Search Results (370)

High-precision 6D pose estimation for pick-and-place operations remains a critical problem for industrial robot arms in manufacturing. This study introduces an analytics-based solution for 6D pose estimation designed for a real-world industrial application: it enables the Staubli TX2-60L (manufactured by Stäubli International AG, Horgen, Switzerland) robot arm to pick up metal plates from various locations and place them into a precisely defined slot on a brake pad production line. The system uses a fixed eye-to-hand Intel RealSense D435 RGB-D camera (manufactured by Intel Corporation, Santa Clara, California, USA) to capture color and depth data. A robust software infrastructure developed in LabVIEW (ver.2019) integrated with the NI Vision (ver.2019) library processes the images through a series of steps, including particle filtering, equalization, and pattern matching, to determine the X-Y positions and Z-axis rotation of the object. The Z-position of the object is calculated from the camera’s intensity data, while the remaining X-Y rotation angles are determined using the angle-of-inclination analytics method. It is experimentally verified that the proposed analytical solution outperforms the hybrid-based method (YOLO-v8 combined with PnP/RANSAC algorithms). Experimental results across four distinct picking scenarios demonstrate the proposed solution’s superior accuracy, with position errors under 2 mm, orientation errors below 1°, and a perfect success rate in pick-and-place tasks. Full article

The gross benefit of feeding multi-species probiotics has been reported, but the effect on the gut microbiota in pre-weaned dairy calves has not been elucidated. To address this gap, a randomized controlled trial was conducted in California, USA, to investigate the effect of feeding probiotics on the fecal microbiota of pre-weaned dairy calves. A total of 30 neonatal calves were randomly assigned to either the probiotic (PRO) or control (CON) treatment. Fecal samples were collected at four age timepoints: days 7, 14, 21, and 42. Fecal bacterial population was analyzed using 16S rRNA amplicon sequencing. Differential abundance analysis was conducted to investigate the difference between the PRO and CON treatments, and diarrheic and non-diarrheic calves in each PRO and CON group. The PRO group had decreased Clostridium perfringens and Fusobacterium varium compared to the CON at 7 days of age. At 7 days of age, diarrheic calves in CON had more abundant F. varium compared to non-diarrheic calves, but there was no difference between diarrheic and non-diarrheic calves in the PRO group. In conclusion, probiotics administration decreased the population of pathogenic bacteria in feces from pre-weaned dairy calves on Day 7 of age. However, the treatment did not have an impact on bacterial diversity. These results suggest that the administration of probiotics has the potential to control gastrointestinal pathogens. Full article

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue in recent years, is lacking. The team proposes a traffic prediction method that leverages K-means clustering, long short-term memory (LSTM) neural network, and Fourier transform (FT) for long-term traffic prediction. The proposed method was evaluated on a real-world dataset from the U.S. Travel Monitoring Analysis System (TMAS) database, which enhances practical relevance and potential impact on transportation planning and management. The forecasting performance is evaluated with real-world traffic flow data in the state of California, in the western USA. Results show good forecasting accuracy on traffic trends and counts over a one-year period, capturing periodicity and variation. Full article

Residual dry matter (RDM) is a term used in rangeland management to describe the non-photosynthetic plant material left on the soil surface at the end of the growing season. RDM measurements are used by agencies and conservation entities for managing grazing and fire fuels. Measuring the RDM using traditional methods is labor-intensive, costly, and subjective, making consistent sampling challenging. Previous studies have assessed the use of multispectral remote sensing to estimate the RDM, but with limited success across space and time. The existing approaches may be improved through the use of spectroscopic (hyperspectral) sensors, capable of capturing the cellulose and lignin present in dry grass, as well as Unmanned Aerial Vehicle (UAV)-mounted Light Detection and Ranging (LiDAR) sensors, capable of capturing centimeter-scale 3D vegetation structures. Here, we evaluate the relationships between the RDM and spectral and LiDAR data across the Jack and Laura Dangermond Preserve (Santa Barbara County, CA, USA), which uses grazing and prescribed fire for rangeland management. The spectral indices did not correlate with the RDM (R² < 0.1), likely due to complete areal coverage with dense grass. The LiDAR canopy height models performed better for all the samples (R² = 0.37), with much stronger performance (R² = 0.81) when using a stratified model to predict the RDM in plots with predominantly standing (as opposed to laying) vegetation. This study demonstrates the potential of UAV LiDAR for direct RDM quantification where vegetation is standing upright, which could help improve RDM mapping and management for rangelands in California and beyond. Full article

The increasing frequency and intensity of wildfires in hard-to-reach and hazardous areas represents a significant challenge for traditional firefighting methods. Wildfires pose a growing threat to the environment, property, and human lives. In many cases, conventional suppression techniques prove ineffective, highlighting the need for innovative and efficient solutions. Recent fires in the Bohemian Switzerland National Park in the Czech Republic; the Los Angeles area in California, USA; and the southeastern region of South Korea have underscored the necessity for alternative wildfire mitigation strategies. This article explores the potential of employing military technologies, such as artillery systems and specialized munitions, in wildfire suppression. The analysis includes a review of previous experiments, the research into non-standard methods, and an assessment of the risks and limitations associated with these approaches. Based on the research and simulations, it was found that one salvo (eight rounds) of fire-suppressant shells can cover up to 650 m² of terrain with suppressant. Finally, this article proposes a direction for further research aimed at integrating military and civilian technologies to enhance the effectiveness of wildfire response. This work contributes to the ongoing discussion on the integration of artillery capabilities into crisis management and provides a foundation for the future research in this field. Full article

Background/Objectives: Safety-net health centers are increasingly screening for food insecurity and providing patients with referrals to public assistance programs—e.g., the Supplemental Nutrition Assistance Program (SNAP). However, not all individuals actively participate in or are eligible for these programs. Onsite distributions of free produce at health center sites represent a promising complementary option for addressing this need. This study examines free produce events at these sites and their associations with attendees’ food and vegetable consumption, household food insecurity, and SNAP participation (study outcomes). Methods: In 2024, an intercept survey was conducted with 497 adults attending produce events at 16 safety-net health center sites in Los Angeles County, California, USA. Descriptive analyses profiled these food events, gathering information on attendee characteristics. Multivariable regressions examined associations between event attendance and study outcomes. Results: Over 80% of attendees lived in food-insecure households. Among those who were patients of the event site, 68% and 28%, respectively, indicated they received information about Medicaid and SNAP from the clinic staff. Compared to first-time attendees, those who attended produce events frequently consumed, on average, one additional serving of fruit and vegetables a day (p < 0.000). Conclusions: Offering free produce events at health center sites, where many attendees receive usual care, is a promising strategy for increasing healthy food access among safety-net populations. This underutilized approach is a viable intervention for improving access to healthy food, especially in circumstances where patients are not eligible for public assistance or nutrition incentive and/or food pharmacy programs are not readily available. Full article

Euglena gracilis is a metabolically versatile microalga capable of thriving under photoautotrophic (light, no ethanol), mixotrophic (light with 1% v/v ethanol), and heterotrophic (dark with 1% v/v ethanol) conditions. Here, we applied untargeted LC-MS metabolomics (Agilent 1290 LC, 6545XT QTOF-MS; Agilent Technologies, Santa Clara, California, USA) to investigate its trophic-mode-dependent metabolic adaptations and assess its biotechnological potential. Metabolites were separated on a C18 column and analyzed in both positive and negative ion modes. Multivariate analyses (PCA and sPLS-DA) revealed clear and reproducible metabolic separations among growth modes (p < 0.001). Photoautotrophic cultures were enriched in phenolic acids, flavonoids, and lipid classes associated with oxidative stress protection. Mixotrophy induced a broader spectrum of upregulated metabolite classes, including saccharolipids, macrolactams, and triterpenoids, reflecting a hybrid metabolism combining photosynthesis and ethanol utilization. Heterotrophic cultures showed elevated levels of polyamines and amino acids (e.g., putrescine, proline), indicative of redox regulation and stress adaptation in dark, ethanol-rich conditions. Class-level comparisons identified distinct and shared metabolite categories, with photoautotrophy favoring antioxidant biosynthesis and mixotrophy supporting metabolic diversity. These findings provide metabolite-level insights into the extraordinary plasticity of E. gracilis and offer a framework for optimizing cultivation strategies to enhance the targeted production of high-value bioproducts. Full article

This study aims to elucidate the characteristics of the mitogenome of Lysmata lipkei and investigate its phylogenetic relationships. Using both the Illumina NovaSeq 6000 (Illumina, Inc., San Diego, CA, USA) and PacBio Sequel II (Pacific Biosciences of California, Inc., Menlo Park, CA, USA) platforms, the complete mitogenome sequence of L. lipkei was determined. The mitogenome of L. lipkei was annotated, measuring 17,497 bp in length and comprising 13 protein-coding genes (PCGs), 2 ribosomal RNA genes (rRNAs), and 22 transfer RNA genes (tRNAs). The nucleotide composition of the genome exhibited an AT bias of 63.4%. Among the PCGs, the most frequently used codon was UUA. All tRNAs, except for trnD, which lacks the TψC loop, were capable of forming the typical cloverleaf structure. Phylogenetic trees for Caridea were constructed using Bayesian Inference (BI) and Maximum Likelihood (ML) methods based on the nucleotide sequences of the 13 PCGs. Both methods yielded consistent topological structures, with L. lipkei showing the closest phylogenetic relationship to L. kuekenthali. Additionally, Lysmatidae, Thoridae, and Hippolytidae formed a monophyletic clade. This research not only filled the gap in mitogenome data for Lysmatidae but also provided novel molecular insights into Caridean phylogenetics. Full article

Ground deformation poses a major threat to socioeconomic development, especially in coastal regions where compounding effects of anthropogenic activities and natural processes exacerbate its destructive consequences. This urgency calls for comprehensive, spatially extensive, and temporally continuous deformation monitoring. In this study, we propose a joint track small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) methodology that enhances conventional SBAS-InSAR workflows through integration of ascending and descending orbit data processing, enabling accurate extraction of vertical surface deformation. By analyzing 2348 Sentinel-1 acquisitions, we derived vertical ground deformation across coastal California. The proposed method demonstrates superior measurement accuracy (4.81 mm/year) compared to individual ascending track (7.19 mm/year) or descending track (7.07 mm/year) results. Our analysis identifies substantial deformation signals in coastal urban centers, reveals deformation-fault distribution correlations, and documents characteristic subsidence patterns induced by subsurface resource extraction. These comprehensive data and insights provide invaluable support for the prevention and mitigation of ground deformation in coastal California, and serve as a scientific basis for formulating effective prevention and control strategies, ensuring the safety and sustainable development of these vulnerable coastal regions. Full article

Amid the advancements in computer-based chemical process modeling and simulation packages used in commercial applications aimed at accelerating chemical process design and analysis, there are still certain tasks in design optimization, such as distillation column internals design, that become bottlenecks due to inherent limitations in such software packages. This work demonstrates the use of soft actor-critic (SAC) reinforcement learning (RL) in automating the task of determining the optimal design of trayed multistage distillation columns. The design environment was created using the AspenPlus^® software (version 12, Aspen Technology Inc., Bedford, Massachusetts, USA) with its RadFrac module for the required rigorous modeling of the column internals. The RL computational work was achieved by developing a Python package that allows interfacing with AspenPlus^® and by implementing in OpenAI’s Gymnasium module (version 1.0.0, OpenAI Inc., San Francisco, California, USA) the learning space for the state and action variables. The results evidently show that (1) SAC RL works as an automation approach for the design of distillation column internals, (2) the reward scheme in the SAC model significantly affects SAC performance, (3) column diameter is a significant constraint in achieving column internals design specifications in flooding, and (4) SAC hyperparameters have varying effects on SAC performance. SAC RL can be implemented as a one-shot learning model that can significantly improve the design of multistage distillation column internals by automating the optimization process. Full article

The pursuit of sustainable protein is underway. This debate is often framed as a choice between two competing agrifood futures: the “no cow” and “clean cow” perspectives. The former comes from alternative protein advocates, while the latter aims to support practices, discourses, and livelihoods associated with regenerative ranching. The findings presented reveal greater nuance than what this simplistic dichotomy suggests. This paper utilizes data collected from fifty-eight individuals in California and Colorado (USA). Participants in the sample were identified by their attendance at various events focused on sustainability in protein production and includes a subsample of regenerative farmers who self-identified as persons of color, disabled or differently abled, and/or part of the LGBTQIA+ (Lesbian, Gay, Bisexual, Transgender, Queer/Questioning, Intersex, Asexual) community. The sample features a range of viewpoints associated with regenerative livestock and non-livestock protein production. The data support arguments aligned with “clean cow” framings, as determined by the anticipated scope of sustainable protein transformations. However, the paper cautions against solely relying on this frame without further interrogating its contours. It particularly notes that the values of specific “clean cow” actors and networks mirror key aspects of “no cow” perspectives. These similarities are especially evident among upstream actors like investors, corporate interests, and government sponsors. For these individuals and networks, the “no” versus “clean” distinction—despite suggesting radically different agrifood futures—overshadows underlying shared concerns that align with core elements of the status quo. A case is also made for greater reflexivity and, thus, inclusivity as we think about who is included in these debates, as the data tell us that this shapes how we frame what is at stake. Full article

Background: Exposure to pesticides has been associated with an increased risk of developing childhood leukemia. However, the impact of pesticides on childhood leukemia survival has not been examined. We investigated the associations between residential pesticide use during key developmental periods and 5-year survival in children treated for acute lymphoblastic leukemia (ALL). Methods: Residential use of insecticides, herbicides, rodenticides, and flea control products from preconception up to 12 months prior to diagnosis and sociodemographic characteristics were collected via parental interview among 837 children diagnosed with ALL between 1995 and 2008 in California, USA. Data on clinical features were abstracted from medical records. Vital status was obtained through linkage to the National Death Index (NDI) up to 2020. Cox proportional hazards regression models were used to estimate hazard ratios (HRs), adjusting for sociodemographic factors and clinical risk group. Results: A total of 108 children with ALL (~13%) died within 5 years of diagnosis. Exposure to any pesticides pre- and/or postnatally was slightly higher among deceased compared to alive children (95.4% vs. 91.5%; p = 0.23), while use of rodenticides was significantly higher in children who died (25.0%) vs. those who survived (15.5%; p = 0.02). In fully adjusted models, exposure to rodenticides was associated with an increased risk of mortality (HR 1.70; 95% confidence interval (CI) 1.08–2.64; p = 0.02), especially when the child was exposed during pregnancy (HR 1.90; 95% CI 1.15–3.16; p = 0.01) and possibly 12 months before diagnosis (HR 1.60; 95% CI 0.98–2.61; p = 0.06). Increased hazards of death were also observed with other types of pesticides during pregnancy, but those associations were not statistically significant. Conclusions: This study is the first to report reduced survival among children with ALL previously exposed to rodenticides, particularly during pregnancy, underscoring the need to further evaluate mechanisms by which environmental exposures during key developmental stages may later impact cancer outcomes. Full article

This research explores the optimal operation of an offshore wave-powered hydrogen system, specifically designed to supply electricity and water to a bay in Humboldt, California, USA, and also sell it with hydrogen. The system incorporates a desalination unit to provide the island with fresh water and feed the electrolyzer to produce hydrogen. The optimization process utilizes a mixture of experts in conjunction with the Quantitative Structure-Activity Relationship (QSAR) algorithm traditionally used in drug design, to achieve two main objectives: minimizing operational costs and maximizing revenue from the sale of water, hydrogen, and electricity. Many case studies are examined, representing typical electricity demand and wave conditions during typical summer, winter, spring, and fall days. The simulation, optimization, and results are carried out using MATLAB 2018 and SAM 2024 software applications. The findings demonstrate that the combination of the QSAR algorithm and quantum-inspired MoE results in higher revenue and lower costs compared to other current techniques, with hydrogen sales being the primary contributor to increased income. Full article

Hibiscus, which belongs to the Malvaceae family, is primarily distributed in tropical and subtropical regions. Hibiscus species are known for their large, visually striking flowers, which are highly valued for ornamental purposes and are widely admired. Despite this diversity, the mitochondrial DNA of Hibiscus species remains largely unexplored. Here, we assembled chromosome-level mitochondrial genomes (mitogenomes) of H. schizopetalus, H. syriacus, H. hamabo, and Talipariti tiliaceum (Hibiscus tiliaceum) using Illumina short reads (Illumina, Inc., San Diego, CA, USA) and PacBio long reads (Pacific Biosciences of California, Inc., Menlo Park, CA, USA), and conducted comparative genomic analyses. Our findings revealed that the mitogenomes of Hibiscus species exhibited structural complexity, including variable sizes and multi-molecular configurations, while maintaining high conservation in codon usage bias and GC content. Repeat sequence analysis suggested that repeat-mediated homologous recombination played a critical role in frequent recombination events in the mitogenomes. In addition, phylogenetic analysis showed that Hibiscus species did not form a monophyletic clade, and H. hamabo and T. tiliaceum were positioned in sister clades, which was consistent with the results of synteny analysis. To sum up, our study provides valuable resources for phylogenetic research and makes significant contributions to exploring further genetic mechanisms and biodiversity of Hibiscus species. Full article

The polyphagous Lygus hesperus Knight is a serious pest on many crops in the western USA, including California’s central coast. Although L. hesperus adults can cause damage to broccoli and cauliflower, symptoms from their interactions with these plants are not fully characterized. Characterizing the feeding and ovipositional damage will help in the early diagnosis of the problem in the field and in greenhouses. Thus, the objective of this study was to characterize the feeding and ovipositional injury symptoms in broccoli and cauliflower after exposing 0, 1, 3, 5, and 10 adult L. hesperus to seedlings of broccoli and cauliflower for 24 h, 48 h, and 7 d. Although distorted and “blind” shoots were observed, feeding injury did not rapidly manifest into damage after 7 d post-exposure with high counts of adults on broccoli and cauliflower seedlings. The ovipositional injury was expressed as lesions that developed rapidly with a high density of adults in 24 h. The same levels of damage were observed with three or five adults to these hosts in 48 h. Significant positive correlations between the total eggs and lesions developed were observed on broccoli and cauliflower seedlings. After adult L. hesperus exposure, the growth of broccoli seedlings was reduced, but there was no effect on the growth of cauliflower seedlings. For diagnosis, data show that lesions are associated with adult L. hesperus ovipositional activity on these crops, which recommends thorough scouting and immediate application of plant protectants to reduce potential crop loss in greenhouses and in the field. Full article