronic urinary retention (CUR) due to spinal cord injury (SCI). The aim of this review was to assess the effectiveness and safety of acupuncture for CUR due to SCI. Three randomized controlled trials (RCTs) including 334 patients with CUR due to SCI were included. Meta-analysis showed that acupuncture plus rehabilitation training was much better than rehabilitation training alone in decreasing postvoid residual (PVR) urine volume (MD −109.44, 95% CI −156.53 to −62.35). Likewise, a combination of acupuncture and aseptic intermittent catheterization was better than aseptic intermittent catheterization alone in improving response rates (RR 1.23, 95% CI 1.10 to 1.38). No severe adverse events were reported. In conclusion, acupuncture as a complementary therapy may have a potential effect in CUR due to SCI in decreasing PVR and improving bladder voiding. Additionally, acupuncture may be safe in treating CUR caused by SCI. However, due to the lack of high quality RCTs, we could not draw any definitive conclusions. More well-designed RCTs are needed to provide strong evidence

Laser in Glaucoma and Ocular Hypertension Trial (LIGHT) in China - A Randomized Controlled Trial: Design and Baseline Characteristics

PURPOSE: To describe the baseline characteristics of a trial to evaluate whether selective laser trabeculoplasty (SLT), as a first-line treatment, provides superior economic and health-related quality of life outcomes to medical treatment in China. DESIGN: The LiGHT China trial is an unmasked, single-center, pragmatic, randomized controlled trial. METHODS: A total of 771 previously undiagnosed patients with primary open angle glaucoma (POAG, 622 patients) or ocular hypertension (OHT, 149 patients) at Zhongshan Ophthalmic Center were recruited from March 2015 to January 2019. Subjects were randomized to SLT-1st (followed by medication then surgery when required) or Medicine-1st (medication followed by surgery when required). The primary outcome was health-related quality of life (HRQL). The secondary outcomes were clinical outcomes, cost, cost-effectiveness, Glaucoma Utility Index, Glaucoma Symptom Scale, visual function, and safety. RESULTS: The mean age of POAG patients was 49.8 years and 38.8 years for OHT. The median intraocular pressure was 20 mm Hg for the 1,105 POAG eyes and 24 mm Hg for the 271 OHT eyes. POAG eyes had thinner central cornea thickness (CCT, 536 µm) than OHT eyes (545 µm). Median mean deviation of the visual field in POAG eyes was -4.2 dB. Median refractive error was -1.5 D for OHT eyes and -1.25 D for POAG eyes. There was no difference between POAG and OHT patients on baseline scores of GUI, GSS and VF-14. The difference between OHT and POAG on the EQ-5D-5L was 0.024. CONCLUSIONS: Compared with participants in the LiGHT UK trial, participants in this trial were younger, more myopic and had more severe visual field defects

Lithium titanate hydrates with superfast and stable cycling in lithium ion batteries

Lithium titanate and titanium dioxide are two best-known high-performance electrodes that can cycle around 10,000 times in aprotic lithium ion electrolytes. Here we show there exists more lithium titanate hydrates with superfast and stable cycling. That is, water promotes structural diversity and nanostructuring of compounds, but does not necessarily degrade electrochemical cycling stability or performance in aprotic electrolytes. As a lithium ion battery anode, our multi-phase lithium titanate hydrates show a specific capacity of about 130 mA h g⁻¹ at ∼35 C (fully charged within ∼100 s) and sustain more than 10,000 cycles with capacity fade of only 0.001% per cycle. In situ synchrotron diffraction reveals no 2-phase transformations, but a single solid-solution behavior during battery cycling. So instead of just a nanostructured intermediate to be calcined, lithium titanate hydrates can be the desirable final destination.United States. Department of Energy (Contract DE-AC0206CH11357