Search Results (267)

Restoring the degraded habitat of the giant panda (Ailuropoda melanoleuca) is of paramount importance for the conservation of the species and its forest ecosystem. However, little is known about the impact of ecological restoration interventions on the growth renewal and nutritional quality of Arundinaria faberi in the degraded habitat of the giant panda. Here, we implemented strip thinning and blocky thinning techniques in the Daxiangling mountain range, alongside a control group. A random forest model and multiple linear regression analysis were employed to predict changes in the growth renewal and nutritional quality of bamboo, particularly in the strip-thinned zones. The key findings were as follows: (1) Compared with the control area, strip thinning increased the number of shoots and increased the diameter and height of shoots. (2) The random forest model predicted a decline in bamboo regeneration indices in 2023 compared to 2022 under strip thinning. (3) Through thinning, the palatability and nutritional level of A. faberi were improved. (4) Long-term effects included increased tannin in leaves, decreased tannin and amino acids in shoots and culms, and increased crude fat, with changes in crude protein distribution across bamboo parts. Overall, these findings provide valuable insights for habitat restoration efforts targeting giant panda populations in the low-canopy forest ecosystems of the Daxiangling mountain range. Full article

A core dielectric cylindrical rod wrapped in a dielectric circular pipe whose outer surface is enclosed by a helical conducting strip grating that is skewed along the axial direction is herein analyzed using the asymptotic strip boundary conditions along with classical vector potential analysis. Targeted for use as a cylindrical holographic antenna, the resultant field solutions facilitate the aperture integration of the equivalent cylindrical surface currents to obtain the radiated far fields. As each rod section of a certain skew angle exhibits a distinct modal attribute; this topology allows for the distribution of the cylindrical surface impedance via the effective refractive index to be modulated, as in gradient-index (GRIN) materials. Beam steering can also be achieved by altering the skew angle via mechanical sliding motion while leaving the cylindrical structure itself unchanged, as opposed to impractically reconfiguring the geometrical and material parameters of the latter to attain each new beam direction. The results computed by the program code based on the proposed technique in terms of the modal dispersion and radiation patterns are compared with simulations by a software solver. Manufactured prototypes are measured, and experimentally acquired dispersion diagrams and radiation patterns are favorably compared with theoretical predictions. Full article

Anaplasma marginale and Babesia bigemina are tick-borne pathogens, posing significant threats to the health and productivity of cattle in tropical and subtropical regions worldwide. Currently, detection of Babesia bigemina and Anaplasma marginale in infected animals relies primarily on microscopic examination of Giemsa-stained blood or organ smears, which has limited sensitivity. Molecular methods offer higher sensitivity but are costly and impractical in resource-limited settings. Following the development of a pen-side test for detecting Theileria parva infections in cattle, we have created two additional CRISPR-Cas12a assays targeting Anaplasma marginale and Babesia bigemina. The assays target the major surface protein 5 (MSP5) for A. marginale and rhoptry-associated protein 1a (RAP1a) for B. bigemina. These additional tests involve a 20 min recombinase polymerase amplification (RPA) reaction followed by a 60 min CRISPR-Cas12a detection with a lateral strip readout. Results demonstrate high specificity, with no cross-reactivity against other tick-borne parasites, and a limit of detection down to 10² DNA copies/µL of each target marker. The findings pave the way for sensitive and user-friendly pen-side tests to diagnose A. marginale and B. bigemina infections. Full article

Dullness or lack of radiance in facial appearance is a common concern among females. Previous studies have linked skin dullness to aging and revealed alterations in skin pigments. However, younger individuals (ages ≤ 35) also report concerns about dull skin in their hectic daily lives, which may not involve pigmentation changes. We hypothesized that the mechanisms underlying dullness in youth differ from those associated with aging. To investigate this, we measured cellular and molecular changes in 132 healthy Japanese and Chinese females aged 18 to 35 using biophotonic multiphoton tomography and biochemical tape-strip analysis. Our findings revealed that dull skin exhibited a thicker stratum granulosum and less densely packed keratinocytes in deeper layers. Biochemical analysis showed upregulation of interleukin-36γ and downregulation of E-cadherin in dull skin, with interleukin-36γ levels negatively correlating (p = 0.023) with metabolites of filaggrin. These alterations resemble those observed in inflammatory skin conditions, suggesting an additional mechanism of skin dullness beyond pigmentation. In vitro cultured cell models evaluated the efficacy of three skincare ingredients: galactomyces fermentation filtrate, bisabolol, and batyl alcohol. Galactomyces suppressed interleukin-36γ (p = 0.037), while both batyl alcohol (p = 0.006) and bisabolol (p = 0.049) showed beneficial effects on filaggrin. Targeting these biomarkers may improve the appearance of dull skin. Full article

Local heating of the activity area for nursing piglets is crucial for piglet health and the energy efficiency of barn climate control. Traditional heating methods using lamps or covers lack precise control, result in significant energy waste, and cannot be dynamically adjusted according to piglet age or changing environmental temperatures. To address these issues, this study designed a Programmable Logic Controller (PLC)-based thermal insulation box for nursing piglets, utilizing a strip heater instead of the conventional round heating lamp. The design incorporates a movable thermal insulation box that dynamically adjusts the heater’s power based on the real-time monitoring of environmental temperatures and target temperatures specific to piglet age. First, in a controlled laboratory environment, the study tested and compared the spatial temperature uniformity, temporal stability, and power consumption of the new thermal insulation box versus traditional heating methods. Subsequently, animal trials were conducted in a farrowing barn using eight sows with similar farrowing dates as test subjects. The new thermal insulation box was installed in one group, and the traditional heating lamp in the control group. During the trial, ambient temperature, insulation area temperature, piglet behavior, growth performance, and power consumption were recorded. The results showed that compared to the control group, the new system reduced average temperature fluctuations in the insulation area by 31.6% and spatial temperature variation by 78.3%. During animal trials, the average temperatures directly under the heater for the new system versus the control in the insulation area were 39.7 ± 0.2 °C and 30.2 ± 1.4 °C in the first week, 40.9 ± 0.5 °C and 31.6 ± 0.7 °C in the second week, and 32.3 ± 1.5 °C and 28.6 ± 1.7 °C in the third week—significantly (p < 0.05) higher in the test group. The new system also reduced total energy consumption by 58.3%. The usage rate of the thermal insulation area by piglets in the test and control groups was 47.5 ± 5.3% and 42.1 ± 6.6%. The daily weight gain of piglets in the test group was 9.8% higher than that of the control group, also significantly (p < 0.05) higher. This intelligent thermal insulation box enables precise and dynamic temperature control, reducing heating energy consumption and supporting improved piglet health and welfare. Full article

Transportation pressure poses a serious threat to the health of live sheep and the quality of their meat. So, the edible Hu sheep was chosen as the research object for meat sheep. We constructed a systematic biosignal detecting, processing, and modeling method. The biosignal sensing was performed with wearable sensors (photoelectric sensor and infrared temperature measurement) for physiological dynamic sensing and continuous monitoring of the transport environment of meat sheep. Core waveform extraction and modern spectral estimation methods are used to determine and strip out the target signal waveform from it for the purpose of accurate sensing and the acquisition of key transport parameters. Subsequently, we built a qualitative stress assessment method based on external manifestations with reference to the Karolinska drowsiness scale to establish stage classification rules for monitoring data in the transportation environment of meat sheep. Finally, machine learning algorithms such as Gaussian Naive Bayes (GaussianNB), Passive-Aggressive Aggregative Classifier (PAC), Nearest Centroid (NC), K-Nearest Neighbor Classification (KNN), Random Forest (RF), Support Vector Classification (SVC), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGB) were established to predict the classification models of transportation stress in meat sheep. Their classification results were compared. The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. XGB has the best results. The accuracy of the assessment of the transport stress state of meat sheep after the optimization of three parameters was 100%, 90.91%, and 93.33%, and the classification accuracy of the overall model reached 94.92%. The final results achieved improve transport reliability, reduce transport risk, and solve the problems of inefficient meat sheep transport supervision and quality control. Full article

Agriculture has consistently improved to meet the needs of a growing global population; however, traditional monoculture farming, while highly productive, is facing challenges such as weed infestation and inefficient resource utilization. Herbicides effectively control weeds. However, their widespread use in weed management has the potential to contaminate soil and water, endangering the ecosystem by damaging non-target plant and animal species. Therefore, the main objective of this study was to evaluate the impact of different maize and soybean cropping systems on weed infestation and resource utilization. The experiment was a randomized complete block design with three replications consisting of three cropping systems: sole maize (SM), sole soybean (SS), and maize–soybean strip intercropping (MSI). In this study, the main difference between SM, SS, and MSI was the planting density, which was 60,000 (SM), 100,000 (SS), and 160,000 (maize–soybean in MSI). We observed that a higher total leaf area index in MSI resulted in increased soil cover, which reduced the solar radiations for weeds and suppressed the weed growth by 17% and 11% as compared to SS and SM, respectively. Whereas the radiation use efficiency for companion crops in MSI was increased by 39% and 42% compared to SS and SM, respectively. Moreover, the increased soil cover by total leaf area index in MSI also increased the efficiency of water use. Furthermore, our results indicated that reduced weed-crop competition increased the resource use in MSI, which resulted in increased crop yield and land equivalent ratio (LER 1.6). Eventually, this resulted in reduced inputs and increased land productivity. Therefore, we suggest that MSI should be adopted in resource-limiting conditions with higher weed infestation as it can simultaneously promote ecological balance and improve agricultural output, thereby reducing the environmental effects of traditional cropping systems. Full article

This study aimed to investigate the degradation of dry biopotential electrodes using the anodic stripping voltammetry (ASV) technique. The electrodes were based on Ti-Cu thin films deposited on different polymeric substrates (polyurethane, polylactic acid, and cellulose) by Direct Current (DC) magnetron sputtering. TiCu_0.34 thin films (chemical composition of 25.4 at.% Cu and 74.6 at.% Ti) were prepared by sputtering a composite Ti target. For comparison purposes, a Cu-pure thin film was prepared under the same conditions and used as a reference. Both films exhibited dense microstructures with differences in surface topography and crystalline structure. The degradation process involved immersing TiCu_0.34 and Cu-pure thin films in artificial sweat (prepared following the ISO standard 3160-2) for different durations (1 h, 4 h, 24 h, 168 h, and 240 h). ASV was the technique selected to quantify the amount of Cu(II) released by the electrodes immersed in the sweat solution. The optimal analysis conditions were set for 120 s and −1.0 V for time deposition and potential deposition, respectively, with a quantification limit of 0.050 ppm and a detection limit of 0.016 ppm. The results showed that TiCu_0.34 electrodes on polyurethane substrates were significantly more reliable over time compared to Cu-pure electrodes. After 240 h of immersion, the TiCu_0.34 electrodes released a maximum of 0.06 ppm Cu, while Cu-pure electrodes released 16 ppm. The results showed the significant impact of the substrate on the electrode’s longevity, with cellulose bases performing poorly. TiCu_0.34 thin films on cellulose released 1.15 µg/cm² of copper after 240 h, compared to 1.12 mg/cm² from Cu-pure films deposited on the same substrate. Optical microscopy revealed that electrodes based on polylactic acid substrates were more prone to corrosion over time, whereas TiCu thin-film metallic glass-like structures on PU substrates showed extended lifespan. This study underscored the importance of assessing the degradation of dry biopotential electrodes for e-health applications, contributing to developing more durable and reliable sensing devices. While the study simulated real-world conditions using artificial sweat, it did not involve in vivo measurements. Full article

Background/Objectives: Ivermectin gained widespread attention as the “miracle drug” during the coronavirus disease 2019 (COVID-19) pandemic. Its inclusion in the 21st World Health Organization (WHO) List of Essential Medicines is attributed to its targeted anti-helminthic response, high efficacy, cost-effectiveness and favorable safety profile. Since the late 2000s, this bio-inspired active pharmaceutical ingredient (API) gained renewed interest for its diverse therapeutic capabilities. However, producing ivermectin formulations does remain challenging due to its poor water solubility, resulting in low bioavailability after oral administration. Therefore, the transdermal drug delivery of ivermectin was considered to overcome these challenges, which are observed after oral administration. Methods: Ivermectin was incorporated in a nano-emulsion, nano-emulgel and a colloidal suspension as ivermectin-loaded nanoparticles. The nano-drug delivery vehicles were optimized, characterized and evaluated through in vitro membrane release studies, ex vivo skin diffusion studies and tape-stripping to determine whether ivermectin was successfully released from its vehicle and delivered transdermally and/or topically throughout the skin. This study concluded with cytotoxicity tests using the methyl thiazolyl tetrazolium (MTT) and neutral red (NR) assays on both human immortalized epidermal keratinocytes (HaCaT) and human immortalized dermal fibroblasts (BJ-5ta). Results: Ivermectin was successfully released from each vehicle, delivered transdermally and topically throughout the skin and demonstrated little to no cytotoxicity at concentrations that diffused through the skin. Conclusions: The type of nano-drug delivery vehicle used to incorporate ivermectin influences its delivery both topically and transdermally, highlighting the dynamic equilibrium between the vehicle, the API and the skin. Full article

Bovine leukemia virus (BLV) is the causative agent of enzootic bovine leukosis (EBL), which presents worldwide prevalence. BLV caused substantial economic loss in China around the 1980s; then, it could not be detected for some time, until recently. Due to its latent and chronic characteristics, the efficient and accurate detection of BLV is of utmost significance to the timely implementation of control measures. Therefore, this study harnessed the recombinase-aided amplification (RAA), clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 13a (Cas13a) technology, and lateral flow (LF) strips to develop an efficient method for detection of BLV. In this method, isothermal amplification of the targeted pol gene is performed at 37 °C with a detection threshold of 1 copy/µL, and the procedure is completed in 100 min. This assay demonstrated high selectivity for BLV, as indicated by the absence of a cross-reaction with six common bovine pathogens. Remarkably, 100 blood samples from dairy cows were tested in parallel with a conventional quantitative polymerase chain reaction (qPCR) and this method and the results showed 100% agreement. Furthermore, this method exhibited good repeatability. In conclusion, in this study, we established a sensitive and specific method for BLV detection, which shows promise for application in BLV surveillance. Full article

This research seeks to enhance the understanding of the multifaceted drivers of food and nutrition insecurity in emergency-affected countries within the Eastern Mediterranean region and investigate the dynamics of food and nutrition security in countries facing emerging emergencies. This is a descriptive aim to determine the key factors and challenges affecting food security and nutrition status in ten countries in the Eastern Mediterranean region (Afghanistan, Djibouti, Iraq, Lebanon, Pakistan, Palestine (Gaza Strip), Somalia, Sudan, Syria, and Yemen). The research reveals that all selected countries experienced severe levels of food insecurity, with many reaching Phase 3 or above according to the IPC classification. In 2020, Afghanistan and Yemen were particularly hard-hit, with food insecurity affecting 42% and 45% of their populations; in 2024 in Gaza and Sudan, the same figures were 93% and 54% of the population, respectively, representing worse food insecurity crises in the region. Somalia, Sudan, and Djibouti also faced significant food insecurity rates. Many key drivers of food security are standard in most countries, and the linkage between food insecurity and malnutrition levels has a similar trend in almost all countries. However, none of the countries achieved all the 2025 global nutrition targets, while some reached one or two targets. Reaching sustainable development goals is still challenging in these countries since nutrition and food security levels, included in many goals, have not yet been reached. Food security and malnutrition in emergency-affected countries are driven by conflict, political instability, natural disasters, and socioeconomic conditions, which disrupt agricultural activities and infrastructure, exacerbating these challenges. To address these issues, we recommend a multisectoral approach, conflict resolution, climate-smart agriculture, integration of emergency responses with long-term strategies, and strengthening health and nutrition information systems. Full article

Assessing the spatially explicit life cycle environmental impacts of livestock production systems is critical for understanding the spatial heterogeneity of environmental releases and devising spatially targeted remediation strategies. This study presents the first spatially explicit assessment on life cycle global warming and eutrophication potentials of confined dairy production at a county scale in the contiguous US. The Environmental Policy Integrated Climate model was used to estimate greenhouse gases (GHGs), NH₃, and aqueous nutrient releases of feed production. The Greenhouse gases, Regulated Emissions, and Energy use in Transportation model and Commodity Flow Survey were used to assess GHGs and NH₃ from feed transportation. Emission-factor-based approaches were primarily used to calculate GHGs from enteric fermentation, and GHGs, NH₃, and aqueous nutrient releases from manure management. Characterization factors reported by the Intergovernmental Panel on Climate Change and Tool for Reduction and Assessment of Chemicals and other Environmental Impacts model were used to compute global warming and eutrophication potentials, respectively. The analyses revealed that life cycle global warming and eutrophication potentials of confined dairy production presented significant spatial heterogeneity among the US counties. For example, the life cycle global warming potential ranged from 462 kg CO₂-eq/head to 14,189 kg CO₂-eq/head. Surprisingly, sourcing feed locally cannot effectively reduce life cycle global warming and eutrophication potentials of confined dairy production. The feed supply scenarios with the lowest life cycle environmental impacts depend on the life cycle environmental impacts of feed production, geographic locations of confined dairy production, and specific impact categories. In addition, installing buffer strips in feed-producing hotspots can effectively reduce life cycle nutrient releases of confined dairy production. If 200 counties with the highest life cycle EP of corn adopt buffer strips, the reduction in life cycle EP of confined dairy production could reach 24.4%. Full article

Wind turbine blades (WTBs) are prone to damage from their working environment, including surface peeling and cracks. Early and effective detection of surface defects on WTBs can avoid complex and costly repairs and serious safety hazards. Traditional object detection methods have disadvantages of insufficient detection capabilities, extended model inference times, low recognition accuracy for small objects, and elongated strip defects within WTB datasets. In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. Firstly, Dynamic Separable Convolution (DSConv) is introduced into the C2f module of YOLOv8, allowing the model to more effectively focus on the geometric structural details associated with damage on WTBs. Secondly, the upsampling method is replaced with the content-aware reassembly of features (CARAFE), which significantly minimizes the degradation of image characteristics throughout the upsampling process and boosts the network’s ability to extract features. Finally, the loss function is substituted with the WIoU (Wise-IoU) strategy. This strategy allows for a more accurate regression of the target bounding boxes and helps to improve the reliability in the localization of WTBs damages, especially for low-quality examples. This model demonstrates a notable superiority in surface damage detection of WTBs compared to the original YOLOv8n and has achieved a substantial improvement in the [email protected] metric, rising from 91.4% to 93.8%. Furthermore, in the more rigorous [email protected]–0.95 metric, it has also seen an increase from 68.9% to 71.2%. Full article

Microsatellites have significantly impacted space missions by offering advanced technology at a low cost. This study introduces an attitude determination and control algorithm for agile whiskbroom scanning maneuvers in microsatellites to enable wide-swath target detection for low-Earth-orbit microsatellites. First, an angular velocity calculation model for agile whiskbroom scanning is established. A methodology has been developed to calculate the maximum available time for whiskbroom scanning from one side of the sub-satellite point to the other while ensuring the seamless joining of adjacent strips to avoid missing targets. Thereafter, a gyro- and magnetometer-based cubature Kalman filter is put forward for microsatellite attitude estimation. Furthermore, for attitude control, a hybrid manipulation law capable of preventing singularities and escaping singularity surfaces is designed to ensure high-precision torque output from the control moment gyroscopes (CMGs) used as actuators. The benefits of the linear sliding mode and fast terminal sliding mode are integrated, and a non-singular sliding surface is designed, yielding a non-singular fast terminal sliding mode attitude control algorithm for tracking the desired trajectory. This algorithm effectively suppresses chattering and enhances dynamic performance without using a switching term. A semi-physical simulation experiment system is also conducted on the ground to validate the proposed algorithm’s high-precision tracking of the planned whiskbroom scanning path. The experimental results demonstrate an attitude angle control accuracy of 4 × 10⁻² degrees and angular velocity control accuracy of 0.01°/s and thus the effectiveness of the proposed algorithm. Full article

Strip steel serves as a crucial raw material in numerous industries, including aircraft and automobile manufacturing. Surface defects in strip steel can degrade the performance, quality, and appearance of industrial steel products. Detecting surface defects in steel strip products is challenging due to the low contrast between defects and background, small defect targets, as well as significant variations in defect sizes. To address these challenges, a two-stage attention-based feature-enhancement network (TAFENet) is proposed, wherein the first-stage feature-enhancement procedure utilizes an attentional convolutional fusion module with convolution to combine all four-level features and then strengthens the features of different levels via a residual spatial-channel attention connection module (RSC). The second-stage feature-enhancement procedure combines three-level features using an attentional self-attention fusion module and then strengthens the features using a RSC attention module. Experiments on the NEU-DET and GC10-DET datasets demonstrated that the proposed method significantly improved detection accuracy, thereby confirming the effectiveness and generalization capability of the proposed method. Full article