Search Results (1,020)

[Introduction] Climate change is a serious global challenge that is currently being faced and could intensify in the future. The resulting climate risks will have varying degrees of impact on sustainable agricultural development. To cope with climate change and achieve sustainable agricultural development, there is an urgent need to enhance agricultural resilience. [Methods] This paper employs fixed effects modeling to explore the impacts of climate change on agricultural resilience (production, economy, society, and ecology) using China’s regional data and examines the moderating roles of digital finance and agricultural infrastructure in the relationship between the two. [Results] The findings indicate the following: first, climate change has a negative impact on agricultural resilience, which constrains sustainable agriculture; second, both digital finance and agricultural infrastructure can mitigate the adverse effects of climate change on agricultural resilience; and third, the heterogeneity analysis further reveals that agricultural resilience in grain functional areas and regions with low levels of agricultural industrial integration is more significantly affected by climate change. [Discussion] Climate change threatens sustainable agriculture as the frequency of extreme climate events increases. Assessing the impact of climate change on agricultural resilience is of profound strategic significance for promoting sustainable agriculture, addressing climate risks, and ensuring food security. Policymakers should take adequate measures to strengthen agricultural resilience, including promoting digital finance in agriculture and increasing targeted infrastructure investments for vulnerable areas. Full article

Ultrafiltration strips water of bacteria. The common misconception is that the filtrate is thus free of bacteria. This only applies, however, in the case that the filtrate compartment is sterile. In real-world applications, the filtrate is rapidly re-colonized, followed by regrowth. In extreme cases of low water usage, the cell numbers in the filtrate can even exceed those in the feed water, probably due to a combination of the microbial enrichment of the bulk water from surfaces, regrowth in the water body itself, and nutrient enrichment on the filter membrane. Regrowth is made possible because dissolved nutrients can freely pass through the membranes. This explains why the initial decrease in cell numbers in drinking water installation systems with ultrafiltration is often followed by an increase in the periphery of the plumbing system. The extent of actual regrowth hereby depends mostly on water usage behaviours. A shorter frequency of membrane wash cycles is beneficial for reducing cell numbers. Neither frequent wash cycles nor cleaning in place (CIP) in filtration units, however, seem to modulate the maximal regrowth potential. Although the effect of ultrafiltration on cell numbers is not sustainable, it causes profound changes in the bacterial communities, with highly distinct populations in the feed water and the filtrate. The microbiological “reset” is demonstrated using examples both from the fields of drinking water and water reuse. Overall, our results suggest that ultrafiltration has a profound impact on the microbiome, but the cell numbers in filtrates depend mostly on the water usage and operational conditions. Full article

To address the challenge of monitoring BeiDou RDSS signals under low signal-to-noise ratio (SNR) and high-dynamic conditions, this paper introduces a hierarchical joint processing algorithm combining PMF-FFT and PMF-FRFT. The method counters the energy dispersion issue in conventional FFT-based techniques by employing a two-stage “coarse–fine” strategy. A computationally efficient PMF-FFT performs a rapid coarse search, followed by an intelligent trigger, based on a correlation peak morphology, that initiates a localized PMF-FRFT fine search for high-dynamic signals, to precisely estimate the code phase, center frequency, and Doppler rate. Experimental results demonstrated that the algorithm’s acquisition performance was comparable to a global PMF-FRFT search and superior to the conventional PMF-FFT, achieving a 4.91% correlation peak improvement at −10 dB SNR and a gain of nearly 30% in extreme conditions (−20 dB SNR, 1000 Hz offset). Crucially, its average processing time (∼0.088 s) was on the same order of magnitude as PMF-FFT (∼0.0568 s) and significantly faster than global PMF-FRFT (∼0.3317 s). The proposed algorithm effectively balances detection performance with computational efficiency, offering a viable solution for the real-time monitoring of high-dynamic DSSS signals. Full article

The Poincaré plot was introduced as a tool to analyze heart rate variations caused by arrhythmias. Later, it was applied to time series with normal beats. The plot shows the relationship between the inter-beat interval (IBI) of one beat to the next. Several parameters were developed to characterize this relationship. The short and long axis of the fitting ellipse, SD1 and SD2, respectively, their ratio, and their product are used. The difference between the IBI of a beat and m beats later are also studied, SD1(m) and SD2(m). We studied the mathematical relations between heart rate variability measures and the Poincaré measures in the time (standard deviation of IBI, SDNN, root mean square of successive differences, RMSSD) and frequency domain (power in low and high frequency band, and their ratio). We concluded that SD1 and SD2 do not provide new information compared to SDNN and RMSSD. Only the correlation coefficient r(m) provides new information for m > 1. Novel findings are that ln(SD2(m)/SD1(m)) = tanh⁻¹(r(m)), which is an approximately normal distributed transformation of r(m), and that SD1(m) and SD2(m) can be calculated by multiplying the power spectrum by a weighing function that depends on m, revealing the relationship with spectral measures, but also the relationship between SD1(m) and SD2(m). Both lagged parameters are extremely difficult to interpret compared to low and high frequency power, which are more closely related to the functioning of the autonomic nervous system. Full article

Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics and regional differentiation of GPP responses to the synergistic effects of meteorological drought (MD) and soil moisture drought (SD), particularly in the drought-sensitive Mongolian Plateau. This study focuses on the Mongolian Plateau from 1982 to 2021, using the standardized precipitation index (SPI) and standardized soil moisture index (SSI) to characterize MD and SD, respectively. The study combines the three-threshold run theory, cross-wavelet analysis, Spearman correlation analysis, and copula models to systematically investigate the variation characteristics, propagation patterns, and the probability and thresholds for triggering GPP loss under different time scales (monthly, seasonal, semi-annual, and annual). The results show that (1) both types of droughts exhibited significant intensification trends, with SD intensifying at a faster rate (annual scale SSI12 trend: −0.34/10a). The intensification trend strengthened with increasing time scales. MD exhibited high frequency, short duration, and low intensity, while SD showed the opposite characteristics. The most significant aridification occurred in the central region. (2) The average propagation time from MD to SD was 11.22 months. The average response time of GPP to MD was 10.46 months, while the response time to SD was significantly shorter (approximately 2 months on average); the correlation between SSI and GPP was significantly higher than that between SPI and GPP. (3) The conditional probability of triggering mild GPP loss (e.g., <40^th percentile) was relatively high for both drought types, and the probability of loss increased as the time scales extended. Compared to MD, SD was more likely to induce severe GPP loss. Additionally, the drought intensity threshold for triggering mild loss was lower (i.e., mild drought could trigger it), while higher drought intensity was required to trigger severe and extreme losses. Therefore, this study provides practical guidance for regional drought early-warning systems and ecosystem adaptive management, while laying an important theoretical foundation for a deeper understanding of drought response mechanisms. Full article

Infrared-visible image fusion quality is critical for nighttime perception in autonomous driving and surveillance but suffers severe degradation under extreme low-light conditions, including irreversible texture loss in visible images, thermal boundary diffusion artifacts, and overexposure under dynamic non-uniform illumination. To address these challenges, a Decomposition–Disentanglement–Dynamic Compensation framework, D3Fusion, is proposed. Firstly, a Retinex-inspired Decomposition Illumination Net (DIN) decomposes inputs into enhanced images and degradative illumination maps for joint low-light recovery. Secondly, an illumination-guided encoder and a multi-scale differential compensation decoder dynamically balance cross-modal features. Finally, a progressive three-stage training paradigm from illumination correction through feature disentanglement to adaptive fusion resolves optimization conflicts. Compared to State-of-the-Art methods, on the LLVIP, TNO, MSRS, and RoadScene datasets, D3Fusion achieves an average improvement of 1.59% in standard deviation (SD), 6.9% in spatial frequency (SF), 2.59% in edge intensity (EI), and 1.99% in visual information fidelity (VIF), demonstrating superior performance in extreme low-light scenarios. The framework effectively suppresses thermal diffusion artifacts while mitigating exposure imbalance, adaptively brightening scenes while preserving texture details in shadowed regions. This significantly improves fusion quality for nighttime images by enhancing salient information, establishing a robust solution for multimodal perception under illumination-critical conditions. Full article

This paper presents the novel design of a printed, low-cost, dual-port, and dual-polarized slot antenna for microwave biomedical radars. The butterfly shape of the radiating element, with orthogonally positioned arms, enables simultaneous radiation of both vertically and horizontally polarized waves. The antenna is intended for full-duplex in-band applications using two mutually isolated antenna ports, with the CPW port on the same side of the substrate as the slot antenna and the microstrip port positioned orthogonally on the other side of the substrate. Those two ports can be used as transmit and receive ports in a radar transceiver, with a port isolation of 25 dB. Thanks to the bow-tie shape of the slots and an additional coupling region between the butterfly arms, there is more flexibility in simultaneous optimization of the resonant frequency and input impedance at both ports, avoiding the need for a complicated matching network that introduces the attenuation and increases antenna dimensions. The advantage of this design is demonstrated through the modeling of an eight-element dual-port linear array with an extremely simple feed network for high-gain biosensing applications. To validate the simulation results, prototypes of the proposed antenna were fabricated and tested. The measured operating band of the antennas spans from 2.35 GHz to 2.55 GHz, with reflection coefficients of less than—10 dB, a maximum gain of 8.5 dBi, and a front-to-back gain ratio that is greater than 15 dB, which is comparable with other published single dual-port slot antennas. This is the simplest proposed dual-port, dual-polarization antenna that enables straightforward scaling to other frequency bands. Full article

Rapid urbanization and climate change have intensified urban flood risks, necessitating resilient upstream infrastructure to ensure metropolitan water security and effective flood mitigation. Gravity dams, as critical components of urban flood protection systems, regulate discharge to downstream urban areas. Gravity dams are critical for regulating flood discharge, yet their seismic vulnerability poses significant challenges, particularly under compound effects involving concurrent seismic loading and climate-induced elevated reservoir levels. This study introduces a novel seismic analysis framework for gravity dams using the scaled boundary finite element method (SBFEM), which efficiently models dam–water and dam–foundation interactions in infinite domains. A two-dimensional numerical model of a concrete gravity dam, subjected to realistic seismic loading, was developed and validated against analytical solutions and conventional finite element method (FEM) results, achieving discrepancies as low as 0.95% for static displacements and 0.21% for natural frequencies. The SBFEM approach accurately captures hydrodynamic pressures and radiation damping, revealing peak pressures at the dam heel during resonance and demonstrating computational efficiency with significantly reduced nodal requirements compared to FEM. These findings enhance understanding of dam behavior under extreme loading. The proposed framework supports climate-adaptive design standards and integrated hydrological–structural modeling. By addressing the seismic safety of flood-control dams, this research contributes to the development of resilient urban water management systems capable of protecting metropolitan areas from compound climatic and seismic extremes. Full article

Climate change has magnified health disparities across the Southern African Development Community (SADC) region by destabilizing the critical natural systems, which include water security, food production, and disease ecology. The IPCC (2007) underscores the disproportionate impact on low-income populations characterized by limited adaptive capacity, exacerbating existing vulnerabilities. Rising temperatures, erratic precipitation patterns, and increased frequency of extreme weather events ranging from prolonged droughts to catastrophic floods have created favourable conditions for the spread of waterborne diseases such as cholera, dysentery, and typhoid, as well as the expansion of vector-borne diseases zone also characterized by warmer and wetter conditions where diseases like malaria thrives. This study employed a comparative analysis of climate and health data across Malawi, Zimbabwe, Mozambique, and South Africa examining the interplay between climatic shifts and disease patterns. Through reviews of national surveillance reports, adaptation policies, and outbreak records, the analysis reveals the existence of critical gaps in preparedness and response. Zimbabwe’s Matabeleland region experienced a doubling of diarrheal diseases in 2019 due to drought-driven water shortages, forcing communities to rely on unsafe alternatives. Mozambique faced a similar crisis following Cyclone Idai in 2019, where floodwaters precipitated a threefold surge in cholera cases, predominantly affecting children under five. In Malawi, Cyclone Ana’s catastrophic flooding in 2022 contaminated water sources, leading to a devastating cholera outbreak that claimed over 1200 lives. Meanwhile, in South Africa, inadequate sanitation in KwaZulu-Natal’s informal settlements amplified cholera transmission during the 2023 rainy season. Malaria incidence has also risen in these regions, with warmer temperatures extending the geographic range of Anopheles mosquitoes and lengthening the transmission seasons. The findings underscore an urgent need for integrated, multisectoral interventions. Strengthening disease surveillance systems to incorporate climate data could enhance early warning capabilities, while national adaptation plans must prioritize health resilience by bridging gaps between water, agriculture, and infrastructure policies. Community-level interventions, such as water purification programs and targeted vector control, are essential to reduce outbreaks in high-risk areas. Beyond these findings, there is a critical need to invest in longitudinal research so as to elucidate the causal pathways between climate change and disease burden, particularly for understudied linkages like malaria expansion and urbanization. Without coordinated action, climate-related health inequalities will continue to widen, leaving marginalized populations increasingly vulnerable to preventable diseases. The SADC region must adopt evidence-based, equity-centred strategies to mitigate these growing threats and safeguard public health in a warming world. Full article

This study presents a comprehensive evaluation and selection framework for extremely low-frequency electromagnetic field (ELF-EMF) measurement instruments. Recognizing the diversity of application environments and technical constraints, the framework addresses the challenges of selecting appropriate tools for specific scenarios. It integrates a structured, quantitative approach through a weighted scoring matrix that evaluates instrumentation across six criteria: monitoring duration, sensitivity, environmental adaptability, biological/regulatory relevance, usability, and cost. Complementing this is a logic-based flowchart that visually guides decision-making based on user-defined operational needs. The framework is applied to a realistic occupational case study, demonstrating its effectiveness in producing evidence-based, scenario-sensitive instrument recommendations. This method provides stakeholders with a transparent and adaptable tool for ELF-EMF device selection. Full article

Copper alloys are critical heat sink materials for fusion reactor divertors due to their high thermal conductivity (TC) and strength, yet their performance under extreme particle bombardment and heat fluxes in future tokamaks requires enhancement. While neutron-induced transmutation helium affects the properties of copper, the atomistic mechanisms linking helium bubble size to thermal transport remain unclear. This study employs non-equilibrium molecular dynamics (NEMD) simulations to isolate the effect of bubble diameter (10, 20, 30, 40 Å) on TC in copper, maintaining a constant He-to-vacancy ratio of 2.5. Results demonstrate that larger bubbles significantly impair TC. This reduction correlates with increased Kapitza thermal resistance and pronounced lattice distortion from outward helium diffusion, intensifying phonon scattering. Phonon density of states (PDOS) analysis reveals diminished low-frequency peaks and an elevated high-frequency peak for bubbles >30 Å, confirming phonon confinement and localized vibrational modes. The PDOS overlap factor decreases with bubble size, directly linking microstructural evolution to thermal resistance. These findings elucidate the size-dependent mechanisms of helium bubble impacts on thermal transport in copper divertor materials. Full article

This paper presents a comprehensive statistical analysis of extremely/very low-frequency (ELF/VLF) whistler-mode waves observed within magnetic ducts (B-ducts) using data from NASA’s Magnetospheric Multiscale (MMS) mission. A total of 687 events were analyzed, comprising 504 occurrences on the dawn-side flank of the magnetosphere and 183 in the nightside magnetotail, to investigate the spatial distribution and underlying mechanisms of wave–particle interactions. We identify distinct differences between these regions by examining key parameters such as event width, frequency, plasma density, and magnetic field extrema within B-ducts. Using an independent two-sample t-test, we assess the statistical significance of variations in these parameters between different observation periods. This study provides valuable insights into the magnetospheric conditions influencing B-duct formation and wave propagation, offering a framework for understanding ELF/VLF wave dynamics in Earth’s space environment. Full article

The safety of lithium-ion batteries during transportation is critically important. However, current standards exhibit limitations, as their environmental testing parameter thresholds fail to fully encompass actual transportation conditions. To enhance both safety and standard applicability, in this study, we focused on four representative environmental conditions: temperature, vibration, shock, and low atmospheric pressure. Field measurements were conducted across road, rail, and air transport modes using a self-developed data acquisition system based on the NearLink communication technology. The measured data were then compared with the threshold values defined in current international and national standards. The results reveal that certain measured values exceeded the upper limits prescribed by existing standards, indicating limitations in their applicability under extreme transport conditions. Based on these findings, we propose revised testing parameters that better reflect actual transport risks, including a temperature cycling range of 72 ± 2 °C (high) and −40 ± 2 °C (low), a shock acceleration limit of 50 gn, adjusted peak frequencies in the vibration PSD profile, and a minimum pressure threshold of 11.6 kPa. These results provide a scientific basis for optimising safety standards and improving the safety of lithium-ion battery transportation. Full article

While rainfall occurs for several reasons, climate change and urbanization influence its frequency and geographical disparities. Although recent research suggests that urbanization may lead to increased rainfall, insights into how urbanization can trigger rainfall remain limited. We selected the Dallas–Fort Worth (DFW) metroplex, which has minimal orographic and coastal influences, to analyze the urban impact on rainfall. DFW was divided into 256 equal grids (10 km × 10 km) and grouped into four clusters using K-means clustering based on the urbanization ratio. Using Multi-Sensor Precipitation Estimator data (with a spatial resolution of 4 km), we examined rainfall exceeding the 95th percentile (i.e., extreme rainfall) on low synoptic days to highlight localized effects. The urban heat island (UHI) effect was estimated based on the average temperature difference between the urban core and the other three non-urban clusters. Multiple rainfall events were monitored on an hourly basis. Potential linkages between urbanization, the UHI, extreme rainfall, wind speed, wind direction, convective inhibition, and convective available potential energy were evaluated. An intense UHI within the DFW area triggered a tornado, resulting in maximum rainfall in the urban core area under high wind speeds and a dominant wind direction. Our findings further clarify the role of urbanization in generating extreme rainfall events, which is essential for developing better policies for urban planning in response to intensifying extreme events due to climate change. Full article

Background: Manual wheelchair propulsion is often associated with pain in the upper extremities. Recording spatio-temporal parameters can optimize movement patterns and prevent injuries. This study compares a marker-based camera system with inertial measurement units to validate their use in wheelchair propulsion on a test stand. Methods: Spatio-temporal parameters of 27 manual wheelchair users propelling at three self-selected speeds (slow, normal, fast) were simultaneously recorded using a marker-based camera system and inertial measurement units, and subsequently compared between both systems. Results: A high correlation was observed among all spatio-temporal parameters (ρ > 0.992). The biases for the start time of hand contact with the pushrim (−0.02 ± 0.02 s), hand release from the pushrim (−0.02 ± 0.01 s), and push length (−0.45 ± 21.45 ms) were slightly overestimated, while recovery length (0.54 ± 21.02 ms), cycle speed (2.37 ± 2.67°/s), and push angle (1.75 ± 4.14°) were slightly underestimated. No bias was found for propulsion frequency. Conclusions: The spatio-temporal parameters recorded using inertial measurement units are suitable for the evaluation of manual wheelchair propulsion and can be used in a clinical context. The low acquisition costs and simple installation process may increase the use of inertial measurement units in the future. Full article