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Various symbiotic/associated oil and gas resources have been found in the exploration area of Shengli Oilfield， and some of them serve as strategic resources for guaranteeing the security of national defense， agriculture， high-tech， and other industries， which are of great value in development and utilization. The current exploration and development status， occurrence characteristics， ore-forming conditions， and comprehensive utilization prospects of helium， brine （potassium salt）， and uranium ore that have been deeply studied and industrially produced in China were analyzed. The results show that ① the high helium anomalies are mainly distributed in more than 10 areas of the Jiyang Depression and Qaidam Basin， as well as in multiple layers of the Proterozoic-Cenozoic， associated with conventional natural gas， non-hydrocarbon gas， and shale gas； ② Jiyang Depression and Qaidam Basin provide the paleoclimate and palaeoenvironment for developing brine （potassium salt） from the Paleogene to the Quaternary. The oilfield water in Dongying Sag contains abundant amounts of bromine， lithium， and potassium， and more potassium and lithium are found in the oilfield water in Qaidam Basin， with the content in some areas reaching industrial grade； ③ the sandstone is the primary type of uranium ore. The multiple wells in Chepaizi Uplift exhibit highly abnormal gamma values in the Cretaceous and Neogene， indicating that this area is the most favorable prospective area of associated uranium ore. In other exploration areas of Shengli Oilfield， such as Tuha Basin， Qaidam Basin， and Jiyang Depression， the forming conditions for uranium ore are observed， including uranium sources， structures， lithofacies， hydrogeology， etc.， and natural gamma logging data from some wells show high abnormal values. Overall， the symbiotic/associated oil and gas resources in the exploration area of Shengli Oilfield show the characteristics of various types， multiple layers， and wide abnormal areas. It is necessary to fully take the natural advantages of Shengli Oilfield in terms of basic exploration data， basic geological achievements， and engineering facilities，to systematically carry out research on the reservoir forming （ore-forming） law of symbiotic/associated oil and gas resources， evaluate resource potential， and innovate extraction technology as soon as possible， to achieve a new business growth pole.

Cylindrical vector beams (CVBs) hold considerable promise as high-capacity information carriers for multiplexing holography due to their mode orthogonality. In CVB holography, phase holograms are encoded onto the wave-front of CVBs with different mode orders while preserving their independence during reconstruction. However, a major challenge lies in the limited ability to manipulate the spatial phase and polarization distribution of CVBs independently. To address this challenge, we propose a spin-decoupled phase modulation strategy by leveraging the propagation and geometric phase of composite phase metasurfaces. By exploiting the polarized Poincaré sphere, we show that CVBs can be decomposed into two circularly polarized components with orthogonal polarization states and conjugate phase distributions. This decomposition enables independent control of the phase and polarization distributions of CVBs by modulating the initial phase and phase difference of these two components. Consequently, two holograms with discrete spatial frequency distributions that carry opposite helical phases are encoded to modulate the wave-front of CVBs by the metasurface consisting of Si nanopillars. This allows for us to achieve successful four-channel CVB multiplexing holography. Benefiting from the non-dispersive nature of geometric phase, this metasurface exhibits a broad operating band spanning the entire visible light spectrum (443 nm–633 nm). These suggest that our proposed method offers comprehensive control over the spatial phase and polarization of CVBs, thereby holding significant potential for advancing their application in holography.

Vortex beams (VBs) carrying orbital angular momentum (OAM) have shown promising potential in enhancing communication capacity through the possession of multiple multiplexing dimensions involving the OAM mode, polarization, and wavelength. Although many research works on multidimensional multiplexing have been conducted, the (de)multiplexer compatible with these dimensions remains elusive. Following the expanded concept of the Pancharatnam–Berry (PB) phase, we designed a polarization-dependent phase-modulation metasurface to phase-modulate the two orthogonal linearly polarized components of light, and two Dammann vortex gratings with orthogonal polarization responses were loaded to simultaneously (de)multiplex OAM mode and polarization channels. As a proof of concept, we constructed a 16-channel multidimensional multiplexing communication system (including two OAM modes, two polarization states, and four wavelengths), and 400 Gbit/s quadrature-phase shift-keying (QPSK) signals were transmitted. The results demonstrate that the OAM mode and polarization channels are successfully (de)multiplexed, and the bit-error-rates (BERs) are below 1.67 × 10−6 at the received power of −15 dBm.

Calcium sulfate is an established carrier for localized drug delivery, but a means to non‐invasively measure drug release, which would improve our understanding of localized delivery, remains an unmet need. We aim to quantitatively estimate the diffusion‐controlled release of small molecules loaded into a calcium sulfate carrier through a gadobutrol‐based contrast agent, which acts as a surrogate small molecule. A central cylindrical core made of calcium sulfate, either alone or within a metal scaffold, is loaded with contrast agents that release into agar. Multi‐echo scans are acquired at multiple time points over 4 weeks and processed into R2* and quantitative susceptibility mapping (QSM) maps. Mean R2* values are fit to a known drug delivery model, which are then compared with the decrease in core QSM. Fitting R2* measurements of calcium sulfate core while constraining constants to a drug release model results in an R2‐value of 0.991, yielding a diffusion constant of 4.59 × 10−11 m2 s−1. Incorporating the carrier within a metal scaffold results in a slower release. QSM shows the resulting loss of susceptibility in the non‐metal core but is unreliable around metal. R2* characterizes the released gadobutrol, and QSM detects the resulting decrease in core susceptibility. The addition of a porous metal scaffold slows the release of gadobutrol, as expected. [ABSTRACT FROM AUTHOR]

Research on the interfacial instability of two‐phase systems can help in gaining a better understanding of various hydrodynamic instabilities in nature. However, owing to the nonlinear and complex spatiotemporal dynamics of the unstable interface, the instability is challenging to control and suppress. This paper presents a novel interfacial instability of the magnetic microswarm induced by the competition between the destabilizing effect of magnetic field and the stabilizing effect of acoustic field. The physics underlying this novel phenomenon is discussed by analyzing the contributions of the external fields. Unlike previous studies, this study demonstrates that the instability is independent of the interfacial force or diffusion effect and can persist without dissipation over time. The manipulation of the unstable interface is further achieved by adjusting the configuration of the magneto‐acoustic system. This approach can be used in thermal encoding metamaterials and has great potential applications in systems where the instability is detrimental. [ABSTRACT FROM AUTHOR]

Building on the observation of gaps in current research, this study provides a comprehensive analysis of the spatial patterns of heritage sites along the Silk Road, focusing on how historical trade routes shaped what are now recognized as heritage sites. Using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage List, the research examines heritage sites across Eurasia and North Africa, with a specific emphasis on the Silk Road corridors. This study employs a spatiotemporal approach, categorizing sites into northern overland routes and southern maritime routes to highlight regional variations in network development. The key findings of this study reveal the significant influence of historical trade routes on the development of settlements, cities, and cultural landmarks along the Silk Road. These findings identify clear trends in the Silk Road network's evolution over time, illustrating a shift in its spatial focus across different historical periods. Initially, the network was centered in the eastern Mediterranean during the Classical Period. In the medieval period, this focus expanded to include a dual core area in both the eastern Mediterranean and Central Asia. By the late Medieval period, the network had shifted again, with a new core emerging in Europe. This chronological and spatial analysis allows for a detailed examination of the Silk Road network's heritage landscape evolution. The study underscores the interconnectedness of heritage sites across these regions, contributing to a deeper understanding of how landscape connectivity and trade network dynamics evolved over time. Furthermore, by identifying patterns of network development and shifts in centrality and density, this research offers valuable insights for the conservation and management of heritage landscapes. These findings are particularly crucial for preserving the historical and cultural integrity of Silk Road heritage sites. [ABSTRACT FROM AUTHOR]

Background and purpose: Thrombus red blood cell (RBC) content has been shown to be a significant factor influencing the efficacy of acute ischemic stroke treatment. In this study, our objective was to evaluate the ability of convolutional neural networks (CNNs) to predict ischemic stroke thrombus RBC content using multiparametric MR images. Materials and methods: Retrieved stroke thrombi were scanned ex vivo using a three-dimensional multi-echo gradient echo sequence and histologically analyzed. 188 thrombus R2*, quantitative susceptibility mapping and late-echo GRE magnitude image slices were used to train and test a 3-layer CNN through cross-validation. Data augmentation techniques involving input equalization and random image transformation were employed to improve network performance. The network was assessed for its ability to quantitatively predict RBC content and to classify thrombi into RBC-rich and RBC-poor groups. Results: The CNN predicted thrombus RBC content with an accuracy of 62% (95% CI 48–76%) when trained on the original dataset and improved to 72% (95% CI 60–84%) on the augmented dataset. The network classified thrombi as RBC-rich or poor with an accuracy of 71% (95% CI 58–84%) and an area under the curve of 0.72 (95% CI 0.57–0.87) when trained on the original dataset and improved to 80% (95% CI 69–91%) and 0.84 (95% CI 0.73–0.95), respectively, on the augmented dataset. Conclusions: The CNN was able to accurately predict thrombus RBC content using multiparametric MR images, and could provide a means to guide treatment strategy in acute ischemic stroke. [ABSTRACT FROM AUTHOR]

This article investigates the experiences of Yi migrant workers in Shenzhen factories through a conceptual framework that focuses on three dimensions of home in migration. Examining industrial dormitories, the foreman system, and governmental attention, it uncovers the intricate ways migrants negotiate their sense of belonging. The spatial dimension is evident in dormitories offering a semblance of home while reflecting broader societal and economic influences. The relational aspect emerges through the evolution of the foreman system, highlighting the interplay between traditional social bonds and modern labour demands. The sensorial dimension becomes apparent in the limited recognition migrants receive despite their contributions. This study underscores the multifaceted nature of migrant experiences as well as the need for comprehensive understandings of home that encompass spatial, relational, and sensorial elements within the dynamic context of migration. [ABSTRACT FROM AUTHOR]

Hybrid neural network models are effective in analyzing time-series data by combining the strengths of neural networks and differential equation models. Although most studies have focused on linear hybrid models, few have examined nonlinear problems. This work explores the potential of a hybrid nonlinear epidemic neural network in predicting the correct infection function of an epidemic model. We design a novel loss function by combining bifurcation theory and mean-squared error loss to ensure the trainability of the hybrid model. Additionally, we identify unique existence conditions that support ordinary differential equations for estimating the correct infection function. Moreover, numerical experiments using the Runge–Kutta method confirm our proposed model's soundness both on our synthetic data and the real COVID-19 data. [ABSTRACT FROM AUTHOR]