Search Results (5,914)

The complexity of tight sandstone reservoirs challenges effective oil and gas exploration. The Chang 8 Member of the Yanchang Formation in the Longdong area of the Ordos Basin has significant exploration potential. However, its reservoir characteristics are controlled by two distinct provenance systems and diverse sedimentary microfacies. The specific impacts of these factors on reservoir quality and their relative importance have remained unclear. This study employs an integrated analytical approach combining casting thin sections, conventional porosity-permeability measurements, and Nuclear Magnetic Resonance (NMR) to systematically investigate the petrological characteristics, pore structure, and physical properties of the Chang 8 reservoirs. Our findings reveal that the entire section of Chang 8 is a delta front subfacies, with sub sections of Chang 8¹ and 8² developing microfacies such as underwater distributary channels, underwater natural levees, sheet sand and mouth bars. The tight sandstone reservoir is mainly composed of lithic arkose and feldspathic litharenite, with its porosity dominated by dissolution and intergranular types. These secondary pores, particularly those resulting from feldspar dissolution, are of great importance. The underwater distributary channels have the best pores, followed by sheet sands, and underwater natural levees the worst. Compaction in Chang 8² is stronger than in Chang 8¹, leading to smaller pores. The northwest provenance is characterized by high clay content and small pores, while the southwest provenance has coarser grain size and better-preserved intergranular pores. Reservoir properties improve toward the lake but deteriorate at the lake-proximal end due to more small pores. This study reveals the control laws of sedimentary microfacies, provenance, and diagenesis on the pore development of tight sandstone in the Longdong area, providing theoretical guidance for the exploration and development of tight sandstone oil and gas in the region. Full article

Frequent channel migrations of the Yellow River, coupled with increasing human disturbances, have driven significant land cover changes in the Yellow River Delta (YRD) over time. Accurate estimation of aboveground biomass (AGB) and clarification of the impact of land cover changes on AGB are crucial for monitoring vegetation dynamics and supporting ecological management. However, field-based biomass samples are often time-consuming and labor-intensive, and the quantity and quality of such samples greatly affect the accuracy of AGB estimation. This study developed a robust AGB estimation framework for the YRD by synthesizing 4717 field-measured samples from the published scientific literature and integrating two critical ecological indicators: leaf area index (LAI) and length of growing season (LGS). A random forest (RF) model was employed to estimate AGB for the YRD from 2001 to 2022, achieving high accuracy (R² = 0.74). The results revealed a continuous spatial expansion of AGB over the past two decades, with higher biomass consistently observed in western cropland and along the Yellow River, whereas lower biomass levels were concentrated in areas south of the Yellow River. AGB followed a fluctuating upward trend, reaching a minimum of 204.07 g/m² in 2007, peaking at 230.79 g/m² in 2016, and stabilizing thereafter. Spatially, western areas showed positive trends, with an average annual increase of approximately 10 g/m², whereas central and coastal zones exhibited localized declines of around 5 g/m². Among the changes in land cover, cropland and wetland changes were the main contributors to AGB increases, accounting for 54.2% and 52.67%, respectively. In contrast, grassland change exhibited limited or even suppressive effects, contributing −6.87% to the AGB change. Wetland showed the greatest volatility in the interaction between area change and biomass density change, which is the most uncertain factor in the dynamic change in AGB. Full article

In the context of China’s increasingly competitive agricultural product branding, authenticity has become a pivotal mechanism for shaping consumer trust and willingness to pay. This study takes Perceived Brand Authenticity (PBA) as its focal construct and builds a chained mediation framework incorporating experiential quality (EQ) and consumer trust. Employing a dual-evidence strategy that combines structural discovery and causal validation, the study integrates Jaccard similarity clustering and PLS-SEM to examine both behavioral patterns and psychological mechanisms. Drawing on 636 valid survey responses from across China, the results reveal clear segmentation in channel choice, certification concern, and premium acceptance by gender, age, income, and education. Younger and highly educated consumers rely more on e-commerce and digital traceability, while middle-aged, older, and higher-income groups emphasize geographical indications and organic certification. The empirical analysis confirms that PBA has a significant positive effect on EQ and consumer trust, and that the chained mediation pathway “PBA → EQ → Trust → Purchase Intention” robustly captures the transmission mechanism of authenticity. The findings demonstrate that verifiable and consistent authenticity signals not only shape cross-group consumption structures but also strengthen trust and repurchase intentions through enhanced experiential quality. The core contribution of this study lies in advancing an evidence-based framework for sustainable agricultural branding. Theoretically, it reconceptualizes authenticity as a measurable governance mechanism rather than a rhetorical construct. Methodologically, it introduces a dual-evidence approach integrating Jaccard clustering and PLS-SEM to bridge structural and causal analyses. Practically, it proposes two governance tools—“evidence density” and “experiential variance”—which translate authenticity into actionable levers for precision marketing, trust management, and policy regulation. Together, these insights offer a replicable model for authenticity governance and consumer trust building in sustainable agri-food systems. Full article

Within the context of global climate change and China’s commitment to the “Dual Carbon” goals (carbon peak and carbon neutrality), this study proposes a novel taxonomy of market-based environmental regulations, dividing them into investment-driven and tax-based supervisory mechanisms. Using panel data from 30 Chinese provinces between 2010 and 2023, we empirically investigate their differential effects on carbon emissions. Results indicate that both regulatory approaches significantly curb carbon emissions, each exhibiting distinct nonlinear patterns: an inverted-U curve for investment-oriented measures and a U-shaped trajectory for tax-oriented policies, implying that excessively stringent tax supervision may lead to a rebound in emissions due to effects such as the “resource curse” and “innovation crowding-out.” Industrial structure transformation functions as a common mediating channel, while green innovation efficiency exerts a distinct moderating influence. Both policy types demonstrate adverse spatial spillover effects, with no support found for the “pollution haven” or “race to the bottom” hypotheses. This study offers new empirical insights into how environmental regulations facilitate green and low-carbon transition through market mechanisms, providing valuable implications for designing ecological policy systems that harmonize emission reduction efficiency with sustainability in China and other emerging economies. Full article

Background: Optimizing training load and recovery is crucial for achieving peak performance in competitive wrestling, a sport characterized by high physical, technical, and psychological demands. Methods: This study compared the effects of two different training programs—one emphasizing high-intensity interval training (HIIT) sessions and the other based on traditional volume-oriented training—on both competitive performance and autonomic regulation measured by heart rate variability (HRV). A total of 24 elite wrestlers were divided into two equal groups, each following a different weekly training regimen over a 3-month period. HRV was recorded using a wearable 3-channel ECG Holter before training, immediately after training, and during recovery phases (up to 2 h post-exercise). HRV parameters were analyzed to assess training-induced stress and recovery status. Competitive performance was evaluated using official national championship scores and ranking positions. Results: Both training programs improved competitive performance, the HIIT-based regimen induced greater short-term suppression of parasympathetic activity (RMSSD: −32% vs. −14%; HF power: −40% vs. −18%) and increased sympathetic dominance (LF/HF: +56% vs. +22%) after training. Wrestlers in the HIIT group achieved a mean competition score of 17.92 ± 4.50 points, compared to 15.08 ± 6.26 points in the volume-oriented group. These acute autonomic shifts may provide a higher readiness for intense and explosive actions, which is advantageous in short and dynamic matches. In contrast, the volume-oriented program induced smaller acute autonomic changes but showed a slower recovery to baseline. Conclusions: These findings suggest that HRV-derived measures can serve as sensitive indicators of training load tolerance, recovery capacity, and stress susceptibility in combat sports athletes. This study highlights the value of integrating HRV monitoring into the periodization of combat training to individualize the load, prevent overtraining, and optimize performance outcomes. Full article

Multispectral LiDAR (MSL) systems offer a significant advantage by actively capturing both spatial and spectral information. These systems offer significant promise in supporting the comprehensive analysis and precise classification of underwater targets. In this study, we build an MSL system based on an acousto-optic tunable filter (AOTF) to investigate the feasibility of underwater sphere classification. The MSL prototype features a spectral resolution of 20 nm and 13 spectral channels, covering a range from 560 to 800 nm. Laboratory-based experiments were conducted to evaluate the accuracy of range measurements and the classification performance of the system. The spectral curves of nine distinct spheres acquired by the MSL were utilized for classification using a support vector machine (SVM). The experimental results indicate that classification using multispectral data yields a higher accuracy and Kappa coefficient. Finally, the point cloud acquired from scanning experiments further validated the MSL system’s performance. This finding preliminarily validates the feasibility of multispectral LiDAR for classifying submerged spherical targets. Full article

Swimming ability is an important means for shrimp to survive in a water environment. To investigate the effects of different body lengths (L₁: 6.5 ± 0.25 cm, L₂: 8.8 ± 0.16 cm, and L₃: 11.5 ± 0.28 cm) and different measurement methods on the measured critical swimming speeds (U_crit), this study used experimental ecology methods to determine the U_crit of three body length (BL) groups of whiteleg shrimp (Litopenaeus vannamei) at different time intervals (10, 20, 30, 40, and 50 min) and speed increments (1/2 BL s⁻¹, 3/4 BL s⁻¹, and BL s⁻¹) in a biological swimming channel. The results showed that the time interval and speed increment significantly affected the U_crit. In the small-body-length group (L₁), the U_crit of the shrimp decreased and then increased as the time interval increased, with no significant difference between time intervals or velocity increments. In the medium-body-length group (L₂), at the speed increment of 1/2 BL s⁻¹, the U_crit of the shrimp under the time interval < 40 min was significantly greater than that in the other treatment groups. At the speed increment of 1/2 BL s⁻¹, the U_crit of the shrimp decreased as the time interval increased. At the speed increment of 3/4 BL s⁻¹, the U_crit of the shrimp showed a trend of decreasing and then increasing with increasing time interval, and at a high-speed increment (BL s⁻¹), the time interval had no significant effect on U_crit. In the large-body-length group (L₃), at the speed increment of 1/2 BL s⁻¹, the U_crit of the shrimp under the time interval < 30 min was significantly higher than that in the other treatment groups. The effect of the time interval on U_crit was not significant at high-speed increments, and U_crit decreased with increasing time interval only at the speed increment of 1/2 BL s⁻¹. This study showed that, in the small-body-length group, the time increment has a more significant effect on the critical swimming speed, and, as the body length increases, both the time increment and velocity increment affect the critical swimming speed. When the time interval is 20 min and the speed increment is 1/2 BL s⁻¹, the measured U_crit is the closest to the appropriate value. Full article

This study reports on the synthesis, structural characterization and gas sorption studies of a homometallic 2D Cd²⁺ MOF and two heterometallic 3D Cd²⁺/Ca²⁺ and Cd²⁺/Sr²⁺ -MOFs based on the angular tetracarboxylic ligand 3,3′,4,4′-sulfonyltetracarboxylic acid (H₄STBA). The homometallic 2D Cd²⁺ MOF with the formula [NH₂(CH₃)₂]⁺₂[Cd(STBA)]²⁻_n·nDMF·1.5nH₂O—(1)_n·nDMF·1.5nH₂O was synthesized from the reaction of CdCl₂·H₂O and 3,3′,4,4′-diphthalic sulfonyl dianhydride (3,3′,4,4′-DPSDA) with stoichiometric ratio of 1:1.3 in DMF/H₂O (5/2 mL) at 100 °C. The two heterometallic Cd²⁺/Ca²⁺ and Cd²⁺/Sr²⁺ compounds were prepared from analogous reactions to this afforded (1)_n·nDMF·1.5nH₂O with the difference that the reaction mixture also contained AE(NO₃)₂ (AE²⁺ = Ca²⁺ or Sr²⁺) and, in particular, from the reaction of AE(NO₃)₂, CdCl₂·H₂O and 3,3′,4,4′-DPSDA with stoichiometric ratio 1:1.1:1.4 in DMF/H₂O (5/2 mL) at 100 °C. Notably, compounds [CdCa(STBA)(H₂O)₂]_n·0.5nDMF—(2)_n·0.5nDMF and [CdSr(STBA)(H₂O)₂]_n·0.5nDMF—(3)_n·0.5nDMF are the first heterometallic compounds Mⁿ⁺/AE²⁺ (M = any metal ion) reported containing ligand H₄STBA. The structure of (1)_n·nDMF·1.5nH₂O comprises a 2D network based on helical 1D chain secondary building unit (SBU) [Cd²⁺(STBA)⁴⁻)]²⁻. The 2D sheets are linked through hydrogen bonding interactions, giving rise to a pseudo-3D structure. On the other hand, compounds (2)_n·1.5nH₂O and (3)_n·1.5nH₂O display 3D microporous structures consisting of a helical 1D chain SBU [Cd²⁺AE²⁺(STBA)⁴⁻)]. All three compounds contain rhombic channels along c axes. The three MOFs exhibit an appreciable thermal stability, up to 350–400 °C. Gas sorption measurements on activated materials (2)_n and (3)_n revealed moderate BET surface areas of 370 m²/g and 343 m²/g, respectively, along with CO₂ uptake capacity of 2.58 mmol/g at 273 K. Full article

Molecular communication (MC) has emerged as a promising paradigm for nanoscale information exchange in Internet of Bio-Nano Things (IoBNT) environments, offering intrinsic biocompatibility and potential for real-time in vivo monitoring. This study proposes a cascaded MC channel framework for vascular stenosis detection, which integrates non-Newtonian blood rheology, bell-shaped constriction geometry, and adsorption–desorption dynamics. Path delay and path loss are introduced as quantitative metrics to characterize how structural narrowing and molecular interactions jointly affect signal propagation. On this basis, a peak response time-based delay inversion method is developed to estimate both the location and severity of stenosis. COMSOL 6.2 simulations demonstrate high spatial resolution and resilience to measurement noise across diverse vascular configurations. By linking nanoscale transport dynamics with system-level detection, the approach establishes a tractable pathway for the early identification of vascular anomalies. Beyond theoretical modeling, the framework underscores the translational potential of MC-based diagnostics. It provides a foundation for non-invasive vascular health monitoring in IoT-enabled biomedical systems with direct relevance to continuous screening and preventive cardiovascular care. Future in vitro and in vivo studies will be essential to validate feasibility and support integration with implantable or wearable biosensing devices, enabling real-time, personalized health management. Full article

Quantum information quantities, such as mutual information and entropies, are essential for characterizing quantum systems and protocols in quantum information science. In this contribution, we identify types of information measures based on generalized divergences and prove their invariance under local isometric or unitary transformations. Leveraging the reversal channel for local isometries together with the data-processing inequality, we establish invariance for information quantities used in both asymptotic and one-shot regimes without relying on the specific functional form of the underlying divergence. These invariances can be applied to improve the computation of such information quantities or optimize protocols and their output states, whose performance is determined by some invariant measure. Our results improve the capability to characterize and compute many operationally relevant information measures with application across the field of quantum information processing. Full article

Optogenetics leverages light to control neural circuits, but traditional systems are often bulky and tethered, limiting their use. This work introduces OptoBrain, a novel, portable wireless system for optogenetics designed to overcome these challenges. The system integrates modules for multichannel data acquisition, smart neurostimulation, and continuous processing, with a focus on low-power and low-voltage operation. OptoBrain features up to eight neuronal acquisition channels with a low input-referred noise (e.g., 0.99 µVRMS at 250 sps with 1 V/V gain), and reliably streams data via a Bluetooth 5.0 link at a measured throughput of up to 400 kbps. Experimental results demonstrate robust performance, highlighting its potential as a simple, practical, and low-cost solution for emerging optogenetics research centers and enabling new avenues in neuroscience. Full article

Understanding the functional modulation of ion channels by multiple activating substances is critical to grasping stimulus-specific gating mechanisms and possible synergistic or competitive interactions. This study investigates the activation of large-conductance, voltage- and Ca²⁺-activated potassium channels (BK) in the plasma membrane of human bronchial epithelial cells by Ca²⁺ and quercetin (Que), both individually and in combination. Patch-clamp recordings were analyzed using open state probability, dwell-time distributions, Shannon entropy, sample entropy, power spectral density (PSD), and empirical mode decomposition (EMD). Our results reveal concentration-dependent alterations in gating kinetics, particularly at a low concentration of quercetin ([Que] = 10 μM) compared with [Que] = 100 μM, where some Que-related effects are strongly attenuated in the presence of Ca²⁺. We also identify specific frequency bands where oscillatory components are most sensitive to the considered stimuli. Our findings highlight the complex reciprocal interplay between Ca²⁺ and Que in modulating BK channel function, and demonstrate the interpretative power of entropic and signal-decomposition approaches in characterizing stimulus-specific gating dynamics. Full article

At a particular frequency, most materials and objects of interest exhibit a polarization signature, or Mueller matrix, of limited dimensionality, with many matrix elements either negligibly small or redundant due to symmetry. Robust design of a polarization sensor for a particular material or object of interest, or for an application with a limited set of materials or objects, will adapt to the signature subspace, as well as the available modulators, in order to avoid unnecessary measurements and hardware and their associated budgets, errors, and artifacts. At the same time, measured polarization features should be expressed in the Stokes–Mueller basis to allow use of known phenomenology for data interpretation and processing as well as instrument calibration and troubleshooting. This approach to partial Mueller-matrix polarimeter (pMMP) design begins by defining a vector space of reduced Mueller matrices and an instrument vector representing the polarization modulators and other components of the sensor. The reduced-Mueller vector space is proven to be identical to ${\mathbb{R}}^{15}$ and to provide a completely linear description constrained to the Mueller cone. The reduced irradiance, the inner product of the reduced instrument and target vectors, is then applied to construct classifiers and tune modulator parameters, for instance to maximize representation of a specific target in a fixed number of measured channels. This design method eliminates the use of pseudo-inverses and reveals the optimal channel compositions to capture a particular signature feature, or a limited set of features, under given hardware constraints. Examples are given for common optical division-of-amplitude (DoA) 2-channel passive and serial/DoT-DoA 4-channel active polarimeters with rotating crystal modulators for classification of targets with diattenuation and depolarization characteristics. Full article

The Nile, Indus, and Yellow River deltas are historically significant and have experienced extensive shoreline changes over the past 50 years, yet the roles of human interventions and natural events remain unclear. In this study, the Net Shoreline Movement and End Point Rate (EPR) were calculated to quantify the erosion and accretion of the shoreline, respectively. Subsequently, linear trend analysis was employed to identify potential directional shifts in shoreline behavior. These measures are combined with segment-scale cumulative area and the EPR trend to reveal where erosion or accretion intensifies, weakens, or reverses through time. Results show distinct, system-specific trajectories, the Nile lost ~27 km² from 1972 to1997 as a result of the dam construction and sediment reduction, and lost only ~3 km² more from 1997 to 2022, with local stabilization. The Indus switched from intermittent gains before 1990s to sustained loss after that, totaling ~300 km² of cumulative land loss mainly due to upstream dam constructions and storm events. The Yellow River gained ~500 km² from 1973 to 1996 then lost ~200 km² after main-channel relocation and reduced sediment supply despite active-mouth management. These outcomes indicate that deltas are very vulnerable to system wide human activities and natural events. Combined, satellite-derived metrics can help prioritize locations, guide feasible interventions, establish annual monitoring and trigger action. A major caveat of this study is that yearly shoreline rates and 5–10-yearaverages can mask short-lived or very local shifts. Targeted field surveys and finer-scale modeling (hydrodynamics, subsidence monitoring, bathymetry) are therefore needed to refine the design and inform better policy choices. Full article

To address the challenge that MOSFET temperature in motor controllers is influenced by multiple factors, exhibits strong temporal dependence, and involves complex feature interactions, this study proposes a temperature prediction model that integrates Temporal Convolutional Networks (TCNs) and the Informer architecture in parallel, enhanced with a cross-attention mechanism. The model leverages TCNs to capture local temporal patterns, while the Informer extracts long-range dependencies, and cross-attention strengthens feature interactions across channels to improve predictive accuracy. A dataset was constructed based on measured MOSFET temperatures under various operating conditions, with input features including voltage, load current, switching frequency, and multiple ambient temperatures. Experimental evaluation shows that the proposed method achieves a mean absolute error of 0.2521 °C, a root mean square error of 0.3641 °C, and an R² of 0.9638 on the test set, outperforming benchmark models such as Times-Net, Informer, and LSTM. These results demonstrate the effectiveness of the proposed approach in reducing prediction errors and enhancing generalization, providing a reliable tool for real-time thermal monitoring of motor controllers. Full article