From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models

Diffusion models have revolted the field of text-to-image generation recently. The unique way of fusing text and image information contributes to their remarkable capability of generating highly text-related images. From another perspective, these generative models imply clues about the precise correlation between words and pixels. In this work, a simple but effective method is proposed to utilize the attention mechanism in the denoising network of text-to-image diffusion models. Without re-training nor inference-time optimization, the semantic grounding of phrases can be attained directly. We evaluate our method on Pascal VOC 2012 and Microsoft COCO 2014 under weakly-supervised semantic segmentation setting and our method achieves superior performance to prior methods. In addition, the acquired word-pixel correlation is found to be generalizable for the learned text embedding of customized generation methods, requiring only a few modifications. To validate our discovery, we introduce a new practical task called "personalized referring image segmentation" with a new dataset. Experiments in various situations demonstrate the advantages of our method compared to strong baselines on this task. In summary, our work reveals a novel way to extract the rich multi-modal knowledge hidden in diffusion models for segmentation

Parallelization and I/O performance optimization of a global nonhydrostatic dynamical core using MPI

The Global ‐ Regional Integrated forecast SysTem (GRIST) is the next- generation weather and climate integrated model dynamic framework developed by Chinese Academy of Meteorological Sciences. In this paper, we present several changes made to the global nonhydrostatic dynamical (GND) core, which is part of the ongoing prototype of GRIST. The changes leveraging MPI and PnetCDF techniques were targeted at the parallelization and performance optimization to the original serial GND core. Meanwhile, some sophisticated data structures and interfaces were designed to adjust flexibly the size of boundary and halo domains according to the variable accuracy in parallel context. In addition, the I/O performance of PnetCDF decreases as the number of MPI processes increases in our experimental environment. Especially when the number exceeds 6000, it caused system-wide outages (SWO). Thus, a grouping solution was proposed to overcome that issue. Several experiments were carried out on the supercomputing platform based on Intel x86 CPUs in the National Supercomputing Center in Wuxi. The results demonstrated that the parallel GND core based on grouping solution achieves good strong scalability and improves the performance significantly, as well as avoiding the SWOs

Breeding response of transcript profiling in developing seeds of Brassica napus

<p>Abstract</p> <p>Background</p> <p>The upgrading of rapeseed cultivars has resulted in a substantial improvement in yield and quality in China over the past 30 years. With the selective pressure against fatty acid composition and oil content, high erucic acid- and low oil-content cultivars have been replaced by low erucic acid- and high oil-content cultivars. The high erucic acid cultivar Zhongyou 821 and its descendent, low erucic acid cultivar Zhongshuang 9, are representatives of two generations of the most outstanding Chinese rapeseed cultivars (<it>B. napus</it>) developed the past 2 decades. This paper compares the transcriptional profiles of Zhongshuang 9 and Zhongyou 821 for 32 genes that are principally involved in lipid biosynthesis during seed development in order to elucidate how the transcriptional profiles of these genes responded to quality improvement over the past 20 years.</p> <p>Results</p> <p>Comparison of the cultivar Zhongyou 821 with its descendent, Zhongshuang 9, shows that the transcriptional levels of seven of the 32 genes were upregulated by 30% to 109%, including <it>FAD3</it>, <it>ACCase, FAE1</it>, <it>GKTP</it>, <it>Caleosin</it>, <it>GAPDH</it>, and <it>PEPC</it>. Of the 32 genes, 10 (<it>KAS3, β-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, α-CT </it>and <it>SUC1</it>) were downregulated by at least 20% and most by 50%. The <it>Napin </it>gene alone accounted for over 75% of total transcription from all 32 genes assessed in both cultivars. Most of the genes showed significant correlation with fatty acid accumulation, but the correlation in ZS9 was significantly different from that in ZY821. Higher <it>KCR2 </it>activity is associated with higher C16:0, C18:0, and C18:2 in both cultivars, lower C22:1 and total fatty acid content in ZY821, and lower 18:1 in ZS9.</p> <p>Conclusion</p> <p>This paper illustrates the response of the transcription levels of 32 genes to breeding in developing rapeseed seeds. Both cultivars showed similar transcription profiles, with the <it>Napin </it>gene predominantly transcribed. Selective pressure for zero erucic acid, low glucosinolate, high oleic acid and high oil content, as well as high yield, resulted in higher <it>FAD3</it>, <it>ACCase, FAE1</it>, <it>GKTP</it>, <it>Caleosin</it>, <it>GAPDH</it>, and <it>PEPC </it>expression levels and lower <it>KAS3, β-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, α-CT </it>and <it>SUC1 </it>expression levels. It also resulted in altered relationships between these genes during storage accumulation in seed development.</p

Spinal infection caused by Aspergillus flavus in a diabetic: a case report and literature review

Spinal infections, notably those induced by Aspergillus flavus (A. flavus), represent a complex and uncommon clinical challenge. In individuals with diabetes mellitus, the risk is exacerbated due to a compromised immune response and a heightened vulnerability to non-standard pathogens. This case report chronicles the intricate diagnostic and treatment journey of a 59-year-old diabetic patient grappling with a spinal infection attributed to A. flavus. The diagnosis was delayed due to non-specific symptoms and unclear radiological signs. The administration of voriconazole, a targeted antifungal treatment, resulted in a significant clinical and radiological improvement, underscoring its effectiveness in treating such unusual fungal spinal infections; meanwhile, we found that terbinafine hydrochloride also has a similar effect in treating fungal spinal infections. This case underscores the importance of considering fungal causes in spinal infections among diabetic patients and highlights prompt diagnosis and individualized targeted antifungal therapy

Influence of body mass index and waist–hip ratio on male semen parameters in infertile men in the real world: a retrospective study

BackgroundIt is suggested that body mass index (BMI) can affect male semen quality; however, the results remain controversial. In addition, most studies have focused on the effect of obesity on semen quality. Evidence on the relationship of underweight or waist-hip ratio (WHR) with semen quality is rare. This study aimed to assess the association of BMI and WHR with semen quality.MethodsData, including BMI and WHR, was collected from 715.00 men who underwent a fertility evaluation. BMI (kg/m2) was categorized as &lt;18.50 (underweight), 18.50–24.90 (normal), 25.00–27.90 (overweight), and ≥28.00 (obese) kg/m2 for analysis. WHR was categorized as &lt;0.81 (normal) and ≥0.81 (high). Semen volume, sperm concentration, progressive motility, and total motile sperm count were detected by experienced clinical technicians.ResultsSpearman’s correlation showed that BMI was weakly associated with sperm progressive motility (r = 0.076, P &lt; 0.05), while WHR showed no relationship with semen parameters. The azoospermia rate was significantly higher (33.33% vs. 2.10%, P &lt; 0.001) and the sperm concentration was lower (P &lt; 0.05) in the underweight group. The nonlinear correlation analysis showed that BMI was negatively associated with sperm concentration while BMI was more than 22.40 kg/m2 (P &lt; 0.05), while WHR was negatively related to sperm progressive motility within 0.82 to 0.89 (P &lt; 0.05). Furthermore, the multivariate logistic analysis showed that follicular stimulating hormone (FSH) was an independent risk factor for normal sperm concentration (odds ratio [OR]: 0.791, P = 0.001) and morphology (OR: 0.821, P = 0.002), BMI was an independent risk factor for normal sperm progressive motility, and testosterone was an independent risk factor for sperm morphology (OR: 0.908, P = 0.023).ConclusionBMI and WHR were significantly associated with semen parameters, while BMI was an independent risk factor for normal sperm progressive motility. Reproductive hormones, including FSH and testosterone, had a significant influence on sperm concentration and sperm morphology

Crowdsourcing the creation of image segmentation algorithms for connectomics

To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This “deep learning” approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge

Understanding Plant-Microbe Interactions for Phytoremediation of Petroleum-Polluted Soil

Plant-microbe interactions are considered to be important processes determining the efficiency of phytoremediation of petroleum pollution, however relatively little is known about how these interactions are influenced by petroleum pollution. In this experimental study using a microcosm approach, we examined how plant ecophysiological traits, soil nutrients and microbial activities were influenced by petroleum pollution in Phragmites australis, a phytoremediating species. Generally, petroleum pollution reduced plant performance, especially at early stages of plant growth. Petroleum had negative effects on the net accumulation of inorganic nitrogen from its organic forms (net nitrogen mineralization (NNM)) most likely by decreasing the inorganic nitrogen available to the plants in petroleum-polluted soils. However, abundant dissolved organic nitrogen (DON) was found in petroleum-polluted soil. In order to overcome initial deficiency of inorganic nitrogen, plants by dint of high colonization of arbuscular mycorrhizal fungi might absorb some DON for their growth in petroleum-polluted soils. In addition, through using a real-time polymerase chain reaction method, we quantified hydrocarbon-degrading bacterial traits based on their catabolic genes (i.e. alkB (alkane monooxygenase), nah (naphthalene dioxygenase) and tol (xylene monooxygenase) genes). This enumeration of target genes suggests that different hydrocarbon-degrading bacteria experienced different dynamic changes during phytoremediation and a greater abundance of alkB was detected during vegetative growth stages. Because phytoremediation of different components of petroleum is performed by different hydrocarbon-degrading bacteria, plants’ ability of phytoremediating different components might therefore vary during the plant life cycle. Phytoremediation might be most effective during the vegetative growth stages as greater abundances of hydrocarbon-degrading bacteria containing alkB and tol genes were observed at these stages. The information provided by this study enhances our understanding of the effects of petroleum pollution on plant-microbe interactions and the roles of these interactions in the phytoremediation of petroleum-polluted soil