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Infrared ship detection technology plays a crucial role in ensuring maritime transportation and navigation safety. However, infrared ship targets at sea exhibit characteristics such as multi-scale, arbitrary orientation, and dense arrangements, with imaging often influenced by complex sea–sky backgrounds. These factors pose significant challenges for the fast and accurate detection of infrared ships. In this paper, we propose a new infrared ship target detection algorithm, YOLO-IRS (YOLO for infrared ship target), based on YOLOv10, which improves detection accuracy while maintaining detection speed. The model introduces the following optimizations: First, to address the difficulty of detecting weak and small targets, the Swin Transformer is introduced to extract features from infrared ship images. By utilizing a shifted window multi-head self-attention mechanism, the window field of view is expanded, enhancing the model’s ability to focus on global features during feature extraction, thereby improving small target detection. Second, the C3KAN module is designed to improve detection accuracy while also addressing issues of false positives and missed detections in complex backgrounds and dense occlusion scenarios. Finally, extensive experiments were conducted on an infrared ship dataset: compared to the baseline model YOLOv10, YOLO-IRS improves precision by 1.3%, mAP50 by 0.5%, and mAP50–95 by 1.7%. Compared to mainstream detection algorithms, YOLO-IRS achieves higher detection accuracy while requiring relatively fewer computational resources, verifying the superiority of the proposed algorithm and enhancing the detection performance of infrared ship targets.

A multiscale regulation strategy has been demonstrated for synthetic energy storage enhancement in a tetragonal tungsten bronze structure ferroelectric. Grain refining and second-phase precipitation (perovskite phase) are introduced in the BaSrTiNb 2-x Ta x O 9 ceramics by regulating the composition and sintering process. Disordered polarization and distribution, chemical inhomogeneity, and insulating boundary layers are achieved to provide the fundamental structural origin of the relaxation characteristic, high breakdown strength, and superior energy storage performance. Thus, an ultrahigh energy storage density of 12.2 J cm −3 with an low energy consumption was achieved at an electric field of 950 kV cm −1 . This is the highest known energy storage performance in tetragonal tungsten bronze-based ferroelectric. Notably, this ceramic shows remarkable stability over frequency, temperature, and cycling electric fields. This work brings new material candidates and structure design for developing of energy storage capacitors apart from the predominant perovskite ferroelectric ceramics. The authors enhance energy storage performance in tetragonal tungsten bronze structure ferroelectrics using a multiscale regulation strategy. By adjusting the composition and sintering process of BaSrTiNb 2-x Ta x O 9 ceramics, they introduce grain refinement and perovskite second-phase precipitation.

As a sport conducted in dynamically changing natural environments, orienteering places high demands on athletes' cognitive processing abilities and visual search efficiency. However, previous studies on orienteering have been primarily limited by the use of fixed stimulus materials on computer screens, which are unable to fully simulate authentic sports scenarios. To better understand the sports expertise of orienteering athletes in terms of their real scene image recognition performance and visual search characteristics, this study recruited 40 orienteering athletes, both experts and novices, as participants. By utilizing eye-tracking technology and setting observation points in real-world scenarios to conduct image recognition task tests, the ecological validity of the experiment was further enhanced. The results showed that the experts demonstrated a high level of accuracy and a short response time, with visual search characteristics including few saccade counts, low fixation frequency, concentrated fixation points, simple and clear fixation paths, and higher visual search efficiency. This study further reveals that long-term specialized training will lead to the formation of a unique cognitive structure related to the specific knowledge and long-term memory required by expert orienteering athletes, thereby promoting the development of expert advantage.

To facilitate the full-pulse sequence received by a radar reconnaissance receiver, this study proposed a clustering segmentation method for radar signals. Owing to the influence of the complex electromagnetic environment, the probability of the occurrence of time–frequency overlapping of signals increases, and the demand for signal localization and classification becomes higher. However, most existing studies have only classified and identified individual pulse signals and lack the ability to analyze signals for full pulses. This study proposed a multi-radar cluster-based segmentation network (MRCS-Net) for large time-length full-pulse signals. The network innovatively addresses the processing challenges of prolonged full-pulse signals and effectively achieves the classification and recognition of different pulses under time–frequency overlapping conditions. The proposed algorithm filters the signal with SincNet and then sequentially feeds the sequence into a long short-term memory network. Consequently, the outputs are clustered and segmented using multilayer perceptrons and classifiers. Experiments were conducted on six different types of radar signals. The results demonstrated that the proposed method exhibited lower segmentation error rate metric compared to other similar methods. Moreover, it outperformed other methods in terms of recognition performance.

Despite advances in DNA methylome analyses of cells and tissues, current techniques for genome-scale profiling of DNA methylation in circulating cell-free DNA （ccfDNA） remain limited. Here we describe a methylated CpG tan- dems amplification and sequencing （MCTA-Seq） method that can detect thousands of hypermethylated CpG islands simultaneously in ccfDNA. This highly sensitive technique can work with genomic DNA as little as 7.5 pg, which is equivalent to 2.5 copies of the haploid genome. We have analyzed a cohort of tissue and plasma samples （n = 151） of hepatocellular carcinoma （HCC） patients and control subjects, identifying dozens of high-performance markers in blood for detecting smaU HCC （≤ 3 cm）. Among these markers, 4 （RGS10, ST8SIA6, RUNX2 and VIM） are mostly specific for cancer detection, while the other 15, classified as a novel set, are already hypermethylated in the normal liver tissues. Two corresponding classifiers have been established, combination of which achieves a sensitivity of 94% with a specificity of 89% for the plasma samples from HCC patients （n = 36） and control subjects including cirrho- sis patients （n = 17） and normal individuals （n = 38）. Notably, all 15 alpha-fetoprotein-negative HCC patients were successfully identified. Comparison between matched plasma and tissue samples indicates that both the cancer and noncancerous tissues contribute to elevation of the methylation markers in plasma. MCTA-Seq will facilitate the development of ccfDNA methylation biomarkers and contribute to the improvement of cancer detection in a clinical setting.

Among various efficient electrocatalysts for water splitting, CoFe and NiFe-based oxides/hydroxides are typically promising candidates thanks to their extraordinary activities towards oxygen evolution reaction (OER). However, the endeavor to advance their performance towards overall water splitting has been largely impeded by the limited activities for hydrogen evolution reaction (HER). Herein, we present a CoFeNi ternary metal-based oxide (CoFeNi-O) with impressive hierarchical bimodal channel nanostructures, which was synthesized via a facile one-step dealloying strategy. The oxide shows superior catalytic activities towards both HER and OER in alkaline solution due to the alloying effect and the intrinsic hierarchical porous structure. CoFeNi-O loaded on glass carbon electrodes only requires the overpotentials as low as 230 and 278 mV to achieve the OER current densities of 10 and 100 mA·cm −2 , respectively. In particular, extremely low overpotentials of 200 and 57.9 mV are sufficient enough for Ni foam-supported CoFeNi-O to drive the current density of 10 mA·cm −2 towards OER and HER respectively, which is comparable with or even better than the already-developed state-of-the-art non-noble metal oxide based catalysts. Benefiting from the bifunctionalities of CoFeNi-O, an alkaline electrolyzer constructed by the Ni foam-supported CoFeNi-O electrodes as both the anode and the cathode can deliver a current density of 10 mA·cm −2 at a fairly low cell-voltage of 1.558 V. In view of its electrocatalytic merits together with the facile and cost-effective dealloying route, CoFeNi-O is envisioned as a promising catalyst for future production of sustainable energy resources.

In this paper, we consider a class of fractional advection–dispersion equations involving instantaneous and non-instantaneous impulses. The existence of nontrivial solutions is established via Bonanno and D’Aguì’s critical point theorem. Under suitable conditions, we further prove the nonexistence of nontrivial solutions, which is the new result. Additionally, the application of our main results is demonstrated through two examples.

The automatic modulation recognition (AMR) of radar signals has become a popular research topic in recent years. However, most algorithms focus on the type of signal modulation and lack further understanding of the signal. To address this gap, a network architecture for multi‐tasking intra‐pulse description words (MIDW‐Net) is proposed herein. In this framework, the denoising algorithm employs a convolutional denoising autoencoder, which is an effective method for suppressing noise interference and preserving signal information. The multiscale feature‐extraction capability of a feature pyramid network (FPN) is utilized to expand the perceptual domain without losing the high‐frequency features of the image. Finally, AMR and modulation parameter estimation are accomplished via multitask learning. Experiments performed on simulated radar signals using four intra‐pulse descriptors verified the effectiveness of the proposed algorithm. A multi‐tasking network architecture, namely multi‐tasking intra‐pulse description words (MIDW‐Net), for intra‐pulse description word extraction was proposed to address the simultaneous tasks of automatic modulation recognition and modulation parameter estimation layer of radar signals. The proposed MIDW‐Net consists of a noise reduction network, feature pyramid network, and multiple convolutional networks for task‐specific layers.

It is a very difficult work to sinter K 0.5 Na 0.5 NbO 3 (KNN)-based materials with good reduction resistance in strong reducing atmosphere. 0.945K 0.48 Na 0.52 Nb 0.96 Ta 0.04 O 3 −0.055BaZrO 3 + 0.03ZrO 2 + y mol%MnO (KNNT−0.055BZ + 0.03Zr + y Mn) ceramics sintered in reducing atmosphere were prepared successfully by conventional solid-state reaction methods. MnO dopant increases grain size at y = 5–8 due to strong lattice distortion and then decreases grain size at y = 9 due to much Mn 4 Nb 2 O 9 accumulated at the grain boundary. MnO dopant as an excellent sintering aid can effectively reduce volatilization of alkali metal by decreasing the sintering temperature ( T sinter ). Reducing alkali metal volatilization can greatly reduce oxygen vacancies and improve piezoelectric properties. MnO dopant can improve the anti-reduction properties. The KNNT−0.055BZ + 0.03Zr + y Mn ceramics at y = 6–9 show outstanding anti-fatigue of unipolar piezoelectric strain under the synergistic effect of reduced oxygen vacancies due to reduced volatilization and increased grain size. Piezoelectric properties and temperature stability of KNNT−0.055BZ + 0.03Zr ceramics sintered in reducing atmosphere are improved simultaneously by MnO dopant. Optimum inverse piezoelectric coefficient ( d 33 * ) of ceramics at y = 8 reaches up to 480 pm/V under low driving electric field E = 20 kV/cm at room temperature, and its temperature stability of d 33 * reaches 158 °C. It will be an excellent lead-free material candidate for the preparation of multilayer piezoelectric actuators co-fired with nickel electrode.

Based on the spectral analysis method, Gelfand’s formula, and the cones fixed point theorem, some positive solutions with their existence of a nonlinear infinite-point Hadamard fractional-order differential equation is achieved on the interval [a, b] under some conditions, and particularly the nonlinear term allows singularities for time and spatial parameters in the present study. Finally, an analysis case is carried out to reveal the principal results.