Efficient access to conjugated 4,4′-bipyridinium oligomers using the Zincke reaction: Synthesis, spectroscopic and electrochemical properties

The cyclocondensation reaction between rigid, electron-rich aromatic diamines and 1,1′-bis(2,4-dinitrophenyl)-4,4′-bipyridinium (Zincke) salts has been harnessed to produce a series of conjugated oligomers containing up to twelve aromatic/heterocyclic residues. These oligomers exhibit discrete, multiple redox processes accompanied by dramatic changes in electronic absorption spectra

Deep Learning based Underwater Object Detection

Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) equipped with an intelligent object detection system play a vital role in various underwater applications such as marine resource exploitation, marine environment monitoring, and marine cable protection. Deep learning based object detection methods have presented great performance advantages over traditional machine learning based methods. However, these deep learning based methods lack sufficient capabilities to handle underwater object detection (UOD) due to these challenges: (1) underwater images acquired in complicated environments suffer fromsevere distortion which dramatically degrades image visibility, objects in the underwater datasets and real applications are usually small whilst accompanying severe noise that greatly degrade the detection accuracy of UOD tasks. (2) well-annotated underwater data is not sufficient in terms of diversity and amount which highly influences the performance of deep learning models. (3) severely imbalanced data distribution and label noise distribtuion occur in underwater datasets, driving a deep learning model to be more biased towards the majority class. In this thesis, we aim to address all these challenges, and develop robust deep learning systems to enhance and detect objects in complex underwater images. To achieve this goal, we firstly propose novel perceptual enhancement models to enhance the quality of underwater images. Secondly, we propose a novel Sample-WeIghted hyPEr Network (SWIPENET), and a robust training paradigm named Curriculum Multi-Class Adaboost (CMA), to address the noise and small object detection problems at the same time. Finally, to address the class imbalance problem, we propose a factor-agnostic gradient re-weighting algorithm (FAGR) that can adaptively fine tune the gradients of individual classes according to the distributions of their detection precision. We have evaluated the proposed methods by conducting extensive experiments on public datasets. Experimental results show the effectiveness of our methods for underwater image synthsis, image enhancement and object detection.</p

Are Financial Constraints Priced? Evidence from Firm Fundamentals and Stock Returns

Using comprehensive firm- and aggregate-level data, this paper studies the real and financial implications of capital market imperfections. We first examine whether financially constrained firms' business fundamentals (capital spending and operating earnings) are more sensitive to macroeconomic movements than unconstrained firms' fundamentals. We then examine whether financial constraint "return factors" respond to macroeconomic shocks in tandem with the responses from business fundamentals. The evidence in this paper points to financial constraints affecting both fundamental quantities and asset returns

Effectiveness and Safety of Interventions for Treating Adults with Displaced Proximal Humeral Fracture: A Network Meta-Analysis and Systematic Review

<div><p>Purpose</p><p>Network meta-analysis (NMA) is a comparatively new evidence-based technique in medical disciplines which compares the relative benefits associated with multiple interventions and obtains hierarchies of these interventions for various treatment options. We evaluated the effectiveness and safety of open reduction and internal fixation (ORIF), hemiarthroplasty (HA), reverse shoulder arthroplasty (RSA), intramedullary nailing (IN) and non-operative treatment (NOT) of displaced proximal humeral fractures in adults using Bayesian NMA of data from clinical trials.</p><p>Method</p><p>PUBMED, EMBASE and CENTRAL in July 2016 were searched and clinical trials that evaluated interventions for treating adults with displaced proximal humeral fractures were identified. Methodological qualities of studies were assessed by the Newcastle—Ottawa Scale and risk of bias using the Cochrane Collaboration tool.</p><p>Result</p><p>Thirty-four trials involving 2165 participants were included in the study. RSA had significantly the highest Constant score and lower total incidence of complications than ORIF, HA and IN. Moreover, RSA resulted in a lower incidence of additional surgery than ORIF and IN. The rank of treatments in terms high Constant score was: RSA, ORIF, IN, NOT and HA. The rank for reduction in total incidence of complications was: RSA, NOT, HA, IN and ORIF. For lowering the risk of additional surgery, the rank was: RSA, NOT, HA, IN and ORIF.</p><p>Conclusion</p><p>RSA had the highest probability for improving functional outcome and reduction in the total incidence of complications and requiring additional surgery among the five interventions for treating adults with displaced proximal humeral fracture.</p></div

Results for incidence of additional surgery, from network meta-analysis (lower diagonal part) and pairwise meta-analysis (upper diagonal part).

<p>Results for incidence of additional surgery, from network meta-analysis (lower diagonal part) and pairwise meta-analysis (upper diagonal part).</p

Ranking of treatment strategies based on the probability of their effects on the outcome of incidence of total complications.

<p>ORIF: open reduction and internal fixation; HA: hemiarthroplasty; RSA: reverse shoulder arthroplasty; IN: intramedullary nailing; NOT: Non-operative treatment.</p

Ranking of treatment strategies based on the probability of their effects on the outcome of incidence of additional surgery.

<p>ORIF: open reduction and internal fixation; HA: hemiarthroplasty; RSA: reverse shoulder arthroplasty; IN: intramedullary nailing; NOT: Non-operative treatment.</p

Risk of bias summary: review authors’ judgements about each risk of bias item for each included study.

<p>Risk of bias summary: review authors’ judgements about each risk of bias item for each included study.</p

Ranking of treatment strategies based on the probability of their effects on the outcome of constant score.

<p>ORIF: open reduction and internal fixation; HA: hemiarthroplasty; RSA: reverse shoulder arthroplasty; IN: intramedullary nailing; NOT: Non-operative treatment.</p

Network of treatment comparisons for constant score.

<p>The size of the node corresponds to the total sample size of treatments. Directly comparable treatments are linked with a line, the thickness of which represents the number of trials that were compared. ORIF: open reduction and internal fixation; HA: hemiarthroplasty; RSA: reverse shoulder arthroplasty; IN: intramedullary nailing; NOT: Non-operative treatment.</p