Region-Aware Exposure Consistency Network for Mixed Exposure Correction

Exposure correction aims to enhance images suffering from improper exposure to achieve satisfactory visual effects. Despite recent progress, existing methods generally mitigate either overexposure or underexposure in input images, and they still struggle to handle images with mixed exposure, i.e., one image incorporates both overexposed and underexposed regions. The mixed exposure distribution is non-uniform and leads to varying representation, which makes it challenging to address in a unified process. In this paper, we introduce an effective Region-aware Exposure Correction Network (RECNet) that can handle mixed exposure by adaptively learning and bridging different regional exposure representations. Specifically, to address the challenge posed by mixed exposure disparities, we develop a region-aware de-exposure module that effectively translates regional features of mixed exposure scenarios into an exposure-invariant feature space. Simultaneously, as de-exposure operation inevitably reduces discriminative information, we introduce a mixed-scale restoration unit that integrates exposure-invariant features and unprocessed features to recover local information. To further achieve a uniform exposure distribution in the global image, we propose an exposure contrastive regularization strategy under the constraints of intra-regional exposure consistency and inter-regional exposure continuity. Extensive experiments are conducted on various datasets, and the experimental results demonstrate the superiority and generalization of our proposed method. The code is released at: https://github.com/kravrolens/RECNet.Comment: Accepted by AAAI 202

Mutual Distillation Learning For Person Re-Identification

With the rapid advancements in deep learning technologies, person re-identification (ReID) has witnessed remarkable performance improvements. However, the majority of prior works have traditionally focused on solving the problem via extracting features solely from a single perspective, such as uniform partitioning, hard attention mechanisms, or semantic masks. While these approaches have demonstrated efficacy within specific contexts, they fall short in diverse situations. In this paper, we propose a novel approach, Mutual Distillation Learning For Person Re-identification (termed as MDPR), which addresses the challenging problem from multiple perspectives within a single unified model, leveraging the power of mutual distillation to enhance the feature representations collectively. Specifically, our approach encompasses two branches: a hard content branch to extract local features via a uniform horizontal partitioning strategy and a Soft Content Branch to dynamically distinguish between foreground and background and facilitate the extraction of multi-granularity features via a carefully designed attention mechanism. To facilitate knowledge exchange between these two branches, a mutual distillation and fusion process is employed, promoting the capability of the outputs of each branch. Extensive experiments are conducted on widely used person ReID datasets to validate the effectiveness and superiority of our approach. Notably, our method achieves an impressive $88.7\%/94.4\%$ in mAP/Rank-1 on the DukeMTMC-reID dataset, surpassing the current state-of-the-art results. Our source code is available at https://github.com/KuilongCui/MDPR

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

Differentiation in Leaf Functional Traits and Driving Factors of the Allopatric Distribution of Tetraploid and Octaploid <i>Buddleja macrostachya</i> in the Sino-Himalayan Region

Leaf functional traits reflect species’ adaptive strategies and habitat requirements. Examining intra-specific variations and their underlying drivers can aid in comprehending species differentiation and adaptation. Here, we investigated the leaf functional traits of Buddleja macrostachya tetraploids and octaploids across 18 sites in the Sino-Himalayan region. The habitat environmental variables were also recorded. In this study, leaf functional traits showed a considerable differentiation in both tetraploid and octaploid B. macrostachya. Redundancy analysis (RDA) revealed that the octaploid cytotypes displayed higher specific leaf area, leaf total nitrogen and phosphorus concentrations, water-use efficiency, and light-use efficiency in contrast to the tetraploid plants. These functional leaf traits exhibited different plasticity levels in both taxa. A positive link was found between habitat altitude and soil total P concentration and the geographic distribution of the B. macrostachya complex, using RDA and Pearson’s correlation. Our findings suggest that both tetraploid and octaploid B. macrostachya exhibited divergent ecological strategies, conservative and acquisitive strategies, respectively. The ecological adaptability of species within the B. macrostachya complex is enhanced by the combination of divergent ecological strategies and high phenotypic plasticity of distinct key ecological traits. Furthermore, abiotic environmental factors influenced the allopatric geographic distribution pattern of the B. macrostachya complex in the Sino-Himalayan region

Region-Based Global Reasoning Networks

Global reasoning plays a significant role in many computer vision tasks which need to capture long-distance relationships. However, most current studies on global reasoning focus on exploring the relationship between pixels and ignore the critical role of the regions. In this paper, we propose an novel approach that explores the relationship between regions which have richer semantics than pixels. Specifically, we design a region aggregation method that can gather regional features automatically into a uniform shape, and adjust theirs positions adaptively for better alignment. To achieve the best performance of global reasoning, we propose various relationship exploration methods and apply them on the regional features. Our region-based global reasoning module, named ReGr, is end-to-end and can be inserted into existing visual understanding models without extra supervision. To evaluate our approach, we apply ReGr to fine-grained classification and action recognition benchmark tasks, and the experimental results demonstrate the effectiveness of our approach

Comparative transcriptomic profiles of Paulownia catalpifolia under different degrees of chilling stress during the seedling stage

Abstract Background Paulownia, an ecologically and economically valuable plant species native to China, is notable for its excellent timber quality and strong adaptability. Among them, Paulownia catalpifolia displays the ability to survive in cold climate, a trait associated with northern China. Yet, the molecular information for its cold-tolerance has not been explored. This study was to investigate the changes in physiological indices and transcript levels of P. catalpifolia following cold exposure, which could provide evidence for revealing whether there were differences in the genetic basis of inducing physiological perturbations between moderate low temperature (MLT) and extreme low temperature (ELT). Results The detection of physiological indices under diverse degrees of chilling stress showed similar patterns of alteration. Enhanced accumulation of osmoregulatory substances, such as soluble sugar and soluble protein, were more conducive under ELT compared to MLT in P. catalpifolia. Moreover, we observed leaf wilting symptoms distinctly after exposure to ELT for 48 h, while this effect was not obvious after MLT exposure for 48 h. Comparative transcriptomic analysis between MLT and ELT demonstrated 13,688 differentially expressed genes (DEGs), most of them appeared after 12 h and 48 h of treatment. GO and KEGG analyses elucidated prominent enrichment in aromatic-L-amino-acid decarboxylase activity term and carbohydrate metabolism pathways. Therefore, it was speculated that the DEGs involved in the above processes might be related to the difference in the contents of soluble protein and soluble sugar between MLT and ELT. Time series clustering analyses further highlighted several key genes engaged in the ‘Glycosyltransferases’, ‘Galactose metabolism’ and ‘Starch and sucrose metabolism’ pathways as well as the ‘tyrosine decarboxylase activity’ term. For instance, cellulose synthase-like A (CLSA2/9), raffinose synthase (RafS2), β-amylase (BAM1) and tyrosine/DOPA decarboxylase (TYDC1/2/5) genes, diverging in their expression trends between MLT and ELT, might significantly affect the soluble sugar and soluble protein abundance within P. catalpifolia. Conclusion Between MLT and ELT treatments, partial overlaps in response pathways of P. catalpifolia were identified, while several genes regulating the accumulation of osmotic adjustment substances had disparate expression patterns. These findings could provide a novel physiological and molecular perspective for P. catalpifolia to adapt to complex low temperature habitats

Selection of suitable reference genes in Paulownia fortunei (Seem.) Hemsl. under different tissues and abiotic stresses for qPCR normalization

By choosing appropriate candidate reference genes (CRGs) and standardizing qPCR data, more accurate experimental data can be obtained. Herein, the expression stability of alpha-tubulin1 (TUA1), beta-tubulin (TUB), beta-tubulin 1 (TUB1), beta-tubulin 5 (TUB5), actin 1 (ACT1), actin 97 (ACT97), molecular chaperone dnaj (DNAJ), adenine phosphoribosyl transferase (APT), and histone H4 (HIS4) genes from Paulownia fortunei (Seem.) Hemsl. under different experimental conditions (different tissues, drought, salinity, Cd, and Cr treatments) was assessed with four statistical tools: RefFinder, BestKeeper, NormFinder, and geNorm. Notably, TUA1 and TUB5 were identified as CRGs for different tissues, ACT97 and TUB1 for drought treatment, ACT97 and APT for salinity treatment, TUB1 and ACT97 for Cd treatment, and DNAJ, TUB1 and TUB5 for Cr treatment. Furthermore, the results of "total" group, V4/V5 &gt; 0.15 and V5/V6 &lt; 0.15 revealed that the CRGs or gene combinations, which could meet all the test conditions, were not easy to identify. To further verify the reliability of CRGs, the expression levels of paulownia fortunei cellulose synthase A catalytic subunit2 (PfCesA2) and paulownia fortunei glutathione reductase (GR) genes were analysed. The expression patterns were different when the unstable CRGs were used for normalization compared to when the stable CRGs and combination were used for normalization. This study will lay a foundation for study on the expression levels of key genes from P. fortunei seedlings

Research on Lightning Overvoltage Characteristics of High-Voltage Diode Rectifier

Failure of the high-voltage diode rectifier caused by lightning will cause huge losses. The traditional analysis of overvoltage induced by the high-voltage diode rectifier shell under lightning stroke cannot adapt to the overvoltage process caused by lightning stroke-induced conduction invading the inside of the high-voltage diode rectifier. Therefore, this paper proposes to establish a high-frequency equivalent model of the core components of the high-voltage diode rectifier, including diodes, reactors, transformers, and overhead lines. On this basis, a lightning overvoltage model of lightning-induced conduction into the high-voltage diode rectifier is built, and the transient process of diode lightning overvoltage under the constraint of reverse recovery charge is analyzed. Then, we describe the transient distribution of overvoltage in high-voltage diode rectifiers caused by lightning stroke. The transient distribution of overvoltage induced by lightning in series diodes under different diode equivalent models is analyzed by simulation. The simulation results show that the inconsistent parameters of series diodes can easily lead to diode damage due to uneven voltage distribution when lightning strikes. Therefore, this paper puts forward a scheme to reduce lightning damage, including selecting diodes with the same parameters and adding fast-melting fuses at the transformer’s secondary side and in front of the series diode bridge arm. The simulation shows that the scheme proposed in this paper can effectively prevent the high-voltage diode rectifier from being damaged by lightning strikes