Improved local smoothing estimate for the wave equation in higher dimensions

In this paper, we establish the sharp $k$-broad estimate for a class of phase functions satisfying the homogeneous convex conditions. As an application, we obtain improved local smoothing estimates for the half-wave operator in dimensions $n\ge3$. As a byproduct, we also generalize the restriction estimates of Ou--Wang to a broader class of phase functions.Comment: 32 pages, 3 figures, Referees' suggestions incorporated. To appear in J. Func. Ana

CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation

Nucleus segmentation is a challenging task due to the crowded distribution and blurry boundaries of nuclei. Recent approaches represent nuclei by means of polygons to differentiate between touching and overlapping nuclei and have accordingly achieved promising performance. Each polygon is represented by a set of centroid-to-boundary distances, which are in turn predicted by features of the centroid pixel for a single nucleus. However, using the centroid pixel alone does not provide sufficient contextual information for robust prediction. To handle this problem, we propose a Context-aware Polygon Proposal Network (CPP-Net) for nucleus segmentation. First, we sample a point set rather than one single pixel within each cell for distance prediction. This strategy substantially enhances contextual information and thereby improves the robustness of the prediction. Second, we propose a Confidence-based Weighting Module, which adaptively fuses the predictions from the sampled point set. Third, we introduce a novel Shape-Aware Perceptual (SAP) loss that constrains the shape of the predicted polygons. Here, the SAP loss is based on an additional network that is pre-trained by means of mapping the centroid probability map and the pixel-to-boundary distance maps to a different nucleus representation. Extensive experiments justify the effectiveness of each component in the proposed CPP-Net. Finally, CPP-Net is found to achieve state-of-the-art performance on three publicly available databases, namely DSB2018, BBBC06, and PanNuke. Code of this paper will be released

Development of helium turbine loss model based on knowledge transfer with Neural Network and its application on aerodynamic design

Helium turbines are widely used in the Closed Brayton Cycle for power generation and aerospace applications. The primary concerns of designing highly loaded helium turbines include choosing between conventional and contra-rotating designs and the guidelines for selecting design parameters. A loss model serving as an evaluation means is the key to addressing this issue. Due to the property disparities between helium and air, turbines utilizing either as working fluid experience distinct loss mechanisms. Consequently, directly applying gas turbine experience to the design of helium turbines leads to inherent inaccuracies. A helium turbine loss model is developed by combining knowledge transfer and the Neural Network method to accurately predict performance at design and off-design points. By utilizing the loss model, design parameter selection guidelines for helium turbines are obtained. A comparative analysis is conducted of conventional and contra-rotating helium turbine designs. Results show that the prediction errors of the loss model are below 0.5% at over 90% of test samples, surpassing the accuracy achieved by the gas turbine loss model. Design parameter selection guidelines for helium turbines differ significantly from those based on gas turbine experience. The contra-rotating helium turbine design exhibits advantages in size, weight, and aerodynamic performance

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, currently, the most captivating topic. However, there have been few endeavors dedicated to the exploration of 1) whether essential linguistic knowledge (e.g., semantics and syntax) can be extracted during VLP, and 2) how such linguistic knowledge impact or enhance the multimodal alignment. In response, here we aim to elucidate the impact of comprehensive linguistic knowledge, including semantic expression and syntactic structure, on multimodal alignment. Specifically, we design and release the SNARE, the first large-scale multimodal alignment probing benchmark, to detect the vital linguistic components, e.g., lexical, semantic, and syntax knowledge, containing four tasks: Semantic structure, Negation logic, Attribute ownership, and Relationship composition. Based on our proposed probing benchmarks, our holistic analyses of five advanced VLP models illustrate that the VLP model: i) shows insensitivity towards complex syntax structures and relies on content words for sentence comprehension; ii) demonstrates limited comprehension of combinations between sentences and negations; iii) faces challenges in determining the presence of actions or spatial relationships within visual information and struggles with verifying the correctness of triple combinations. We make our benchmark and code available at \url{https://github.com/WangFei-2019/SNARE/}.Comment: [TL;DR] we design and release the SNARE, the first large-scale multimodal alignment probing benchmark for current vision-language pretrained model

An improved YOLOv5s model for assessing apple graspability in automated harvesting scene

IntroductionWith continuously increasing labor costs, an urgent need for automated apple- Qpicking equipment has emerged in the agricultural sector. Prior to apple harvesting, it is imperative that the equipment not only accurately locates the apples, but also discerns the graspability of the fruit. While numerous studies on apple detection have been conducted, the challenges related to determining apple graspability remain unresolved.MethodsThis study introduces a method for detecting multi-occluded apples based on an enhanced YOLOv5s model, with the aim of identifying the type of apple occlusion in complex orchard environments and determining apple graspability. Using bootstrap your own atent(BYOL) and knowledge transfer(KT) strategies, we effectively enhance the classification accuracy for multi-occluded apples while reducing data production costs. A selective kernel (SK) module is also incorporated, enabling the network model to more precisely identify various apple occlusion types. To evaluate the performance of our network model, we define three key metrics: APGA, APTUGA, and APUGA, representing the average detection accuracy for graspable, temporarily ungraspable, and ungraspable apples, respectively.ResultsExperimental results indicate that the improved YOLOv5s model performs exceptionally well, achieving detection accuracies of 94.78%, 93.86%, and 94.98% for APGA, APTUGA, and APUGA, respectively.DiscussionCompared to current lightweight network models such as YOLOX-s and YOLOv7s, our proposed method demonstrates significant advantages across multiple evaluation metrics. In future research, we intend to integrate fruit posture and occlusion detection to f]urther enhance the visual perception capabilities of apple-picking equipment

The effect of perioperative pelvic floor muscle exercise on urinary incontinence after radical prostatectomy: a meta-analysis

ABSTRACT Background: Pelvic floor muscle exercise (PFME) is the most common conservative management for urinary incontinence (UI) after radical prostatectomy (RP). We performed this meta-analysis to investigate whether PFME during the entire perioperative period, including before and after RP, can significantly improve the recovery of postoperative UI. Methods: We systematically reviewed randomized controlled trials (RCT) from PubMed, Medline, web of science, Cochrane library, and clinicalitrials.com prior to October 2022. Efficacy data were pooled and analyzed using Review Manager Version 5.3. Pooled analyses of urinary incontinence rates 1, 3, 6, and 12 months postoperatively were conducted, using odds ratio (OR) and 95% confidence intervals (CIs). Results: We included a total of 15 RCT studies involving 2178 patients received RP. Postoperative UI could be improved after 1 month, 3 months and 6 months, and the OR were 0.26 (95%CI:0.15-0.46) 0.30 (95%CI: 0.11-0.80) 0.20 (95%CI: 0.07- 0.56) in postoperative PFME group compared to no PFME group. However, there was no significant difference between the two groups in 12 months after surgery, and the OR was 0.85(95%CI: 0.48,1.51). There were similar results in perioperative PFME group compared to no PFME group with the OR of 0.35 (95%CI: 0.12, 0.98) and 0.40 (95%CI: 0.21, 0.75) in 1 and 3 months after surgery. Our results indicated no significant difference between perioperative PFME group and postoperative PFME group. The OR was 0.58 (95%CI: 0.20-1.71) 0.58 (95%CI:0.20-0.71) and 0.66 (95%CI: 0.32-1.38) in 1, 3 and 6 months after surgery. Conclusion: Application of PFME after RP significantly reduced the incidence of early postoperative UI, and additional preoperative PFME had no significant improvement on the recovery of UI

Bubble in the Whale: Identifying the Optical Counterparts and Extended Nebula for the Ultraluminous X-ray Sources in NGC 4631

We present a deep optical imaging campaign on the starburst galaxy NGC 4631 with CFHT/MegaCam. By supplementing the HST/ACS and Chandra/ACIS archival data, we search for the optical counterpart candidates of the five brightest X-ray sources in this galaxy, four of which are identified as ultraluminous X-ray sources (ULXs). The stellar environments of the X-ray sources are analyzed using the extinction-corrected color-magnitude diagrams and the isochrone models. We discover a highly asymmetric bubble nebula around X4 which exhibits different morphology in the H$\alpha$ and [O III] images. The [O III]/H$\alpha$ ratio map shows that the H$\alpha$-bright bubble may be formed mainly via the shock ionization by the one-sided jet/outflow, while the more compact [O III] structure is photoionized by the ULX. We constrain the bubble expansion velocity and interstellar medium density with the MAPPINGS V code, and hence estimate the mechanical power injected to the bubble as $P_w \sim 5\times10^{40}$ erg s$^{-1}$ and the corresponding bubble age of $\sim7\times 10^{5}$ yr. Relativistic jets are needed to provide such level of mechanical power with a mass-loss rate of $\sim10^{-7}\ M_{\odot}\ \rm yr^{-1}$. Besides the accretion, the black hole spin is likely an additional energy source for the super-Eddington jet power.Comment: 17 pages, 10 figures, accepted by Ap

α-Glucosidase Inhibitors From the Coral-Associated Fungus Aspergillus terreus

Nine novel butenolide derivatives, including four pairs of enantiomers, named (±)-asperteretones A–D (1a/1b–4a/4b), and a racemate, named asperteretone E (5), were isolated and identified from the coral-associated fungus Aspergillus terreus. All the structures were established based on extensive spectroscopic analyses, including HRESIMS and NMR data. The chiral chromatography analyses allowed the separation of (±)-asperteretones A–D, whose absolute configurations were further confirmed by experimental and calculated electronic circular dichroism (ECD) analysis. Structurally, compounds 2–5 represented the first examples of prenylated γ-butenolides bearing 2-phenyl-3-benzyl-4H-furan-1-one motifs, and their crucial biogenetically related metabolite, compound 1, was uniquely defined by an unexpected cleavage of oxygen bridge between C-1 and C-4. Importantly, (±)-asperteretal D and (4S)-4-decarboxylflavipesolide C were revised to (±)-asperteretones B (2a/2b) and D (4), respectively. Additionally, compounds 1a/1b–4a/4b and 5 were evaluated for the α-glucosidase inhibitory activity, and all these compounds exhibited potent inhibitory potency against α-glucosidase, with IC50 values ranging from 15.7 ± 1.1 to 53.1 ± 1.4 μM, which was much lower than that of the positive control acarbose (IC50 = 154.7 ± 8.1 μM), endowing them as promising leading molecules for the discovery of new α-glucosidase inhibitors for type-2 diabetes mellitus treatment

Energy Scattering for a Klein-Gordon Equation with a Cubic Convolution

In this paper, we study the global well-posedness and scattering problem in the energy space for both focusing and defocusing the Klein-Gordon-Hartree equation in the spatial dimension $d \geq 3$. The main difficulties are the absence of an interaction Morawetz-type estimate and of a Lorentz invariance which enable one to control the momentum. To compensate, we utilize the strategy derived from concentration compactness ideas, which was first introduced by Kenig and Merle \cite{KM} to the scattering problem. Furthermore, employing technique from \cite{Pa2}, we consider a virial-type identity in the direction orthogonal to the momentum vector so as to control the momentum in the defocusing case. While in the focusing case, we show that the scattering holds when the initial data $(u_0,u_1)$ is radial, and the energy $E(u_0,u_1)<E(\mathcal{W},0)$ and $\|\nabla u_0\|_2^2+\|u_0\|_2^2<\|\nabla \mathcal{W}\|_2^2+\|\mathcal{W}\|_2^2$, where $\mathcal{W}$ is the ground state.Comment: 42pages. We abandon the last version, and we re-study the global well-posedness and scattering problem in the energy space for both focusing and defocusing the Klein-Gordon-Hartree equation by the strategy derived from concentration compactness ideas developed by Kenig and Merle. arXiv admin note: text overlap with arXiv:1001.147

Genome-Wide Scan for Copy Number Variation Association with Age at Onset of Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with high prevalence, which imposes a substantial public health problem. The heritability of AD is estimated at 60–80% forecasting the potential use of genetic biomarkers for risk stratification in the future. Several large scale genome-wide association studies using high frequency variants identified 10 loci accountable for only a fraction of the estimated heritability. To find the missing heritability, systematic assessment of various mutational mechanisms needs to be performed. This copy number variation (CNV) genome-wide association study with age at onset (AAO) of AD identified 5 CNV regions that may contribute to the heritability of AAO of AD. Two CNV events are intragenic causing a deletion in CPNE4. In addition, to further study the mutational load at the 10 known susceptibility loci, CNVs overlapping with these loci were also catalogued. We identified rare small events overlapping CR1 and BIN1 in AD and normal controls with opposite CNV dosage. The CR1 events are consistent with previous reports. Larger scale studies with deeper genotyping specifically addressing CNV are needed to evaluate the significance of these findings