Dual-Branch Temperature Scaling Calibration for Long-Tailed Recognition

The calibration for deep neural networks is currently receiving widespread attention and research. Miscalibration usually leads to overconfidence of the model. While, under the condition of long-tailed distribution of data, the problem of miscalibration is more prominent due to the different confidence levels of samples in minority and majority categories, and it will result in more serious overconfidence. To address this problem, some current research have designed diverse temperature coefficients for different categories based on temperature scaling (TS) method. However, in the case of rare samples in minority classes, the temperature coefficient is not generalizable, and there is a large difference between the temperature coefficients of the training set and the validation set. To solve this challenge, this paper proposes a dual-branch temperature scaling calibration model (Dual-TS), which considers the diversities in temperature parameters of different categories and the non-generalizability of temperature parameters for rare samples in minority classes simultaneously. Moreover, we noticed that the traditional calibration evaluation metric, Excepted Calibration Error (ECE), gives a higher weight to low-confidence samples in the minority classes, which leads to inaccurate evaluation of model calibration. Therefore, we also propose Equal Sample Bin Excepted Calibration Error (Esbin-ECE) as a new calibration evaluation metric. Through experiments, we demonstrate that our model yields state-of-the-art in both traditional ECE and Esbin-ECE metrics

centroIDA: Cross-Domain Class Discrepancy Minimization Based on Accumulative Class-Centroids for Imbalanced Domain Adaptation

Unsupervised Domain Adaptation (UDA) approaches address the covariate shift problem by minimizing the distribution discrepancy between the source and target domains, assuming that the label distribution is invariant across domains. However, in the imbalanced domain adaptation (IDA) scenario, covariate and long-tailed label shifts both exist across domains. To tackle the IDA problem, some current research focus on minimizing the distribution discrepancies of each corresponding class between source and target domains. Such methods rely much on the reliable pseudo labels' selection and the feature distributions estimation for target domain, and the minority classes with limited numbers makes the estimations more uncertainty, which influences the model's performance. In this paper, we propose a cross-domain class discrepancy minimization method based on accumulative class-centroids for IDA (centroIDA). Firstly, class-based re-sampling strategy is used to obtain an unbiased classifier on source domain. Secondly, the accumulative class-centroids alignment loss is proposed for iterative class-centroids alignment across domains. Finally, class-wise feature alignment loss is used to optimize the feature representation for a robust classification boundary. A series of experiments have proved that our method outperforms other SOTA methods on IDA problem, especially with the increasing degree of label shift

Accelerating-particle-deposition Method for Quickly Evaluating Long-term Performance of Fin-and-tube Heat Exchangers

Fin-and-tube heat exchanger is the most commonly used heat exchanger type in air-conditioning systems. In the actual operation of air-conditioning systems, the dust particles involved in the air may partly deposit and form particulate fouling on fins and tubes when the dusty air flows through the heat exchangers. The deposited particles may gradually block the passageway of air flow and occupy the heat transfer area, which results in the continuous increase of air side thermal resistance and the significant deterioration of the heat transfer capacity of heat exchangers during the long-term operation. In order to quickly evaluate the long-term performance of fin-and-tube heat exchangers, an accelerating-particle-deposition method, which is capable of implementing the particle deposition process on the long-running heat exchangers in a short time, is proposed in this study. The idea of the accelerating-particle-deposition method is to employ high concentration dusty air flow through heat exchangers in the accelerated test, and to quickly form the particulate fouling with the same weight as that on long-running heat exchangers under the actual operating environment with low particle concentration. The accelerating factor, which is defined as the ratio of the actual running time to the accelerated testing time, is calculated based on the deposition weight of dust particles. The deposition weight is calculated by the relationship of the impact frequency and deposition probability of dust particles with the particle concentration of dusty air. An experimental apparatus for accelerating the particle deposition process and testing the heat transfer capacity of fin-and-tube heat exchangers is designed. The predicted long-term performances of heat exchangers based on the proposed accelerating-particle-deposition method are compared with the actual performance data of heat exchangers after 5-8 years’ operation published by China Quality Certification Center. The comparison results show that, the predicted results agree well with the actual operation data, and the mean deviation of the heat transfer capacity is within 10%

Metabonomic Study on the Antidepressant-Like Effects of Banxia Houpu Decoction and Its Action Mechanism

The aim of this study was to establish an experimental model for metabonomic profiles of the rat’s brain and then to investigate the antidepressant effect of Banxia Houpu decoction (BHD) and its possible mechanisms. Behavioral research and metabonomics method based on UPLC-MS were used to assess the efficacy of different fractions of BHD on chronic unpredictable mild stress (CUMS) model of depression. There was a significant difference between the BHD group and the model group. Eight endogenous metabolites, which are contributing to the separation of the model group and control group, were detected, while BHD group regulated the perturbed metabolites showing that there is a tendency of recovery compared to control group. Therefore, we think that those potential metabolite biomarkers have some relationship with BHD’s antidepression effect. This work appraised the antidepressant effect of Banxia Houpu decoction as well as revealing a metabonomics method, a valuable parameter in the TCM research

Evidence for a synergistic effect of post-translational modifications and genomic composition of eEF-1 alpha on the adaptation of Phytophthora infestans

Genetic variation plays a fundamental role in pathogen's adaptation to environmental stresses. Pathogens with low genetic variation tend to survive and proliferate more poorly due to their lack of genotypic/phenotypic polymorphisms in responding to fluctuating environments. Evolutionary theory hypothesizes that the adaptive disadvantage of genes with low genomic variation can be compensated for structural diversity of proteins through post-translation modification (PTM) but this theory is rarely tested experimentally and its implication to sustainable disease management is hardly discussed. In this study, we analyzed nucleotide characteristics of eukaryotic translation elongation factor-1 alpha (eEF-l alpha) gene from 165 Phytophthora infestans isolates and the physical and chemical properties of its derived proteins. We found a low sequence variation of eEF-l alpha protein, possibly attributable to purifying selection and a lack of intra-genic recombination rather than reduced mutation. In the only two isoforms detected by the study, the major one accounted for >95% of the pathogen collection and displayed a significantly higher fitness than the minor one. High lysine representation enhances the opportunity of the eEF-1 alpha protein to be methylated and the absence of disulfide bonds is consistent with the structural prediction showing that many disordered regions are existed in the protein. Methylation, structural disordering, and possibly other PTMs ensure the ability of the protein to modify its functions during biological, cellular and biochemical processes, and compensate for its adaptive disadvantage caused by sequence conservation. Our results indicate that PTMs may function synergistically with nucleotide codes to regulate the adaptive landscape of eEF-1 alpha, possibly as well as other housekeeping genes, in P. infestans. Compensatory evolution between pre- and post-translational phase in eEF-1 alpha could enable pathogens quickly adapting to disease management strategies while efficiently maintaining critical roles of the protein playing in biological, cellular, and biochemical activities. Implications of these results to sustainable plant disease management are discussed

Noninvasive Submillimeter-Precision Brain Stimulation by Optically-Driven Focused Ultrasound

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological diseases. Current non-invasive neuromodulation methods offer limited millimeter-level precision. Here, we report an optically-driven focused ultrasound (OFUS) for non-invasive brain stimulation with submillimeter precision. OFUS is generated by a soft optoacoustic pad (SOAP) fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane film. SOAP generates a transcranial ultrasound focus at 15 MHz with a lateral resolution of 83 micrometers, which is two orders of magnitude smaller than that of conventional transcranial focused ultrasound (tFUS). Effective OFUS neurostimulation in vitro with a single ultrasound cycle is shown. Submillimeter transcranial stimulation of mouse motor cortex in vivo is demonstrated. An acoustic energy of 0.02 J/cm^2, two orders of magnitude less than that of tFUS, is sufficient for successful OFUS neurostimulation. By delivering a submillimeter focus non-invasively, OFUS opens a new way for neuroscience studies and disease treatments.Comment: 36 pages, 5 main figures, 13 supplementary figure

Impact of GLP-1 Receptor Agonists on Major Gastrointestinal Disorders for Type 2 Diabetes Mellitus: A Mixed Treatment Comparison Meta-Analysis

Aim. We aimed to integrate evidence from all randomized controlled trials (RCTs) and assess the impact of different doses of exenatide or liraglutide on major gastrointestinal adverse events (GIAEs) in type 2 diabetes (T2DM). Methods. RCTs evaluating different doses of exenatide and liraglutide against placebo or an active comparator with treatment duration ≥4 weeks were searched and reviewed. A total of 35, 32 and 28 RCTs met the selection criteria evaluated for nausea, vomiting, and diarrhea, respectively. Pairwise random-effects meta-analyses and mixed treatment comparisons (MTC) of all RCTs were performed. Results. All GLP-1 dose groups significantly increased the probability of nausea, vomiting and diarrhea relative to placebo and conventional treatment. MTC meta-analysis showed that there was 99.2% and 85.0% probability, respectively, that people with exenatide 10 μg twice daily (EX10BID) was more vulnerable to nausea and vomiting than those with other treatments. There was a 78.90% probability that liraglutide 1.2 mg once daily (LIR1.2) has a higher risk of diarrhea than other groups. A dose-dependent relationship of exenatide and liraglutide on GIAEs was observed. Conclusions. Our MTC meta-analysis suggests that patients should be warned about these GIAEs in early stage of treatment by GLP-1s, especially by EX10BID and LIR1.2, to promote treatment compliance

Metabonomic Study on the Antidepressant-Like Effects of Banxia Houpu Decoction and Its Action Mechanism

The aim of this study was to establish an experimental model for metabonomic profiles of the rat's brain and then to investigate the antidepressant effect of Banxia Houpu decoction (BHD) and its possible mechanisms. Behavioral research and metabonomics method based on UPLC-MS were used to assess the efficacy of different fractions of BHD on chronic unpredictable mild stress (CUMS) model of depression. There was a significant difference between the BHD group and the model group. Eight endogenous metabolites, which are contributing to the separation of the model group and control group, were detected, while BHD group regulated the perturbed metabolites showing that there is a tendency of recovery compared to control group. Therefore, we think that those potential metabolite biomarkers have some relationship with BHD's antidepression effect. This work appraised the antidepressant effect of Banxia Houpu decoction as well as revealing a metabonomics method, a valuable parameter in the TCM research

Near-infrared and mid-infrared semiconductor broadband light emitters

Semiconductor broadband light emitters have emerged as ideal and vital light sources for a range of biomedical sensing/imaging applications, especially for optical coherence tomography systems. Although near-infrared broadband light emitters have found increasingly wide utilization in these imaging applications, the requirement to simultaneously achieve both a high spectral bandwidth and output power is still challenging for such devices. Owing to the relatively weak amplified spontaneous emission, as a consequence of the very short non-radiative carrier lifetime of the inter-subband transitions in quantum cascade structures, it is even more challenging to obtain desirable mid-infrared broadband light emitters. There have been great efforts in the past 20 years to pursue high-efficiency broadband optical gain and very low reflectivity in waveguide structures, which are two key factors determining the performance of broadband light emitters. Here we describe the realization of a high continuous wave light power of >20 mW and broadband width of >130 nm with near-infrared broadband light emitters and the first mid-infrared broadband light emitters operating under continuous wave mode at room temperature by employing a modulation p-doped InGaAs/GaAs quantum dot active region with a ‘J’-shape ridge waveguide structure and a quantum cascade active region with a dual-end analogous monolithic integrated tapered waveguide structure, respectively. This work is of great importance to improve the performance of existing near-infrared optical coherence tomography systems and describes a major advance toward reliable and cost-effective mid-infrared imaging and sensing systems, which do not presently exist due to the lack of appropriate low-coherence mid-infrared semiconductor broadband light sources