Physical Parameters Research Articles

Accurate Conversion of Land Surface Reflectance for Drone-Based Multispectral Remote Sensing Images Using a Solar Radiation Component Separation Approach

Land surface reflectance is a basic physical parameter in many quantitative remote sensing models. However, the existing reflectance conversion techniques for drone-based (or UAV-based) remote sensing need further improvement and optimization due to either cumbersome operational procedures or inaccurate results. To tackle this problem, this study proposes a novel method to mathematically implement the separation of direct and scattering radiation using a self-developed multi-angle light intensity device. The verification results from practical experiments demonstrate that the proposed method has strong adaptability, as it can obtain accurate surface reflectance even under complicated conditions where both illumination intensity and component change simultaneously. Among the six selected typical land cover types (i.e., lake water, slab stone, shrub, green grass, red grass, and dry grass), green grass has the highest error among the five multispectral bands with a mean absolute error (MAE) of 1.59%. For all land cover types, the highest MAE of 1.01% is found in the red band. The above validation results indicate that the proposed land surface reflectance conversion method has considerably high accuracy. Therefore, the study results may provide valuable references for quantitative remote sensing applications of drone-based multispectral data, as well as the design of future multispectral drones.

Coenzyme Q10 microemulsion ion-activated gel: a promising ophthalmic delivery system for enhanced corneal protection and sustained release

PurposeThis study aimed to evaluate a novel microemulsion ion-activated gel system for the ophthalmic delivery of coenzyme Q10 (CoQ10).MethodsVarious CoQ10 microemulsion ion-activated formulations were prepared and fully assessed for physical and chemical parameters, assay and related substances, in vitro release, rheological properties, in vitro cytotoxicity and ophthalmic retention. A preliminary pharmacokinetic study was also performed in rabbits.ResultsThe formulations met the specified criteria, showing a droplet size of 24.5 ± 2.0 nm for microemulsions, increasing slightly to 39.6 ± 3.5 nm for the microemulsion gels. They exhibited a 24-hour sustained in vitro release (80.0% ± 3.2%) and increased viscosity upon contact with artificial tears containing Ca2+ and K+ ions. The no-film dissolution method and in vitro models indicated first-order release kinetics (r = 0.987). The preparations demonstrated good tolerance and non-irritating properties, with a Draize score of 0–0.55 in rabbits, and provided a 2-hour extension in drug retention on the ocular surface compared with microemulsions alone. In ultraviolet B (UVB)-exposed rats, corneal epithelial damage was reduced and antioxidant marker levels (superoxide dismutase, malondialdehyde) were significantly improved.ConclusionThis novel system is a promising preparation for ophthalmic CoQ10 delivery, offering sustained release and protection against UVB-induced corneal damage.

Optimization of thermostable amylolytic enzyme production from Bacillus cereus isolated from a recreational warm spring via Box Behnken design and response surface methodology

This study aimed to find a source for local amylase-producing microbes. Sixteen isolates were obtained from the water samples from the warm spring and characterized based on morphological and biochemical tests. The 16S rRNA molecular identification technique confirmed the most potent isolate as Bacillus cereus. The thermophilic property of the bacterium demonstrated that it could withstand temperatures of up to 80 °C. One-factor-at-a-time (OFAT) and Box Behnken Design (BBD) coupled with response surface methodology (RSM) optimization techniques were used to improve amylase production. OFAT established optimal physical parameter conditions as the starch concentration of 5% w/v, inoculum volume of 2% v/v, pH of 8, incubation temperature of 45 °C, and 48 h of incubation, leading to amylase activity of 172.6 U/mL by the isolated B. cereus. A quadratic mathematical model with a coefficient of determination (R2) of 0.9957 was established for the amylase production process. Enhanced amylase activity of 196.02 U/mL was achieved with BBD-RSM under optimal growth conditions of pH of 7, incubation time of 48 h, substrate concentration of 5% w/v of starch, and at 45 °C, a 1.2-fold increase compared to the OFAT method. The B. cereus strain isolated from the warm spring was a mildly thermophilic bacterium with the potential for synthesizing amylolytic enzymes with characteristics beneficial for commercial utilization.

Primary, superharmonic and subharmonic resonances control of an oscillatory cantilever beam excited transversely at its free end

The nonlinear vibrations of a cantilever beam model and the dynamic analysis of several resonances (primary and secondary) controlled by the proportional-derivative (PD) control are studied and discussed. The multiple time-scales method is applied to solve the dynamical system of the cantilever beam where the response curves before and after control are obtained. Through these curves, the stability of the beam’s oscillatory behavior is tested under the effect of different physical parameters. The beam suffers from high vibration amplitudes in each resonance case, especially in the superharmonic and subharmonic resonance cases. Besides the nontrivial amplitude of oscillation, a trivial one appears in some secondary resonance cases. Tuning the control gains can lead to acceptable vibration mitigation levels besides approaching the trivial amplitude in some resonance cases. Accordingly, the analytical and numerical results are compared before and after control to validate the control law.

Bipartite entanglement and Gaussian quantum steering in a whispering gallery mode coupled with two magnon modes

We theoretically propose a scheme to generate and control continuous variable bipartite entanglement and Gaussian quantum steering in an optical whispering gallery mode (WGM)-based cavity optomagnonical system that consists of two macroscopic YIG resonator. Owing to the well-known Faraday effect, both the magnon modes are coupled to single-mode optical WGM through nonlinear interaction. We investigate in detail the impact of several physical parameters such as effective cavity detuning, input laser power, environment temperature, optomagnonical coupling strengths and magnon decay rate on different bipartite entanglement. We also found a suitable parameter regime to obtain maximum cavity-magnon and magnon-magnon bipartite entanglement in our proposed system. It is interesting to note that the numerical simulation result shows that magnon-magnon entanglement persists up to 60K. With a proper choice of optomagnonical coupling strengths and normalized effective cavity detuning, we can effectively control the nature and strength of Gaussian quantum steering. In the WGM-based cavity optomagnonical system, our current work will offer a new way of greatly controlling a variety of nonclassical quantum correlations of macroscopic objects, which may find use in a number of contemporary quantum technology fields.

Physicochemical Properties and Molecular Insights of Favipiravir and Roflumilast Solid Dispersions for COVID-19 Treatment

Background/Objectives: Fixed-dose combinations (FDCs) offer significant advantages for patients and healthcare systems by improving adherence and reducing pill burden. However, developing multi-drug formulations remains challenging due to complexities in drug compatibility, stability, and dissolution behavior. The COVID-19 pandemic has necessitated innovative therapeutic approaches. This study aims to develop and evaluate an FDC containing FR (an antiviral drug) and RT (a PDE4 inhibitor) for potential COVID-19 treatment. Methods: The proposed dual-layer FDC was formulated to achieve immediate release of RT using Klucel EXF and controlled release of FR using a combination of Klucel HXF and Compritol ATO888. Critical quality attributes, including drug–excipient compatibility, solid-state properties, tablet uniformity, and dissolution kinetics, were assessed. RT and FR quantification methods were developed and validated per international guidelines. Compatibility studies were conducted by combining excipients in fixed ratios with APIs, followed by stability testing. Results: No degradation or adverse interactions were observed between APIs and excipients. RT exhibited rapid dissolution within 30 min, while FR release was effectively controlled through a gel-forming matrix and lipid barrier. Bulk powder and tablet physical parameters met pharmacopeial standards, and content uniformity between layers was maintained. The formulation demonstrated a stable dissolution profile for both drugs, ensuring consistent drug release. Conclusions: The novel FDC of RT and FR exhibits favorable physicochemical properties, a stable dissolution profile, and potential for improved treatment efficacy in COVID-19 patients. By optimizing drug release mechanisms and ensuring formulation stability, this FDC could serve as a pharmaco-economically viable alternative to existing therapies, enhancing patient compliance and treatment outcomes.

Comprehensive quality profiling and multivariate analysis of rice (Oryza sativa L.) cultivars: integrating physical, cooking, nutritional, and micronutrient characteristics for enhanced varietal selection

BackgroundRice (Oryza sativa L.) is a staple food for nearly half the global population, with rice grain quality (RGQ) and yield being the most valuable attributes for consumers and food security. RGQ encompasses multiple interconnected features including physical appearance, cooking properties, biochemical composition, nutritional components, and sensory aspects.MethodsThis study evaluated the agronomic performance of four commercial rice cultivars (Giza 178, Sakha 108, Sakha Super 300, and Egyptian Yasmin) during the 2022 and 2023 growing seasons. The experiment was conducted at the Rice Technology Training Center in Alexandria using a randomized complete block design with three replications. A cultivars were selected based on their commercial significance and diverse genetic backgrounds to represent the primary rice varieties grown in Egypt.ResultsAnalysis of variance revealed significant genotypic effects (p < 0.001) for most traits, with notable genotype × environment interactions in milling quality and water uptake characteristics. Multivariate analyses, including Principal Component Analysis (PCA), hierarchical clustering, and correlation analysis, provided complementary evidence for cultivar differentiation. PCA demonstrated that 94.2% of total variance was explained by two principal components, with Yasmin distinctly clustering in the positive quadrant of Dim1, showing superior performance in nutritional and cooking parameters (protein: 8.51%, fiber: 0.33%, water uptake: 439.45%, elongation: 60.73%). Hierarchical cluster analysis revealed two distinct trait groupings: physical-processing parameters and nutritional-functional attributes. Cultivar Super 300 demonstrated superior performance in physical-processing metrics (milling yield: 71.69%, grain hardness: 6.56), while Yasmin exhibited exceptional nutritional-functional characteristics. Furthermore, correlation analysis revealed significant relationships among quality parameters (p < 0.001), particularly between physical characteristics and milling traits (r = 0.99), and among nutritional components (r = 0.87–0.99).ConclusionThe integrated multivariate approach identified Yasmin as the superior cultivar for nutritional and cooking qualities, while Super 300 excelled in physical parameters, providing comprehensive insights for developing cultivars with optimized quality profiles tailored to specific market demands and consumer preferences.

Feasibility Study of Moving Bed Biofilm Reactor (MBBR) Technology at Guheshwori Wastewater Treatment Plant, Nepal

&lt;p&gt;Moving Bed Biofilm Reactor (MBBR) technology is applicable for removing organic components and nitrogen from wastewater in the Guheshwori Wastewater Treatment Plant (GWWTP). A lab-scale single-staged aerobic batch MBBR (16L pure volume, 5L active working volume) was designed and initiated using synthetic and municipal wastewater in two phases. Removal efficiencies of COD, BOD, NH4-N, and PO43- were investigated at various retention times (0-72h) for municipal wastewater treatment with and without media. Physical parameters (pH, DO, temperature, and conductivity) were monitored under ambient conditions. Both treatments demonstrated similar BOD removals (89.68% and 88.97%) at 72h, with the treatment using media exhibiting higher COD removal (96.84%). Ammonia-nitrogen removal was completed at 20h for the treatment without media and 99.20% at 24h for the treatment with media. Phosphate removal was significant (92.98%) at 24h for MBBR with media, whereas no notable phosphate removal was observed without media. MBBR is efficient in BOD, COD, ammonia-nitrogen, and phosphate removal from municipal wastewater, offering advantages over traditional activated sludge processes regarding tank size. The findings support the feasibility of implementing MBBR for wastewater treatment at GWWTP.&lt;/p&gt;

Correlational Analysis of Physical Activity Level with Agility, Speed and Foot Arch Configuration in SGT University Students

Background: Physical activity is essential for overall health, especially for university students, whose changing lifestyles can impact their fitness levels. Understanding the link between physical activity and fitness parameters, such as Arch of foot and biomechanical efficiency, is key for creating interventions that promote long-term well-being. This study explores how physical activity levels correlate with these key fitness components among university students.  Methods: A cross-sectional study was conducted with university students from various academic backgrounds. Participants were grouped based on their self-reported physical activity levels, assessed using validated tools. Fitness tests included the agility and speed test. Biomechanical parameter which was foot arch were also measured. Data were analyzed using statistical methods like Pearson correlation and regression analysis to explore relationships between physical activity, Agility and speed and the arch of foot.  Results: The study found a negative linear relationship between physical fitness and agility/speed, with a statistically significant correlation (p &lt; 0.05). This means that higher fitness levels led to quicker completion of the agility test, improving both speed and agility.  Conclusion: The results suggest that increasing physical activity levels can enhance agility and speed. This highlights the importance of regular physical activity for improving specific fitness attributes like agility and speed and improving the arch of foot.

Effects of neutral beam injection on tearing mode stability: insights from hybrid simulations

Abstract In tokamak plasmas, tangential neutral beam injection (NBI) produces (a large fraction of) circulating energetic ions (CEIs) and induces plasma toroidal rotation, both of which play an important role in the stability of tearing mode (TM). In this study, the effect of NBI on TM is systematically investigated using kinetic-magnetohydrodynamic hybrid code M3D-K. Here, the effect of NBI is modeled as the combined effects of CEI and toroidal rotation. The analysis focuses on the dependency of NBI's effect on key physical parameters, including magnetic shear, total beta and plasma shape. The modification of rotation on equilibrium is self-consistently included in simulation, which can enhance the destabilizing effect of counter-CEI on TM and has a negligible contribution to the effect of co-CEI. Furthermore, the simulation results reveal that the co-NBI always reduces TM's growth rate due to the dominant stabilizing effect of rotation and the weak net effect of co-CEI, agreeing well with most experimental results. Whether the counter-NBI stabilizes or destabilizes TM depends on the competition between the stabilizing contribution from rotation and the destabilizing contribution from counter-CEI. Specifically, the counter-NBI tends to stabilize TM when elongation and triangularity decrease, while magnetic shear, total beta and aspect ratio increase.

Creation field cosmological models with variable G and Λ in FRW spacetime

We discuss cosmological models based on creation field theory with the variable cosmological term ([Formula: see text]) and variable gravitational constant (G) in FRW spacetime. Our laws of variation are [Formula: see text] and [Formula: see text] where [Formula: see text], is a constant. The physical parameters for [Formula: see text], [Formula: see text] are discussed. The conservation laws are satisfied for both the models in C-field cosmology.

A study on the effects of effusion rate on 2D numerical simulations of lava flow evolution

The effusion rate plays a crucial role in controlling the evolution of volcanic eruptions and it is thus critical to quantify the associated volcanic hazards. It represents the volume of lava emitted over time and can be estimated using satellite remote sensing data, such as Volcanic Radiative Power (VRP) measurements, deriving the Time Averaged Discharge Rate (TADR). Variations in the effusion rate can influence the resulting eruption style, ranging from effusive or Strombolian to lava fountaining activity. Thanks to the abundance of free data collected through fieldwork and remote sensing, it is now possible to numerically simulate eruptive behaviors with Computational Fluid Dynamics (CFD) models, allowing for a detailed study of lava flow evolution in time and space, without the dangers of collecting field data. We have already largely simulated lava flows with a Lagrangian mesh‑free particle CFD method, known as Smoothed Particle Hydrodynamics (SPH). This model takes in input the physical parameters of the fluid and returns in output a numerical simulation of its spatio‑temporal evolution. Here, we propose a framework to simulate lava flows with a range of values for some physical parameter, to better understand their results on numerical simulations, bringing to a deeper knowledge of the different eruptive behaviors in function of these parameters. In particular, we conduct a study on the effusion rate effects over 2D numerical simulations of lava using numerical physical‑mathematical models that return as output not only the evolution of the flow front but also the behavior of the vertical flow section. Using the TADR derived from VRP data and the SPH method, we simulate the fluid flow under different effusion rate conditions. This sensitivity analysis demonstrates how varying effusion rates affect the evolution of the flow front and vertical cross‑section. In detail, we show how time‑independent and time‑dependent effusion rates, obtained by satellite data, can make possible to qualitatively analyze and reproduce different eruptive styles, as effusive, Strombolian, or explosive activity and variable flows. The results highlight the potential for integrating real observations with numerical models and lay the groundwork for future applications that combine these approaches with artificial intelligence to enhance the model performance.

A photonic crystal-hydrogel sensor for the monitoring of potassium ions in sweat.

Sweat contains abundant physiological information critical for health monitoring, making wearable sweat sensors increasingly popular in exercise and training surveillance. Most of the existing sensors are designed to measure physical parameters such as heart rate, blood pressure, and respiration, relying on electronic instruments for biochemical analysis of body fluids. In this study, we present a wearable hydrogel band integrated with a photonic crystal array, for visual, non-invasive and in situ analysis of sweat for sports practitioners. The hydrogel sensor, inspired by the biological properties of onions, demonstrates excellent skin adhesion for efficient sweat collection. This innovative design allows for the development of a simple, reliable, and low-cost sensor capable of detecting potassium ion concentrations and pH levels in sweat. Under optimized conditions, the developed sensor can respond to potassium ion concentrations ranging from 1 mM to 150 mM, with a pH response range of 3 to 9 for human sweat. The dynamic cycling tests of potassium ion concentration and pH in sweat demonstrated that this sensor can effectively monitor electrolyte balance and dehydration during outdoor exercise.

Photometric Monitoring of MCG–06-30-15

Abstract We describe photometric monitoring of the Seyfert 1 galaxy MCG–06-30-15 with the Las Cumbres Observatory network. Using the V filter, 496 images were collected between 2023 December and 2024 June from observatories in Chile, South Africa, and Australia. We created light curves of the active galactic nucleus continuum emission using aperture photometry and image subtraction methods. We find that the typical magnitude difference between the two light curves is ΔV ≈ 1.9 mag, indicating that the host galaxy contributes approximately 85% of the total flux through the photometric aperture. The amplitude of variation is significantly enhanced when the host galaxy is removed: ΔV = 0.1 mag from aperture photometry compared to ΔV = 0.5 mag with image subtraction. Future work will compare the continuum light curve with the broad emission-line flux variations to provide insight into the physical parameters of the broad-line region in MCG–06-30-15 and the mass of the central supermassive black hole.

Adverse health effects following exposure to engineered nanomaterials

Advances in nanotechnology have enabled fabrication of nanomaterials with defined structures that areincreasingly being used for commercial purposes. Unlike chemical toxins, nanomaterials have unique interactions with macromolecules and cells based on their molecular size and interfacial physiochemistry. Adverse human health impacts due to occupational and environmental exposures to engineered nanomaterials (ENMs) are therefore of concern. Although the impact of ENMs on biological systems is still not clearly understood, strong evidence suggests that nanomaterials are present in human fluids and tissues. Effective and feasible hazard assessment of ENMs is urgently needed to guide regulation and policy-making and support the development of benign next generation ENMs. Beyond the physical parameters of the NMs themselves, the surrounding biological system has been shown to influence NM behavior, the nano-cellular interface, and subsequent biological responses.It has recently been established that ENMs, upon entry into a physiological environment, exhibit a tendency of physical adsorption with proteins, peptides, lipids and amino acids to render a "biocorona" that may influence the bioavailability and distribution of ENMs within the host system, at the cellular, tissue and whole organism level. Consequently, research on the health and safety implications of ENMs must include assessments of how the biocorona may impact toxicity and lead to a new 'biological' identity of the ENM.Although ongoing research suggests that almost every organ and organ system may be affected by ENMs, in this review we will focus on the main pathogenetic mechanisms and on key organ and organ systems such as the lung, the skin and the gastro-intestinal tract; we will also highlight several challenges associated with a comprehensive evaluation of their toxicity, including the vast and diverse array of ENM products, dependence on physicochemical characteristics and exposure matrices, and difficulties in quantifying dosimetry and dose-response. Possible attempts to overcome these challenges are also discussed.

Digital twin system for manufacturing processes based on a multi-layer knowledge graph model

Digital twin technology in the manufacturing process faces challenges like integrating diverse data sources and managing real-time data flow. To address this, we propose a novel three-layer knowledge graph architecture to enhance digital twin modeling for manufacturing processes. This architecture consists of a concept layer that structures key information into a knowledge network, a model layer that aligns digital and physical parameters, and a decision layer that leverages model and real-time data for decision support. Validated in aero-engine blade production, this system integrates multi-source data, enhances predictive analysis and anomaly detection, and supports process control and quality management. Over a 5-month validation period, the maximum contour error precision of the blades improved from 0.073 mm to 0.062 mm, and the product qualification rate increased from 81.3% to 85.2%. This demonstrates the system’s robust capability for advancing digital twin utilization in manufacturing, highlighting its potential for future improvements.

Occurrence, partitioning behavior, and ecological risk assessment of octylphenol and nonylphenol in surface waters and sediments of Terengganu Rivers, Malaysia.

The occurrence, partitioning behavior, and ecological risk assessment of octylphenol (OP) and nonylphenol (NP) were investigated in the surface water and sediment of three rivers in Terengganu, Malaysia, to understand the fate and ecological risk of these chemicals in aquatic ecosystems. Target chemicals were extracted using solvent extractant and cleaned up via solid-phase extraction. This is followed by analysis via high-performance liquid chromatography (HPLC), and verification by liquid chromatography-tandem mass spectrometry (LC-MS/MS). OP was consistently higher in both surface water and sediment, while NP was predominantly found in sediment with minimal detection in surface water. Concentrations in sediment (OP, 0.19-30.88 ng/g dw; NP, 0.38-84.42 ng/g dw) and in surface water (OP, 0.0019-0.0077 ng/mL; NP, 0.0007-0.0023 ng/mL) suggest strong adsorption from water to sediment due to the hydrophobic effects of these compounds. The partitioning behavior of OP was evaluated using two indicators: (1) the sediment-water partition coefficient (Kd) and (2) the carbon-normalized partition coefficient (K'oc). The results indicated that OP is readily adsorbed and released from sediment, with log Kd values ranging from 3.06 to 3.57 and log K'oc values from 3.00 to 3.97. A significant positive correlation was observed between physical water parameters (temperature, salinity, and pH), whereas a significant negative correlation was found between these parameters and the concentrations of OP and NP in sediment. The ecological risk assessment showed that OP in water posed a low risk, while OP and NP in sediment presented varying risks, ranging from low to high risk between 2018 and 2019. This baseline information on the partitioning behavior is invaluable for predicting the environmental fate of these compounds in sediment-water interactions in Malaysia and for assessing the ecological risks they may pose to aquatic organisms.

Towards improved prescription metrics in novel radiotherapy techniques: a machine learning study

Objective.FLASH radiotherapy (RT), microbeam RT (MRT) and minibeam RT (MBRT) are novel RT techniques that have been shown to reduce normal tissue complication probabilities, by modulating the dose distributions through different parameters in space and time. This study aims to investigate the importance of these parameters for predicting biological outcomes using a machine learning (ML) approach and to compare the findings with previous correlation analyses in the context of the current understanding of these techniques.Approach.A ML algorithm was trained for predicting normal tissue toxicity, tumor control and increased lifespan (ILS) quantitative metrics on published datasets of preclinical MRT, MBRT and FLASH RT data. The influence of different variables on the performance of the model over unseen data was quantified, and their importance on its predictive power was ranked.Main results.An accuracy of 70% or superior was achieved for the prediction of most metrics, reduced for normal tissue toxicity to 60% in MBRT and 40% in FLASH RT. In MRT, valley dose was found as the most influencing physical parameter for normal tissue sparing, while in MBRT the peak dose was highlighted as one of the most influential parameters. Valley dose showed the greatest impact over ILS in a conjoint study of both techniques. In FLASH RT, the total dose, along with the tissue characteristics, were identified as the most influencing variables for tumor control and normal tissue toxicity. The importance of dose rate increased when considering therapeutic index.Significance.These results agree with previous studies that highlight how dose heterogeneity prevents normal tissue damage in MBRT and MRT and the need of prescribing under critical tissue specific valley and peak dose values respectively for optimal sparing and tumor control. The described findings are also consistent with FLASH RT tumor control being driven by the same mechanisms as in conventional RT.

Exploring Placental Protein-Target Protein Interactions: In Silico and In Vitro Approaches for Osteoarthritis Therapy.

Osteoarthritis (OA) is a persistent joint condition marked by gradual softening and breakdown of articular cartilage. Current research in OA treatment explores biologics that target proinflammatory cytokines and proteases, as well as promote chondrocyte regeneration and cartilage repair. Human placental tissues, abundant in anti-catabolic factors, can mitigate cartilage degradation by inhibiting protease expression and maintaining cartilage homeostasis in the presence of anabolic factors. This investigation examined placental protein interactions with proteases and OA target proteins through protein-protein docking and dynamic studies. The NCBI conserved domain database was utilized to predict functional protein domains. Protein sequence motifs were identified using literature, the MEME suite tool, and the My- Hits database. The Expasy-ProtParam online tool was employed to analyze protein physical parameters. ClusPro Advanced Options was used to dock binding site residues of selected placental proteins against specific OA target proteins, while PDBsum and Biovia Discovery Studio were used to visualize and examine molecular interactions. A 100 ns molecular dynamics (MD) study was conducted using DESMOND software. Protein-protein docking revealed strong interactions of placental proteins with docking scores ranging from -1700 to -2450.3 against proteases and -900 to -1400 against specific target proteins. PDBsum analysis of placental protein-target protein docked complexes revealed residue interactions, hydrogen bonds, and non-bonded contacts. Molecular dynamics simulations further confirmed the stability of these complexes, indicating favorable protein-protein interactions (PPIs). The anti-inflammatory activity of human placental tissue against lipopolysaccharide-induced macrophages was investigated using flow cytometry. These results provide a foundation for future experimental studies to confirm the predicted interactions and to explore their potential therapeutic applications in OA treatment. Additionally, patients with OA and other arthritic conditions could benefit from the biologics chondroprotective biofactors, which serve as a promising alternative to conventional knee replacement surgery.

Integrating Cover Crops as a BMP for Improving Soil Health into Commercial Vegetable Production Systems

Alternative sustainable management practices such as incorporation of cover crops into commercial crop production systems have been shown to positively influence physical, chemical, and biological aspects of soil health without negatively affecting the yields. Although the majority of soil health research has been conducted with field crops, benefits such as reduced loss of nitrogen (N) and phosphorus (P), improved nutrient balances, and increased soil carbon levels were also found in rotational systems of cover crops with vegetables as the main crop. Due to limited information on the specificity of the parameters measured for soil health for specific soils, cropping systems, and ecosystems in Florida, a two-year field study has been initiated in a commercial vegetable-cover crop system. Data presented will focus on the physical parameters of soil health and will use saturated hydraulic conductivity and bulk density as indicators of soil pore space and water movement withing the soil profile in a commercial tomato-cover crop system produced on sandy soils.