Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)

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Analytical Investigation of Electromechanical Hierarchical Metamaterials for Vibration Attenuation and Energy Harvesting
Mebrat, Ashenafi Abebe; LeGrande, Joshua; Barry, Oumar (MDPI, 2025-03-21)
This work presents a theoretical study of outward and inward hierarchical metamaterials. Hierarchically configured multiple electromechanical resonators with shunt circuits are implemented, maintaining the same overall mass as that of a comparable single resonator metamaterial. The governing equations of motion for the outward and inward hierarchical configurations are derived. Dispersion relations are determined for each configuration with varying system parameters to identify key design parameters and assess their impact on the system’s dynamic behavior. Furthermore, outer mass displacement transmissibility and normalized total power output of finite chain hierarchical metamaterials are compared to observe vibration attenuation and energy harvesting capacity. The results reveal that the band structure of the hierarchical electromechanical metamaterials depends on the configuration type, the resonator masses, the electromechanical coupling coefficient, and the resistance of the shunt circuit. The first-order hierarchy offers a greater total band gap width, increased bandwidth, and greater flexibility in tuning the band structure. Finite chain transmissibility analysis demonstrates that, compared to the baseline performance of the zero-order hierarchy, the first-order hierarchy exhibits superior abilities in vibration attenuation and energy harvesting for the same total mass. The ideal design requires careful consideration of the resonator masses and their configuration, electromechanical coupling coefficient, and resistance of the shunt circuits. This theoretical work provides a foundation for designing lightweight hierarchical metamaterials for simultaneous vibration attenuation and energy harvesting.
Understanding Polysiloxane Polymer to Amorphous SiOC Conversion During Pyrolysis Through ReaxFF Simulation
Lu, Kathy; Chaney, Harrison (MDPI, 2025-03-22)
A significant challenge during the polymer-to-ceramic pyrolysis conversion is to understand the polymer-to-ceramic atomic evolution and correlate the composition changes with the precursor molecular structures, pyrolysis conditions, and resulting ceramic characteristics. In this study, a Reactive Force Field (ReaxFF) simulation approach has been used to simulate silicon oxycarbide (SiOC) ceramic formation from four different polysiloxane precursors. For the first time, we show atomically that pyrolysis time and temperature proportionally impact the new Si-O rich and C rich cluster sizes as well as the composition separation of Si-O from C. Polymer side groups have a more complex effect on the Si-O and C cluster separation and growth, with ethyl group leading to the most Si-O cluster separation and phenyl group leading to the most C cluster separation. We also demonstrate never-before correlations of gas release with polymer molecular structures and functional groups. CH₄, C₂H₆, C₂H₄, and H₂ are preferentially released from the pyrolyzing systems. The sequence is determined by the polymer molecular structures. This work is the first to atomically illustrate the innate correlations between the polymer precursors and pyrolyzed ceramics.
Feasibility of Little Cherry/X-Disease Detection in Prunus avium Using Field Asymmetric Ion Mobility Spectrometry
Kothawade, Gajanan S.; Khot, Lav R.; Chandel, Abhilash K.; Molnar, Cody; Harper, Scott J.; Wright, Alice A. (MDPI, 2025-03-25)
Little cherry disease (LCD) and X-disease have critically impacted the Pacific Northwest sweet cherry (Prunus avium) industry. Current detection methods rely on laborious visual scouting or molecular analyses. This study evaluates the suitability of field asymmetric ion mobility spectrometry (FAIMS) for rapid detection of LCD and X-disease infection in three sweet cherry cultivars (‘Benton’, ‘Cristalina’, and ‘Tieton’) at the post-harvest stage. Stem cuttings with leaves were collected from commercial orchards and greenhouse trees. FAIMS operated at 1.5 L/min and 50 kPa, was used for headspace analysis. Molecular analyses confirmed symptomatic and asymptomatic samples. FAIMS data were processed for ion current sum (I_sum), maximum ion current (I_max), and area under the curve (I_AUC). Symptomatic samples showed higher ion currents in specific FAIMS regions (p < 0.05), with clear differences between symptomatic and asymptomatic samples across compensation voltage and dispersion field ranges. Cultivar-specific variation was also observed in the data. FAIMS spectra for LCD/X-disease symptomatic samples differed from those for asymptomatic samples in other Prunus species, such as peach and nectarines. These findings support FAIMS as a potential diagnostic tool for LCD/X disease. Further studies with controlled variables and key growth stages are recommended to realize early-stage detection.
Blind Interference Suppression with Uncalibrated Phased-Array Processing
Lusk, Lauren O.; Gaeddert, Joseph D. (MDPI, 2025-03-27)
As the number of devices using wireless communications increases, the amount of usable radio frequency spectrum becomes increasingly congested. As a result, the need for robust, adaptive communications to improve spectral efficiency and ensure reliable communication in the presence of interference is apparent. One solution is using beamforming techniques on digital phased-array receivers to maximize the energy in a desired direction and steer nulls to remove interference; however, traditional phased-array beamforming techniques used for interference removal rely on perfect calibration between antenna elements and precise knowledge of the array configuration. Consequently, if the exact array configuration is not known (unknown or imperfect assumption of element locations, unknown mutual coupling between elements, etc.), these traditional beamforming techniques are not viable, so a beamforming approach with relaxed requirements (blind beamforming) is required. This paper proposes a novel blind beamforming approach to address complex narrowband interference in spectrally congested environments where the precise array configuration is unknown. The resulting process is shown to suppress numerous interference sources, all without any knowledge of the primary signal of interest. The results are validated through wireless laboratory experimentation conducted with a two-element array, verifying that the proposed beamforming approach achieves a similar performance to the theoretical performance bound of receiving packets in additive white Gaussian noise (AWGN) with no interference present.
Consumer Preference and Purchase Intention for Plant Milk: A Survey of Chinese Market
Wang, Aili; Tan, Chunhua; Yu, Wenwen; Zou, Liang; Wu, Dingtao; Liu, Xuanbo (MDPI, 2025-04-01)
Plant milks are considered to be nutritious, sustainable, and vegetarian food products, and they have been the fastest growing beverages in the past decade in China. However, few studies have investigated consumers’ demands and purchase behaviors with respect to plant milks. Through an online questionnaire (n = 1052 valid responses), this study identified the factors that influenced individuals’ purchase intentions, purchase behaviors, attitudes, and demands with respect to current and future plant milk products. Through descriptive analysis and PCA, this study revealed that nutritional value (63.6%), taste (56.3%), and calories (42.8%) were the top three factors that Chinese consumers most cared about regarding plant milks. In the current Chinese market, coconut milk is the most popular plant milk with the highest purchase rate (61.2%), followed by soymilk (53.9%). Male consumers preferred plant milk with higher protein content and fortified with antioxidants, while female consumers preferred plant milk low in calories and enriched with collagen, dietary fiber, and probiotics. Chinese consumers are willing to pay higher prices for plant milks with enhanced nutritional value, improved product quality, and strengthened safety assurances. Innovative forms of plant milk, such as bean milk, rice milk, and quinoa milk, may be developed to satisfy the diversified needs of consumers.
Phytochemical Composition and Effects of Aqueous Extracts from Moringa oleifera Leaves on In Vitro Ruminal Fermentation Parameters
Oliveira, Inessa Steffany Torres de; Fernandes, Tatiane; Santos, Aylpy Renan Dutra; González Aquino, Carolina; Vega Britez, Gustavo Daniel; Vargas Junior, Fernando Miranda de (MDPI, 2025-01-20)
This study evaluated the phytochemical composition of aqueous extracts of Moringa oleifera (MO) obtained by maceration, decoction, and infusion of fresh or dried leaves and their effects on in vitro ruminal fermentation parameters. Phytochemical prospecting analyses were conducted to determine the bioactive compounds in each aqueous extract. Regarding the in vitro ruminal fermentation study, the seven treatments were the following: no addition of extract or control (CON); extract obtained by maceration of fresh leaves (MFL); extract obtained by maceration of dry leaves (MDL); extract obtained by decoction of the fresh leaves (DFL); extract obtained by decoction of dry leaves (DDL); extract obtained by infusion of fresh leaves (IFL) and extract obtained by infusion of dry leaves (IDL). The concentration of all bioactives (saponins, flavonoids, tannins, and alkaloids) quantified was higher when fresh MO leaves were used (p < 0.001). DFL and DDL provided less elimination of azino-bis radicals. On the other hand, MFL resulted in a greater elimination of these radicals. Extracts obtained from fresh leaves resulted in a greater total production of short-chain fatty acids, acetate, and butyrate (p < 0.05). Compared to the control treatment, the inclusion of extracts obtained from fresh leaves provided a higher concentration of propionate (p = 0.049). It is thereby concluded that the use of fresh MO leaves for the production of aqueous extracts is the most recommended, as it results in a higher concentration of bioactive compounds. The use of aqueous extracts of fresh MO leaves increases the total production of fatty acids but does not change their proportion.
Enhancing Place Attachment Through Developing Public Open Places: A Cross-Cultural Study in Gold Coast, Australia
Ghasemieshkaftaki, Marzieh; Dupre, Karine; Campbell, Jennifer; Fernando, Ruwan (MDPI, 2025-01-24)
Urban studies research has increasingly focused on placemaking and place attachment in public open places. While several studies have explored how immigrants interact with these places, this study investigates how cultural differences affect immigrants’ place attachment, providing a deeper understanding of inclusive urban design. Semi-structured interviews were conducted with 21 students from India, Iran, China, and Australia, in Southport, a preferred neighborhood for immigrants on the Gold Coast, Australia. NVivo software was used to analyze the data and extract themes. The findings highlighted that, despite universal factors such as natural environments and social opportunities, cultural factors are crucial in shaping individuals’ experiences.
Cobalt Protoporphyrin IX Attenuates Antibody-Mediated, Complement-Dependent Podocyte Injury: Role of Cobalt and Porphyrin Moieties
Lianos, Elias A.; Phung, Gia Nghi; Zhou, Jianping; Sharma, Mukut (MDPI, 2025-02-23)
Metalloporphyrins (MPs) that induce heme oxygenase (HO)-1 were shown to attenuate complement-mediated glomerular injury, with cobalt protoporphyrin IX (CoPPIX) being the most effective. To decipher the efficacy between CoPPIX and its constituents (Co, PPIX), we compared the outcomes of treatment with each in a rat model of complement-dependent immune injury of glomerular epithelial cells (podocytes). Outcomes were correlated with HO-1 induction and expression levels of complement C3 and of the complement activation regulators (CARs) cluster of differentiation (CD)55, CD59, and CR1-related gene y protein product (Crry). Podocyte injury was induced in rats following a single injection of the complement-fixing antibody against the podocyte antigen, Fx1A. CoPPIX or its constituents, cobaltous chloride (CoCl₂) and protoporphyrin IX (PPIX), were injected prior to and on alternate days thereafter. Urine was assessed for protein excretion and kidney cortex samples were processed for histopathology and assessment of target gene mRNA and protein levels using digital polymerase Chain Reaction (dPCR) and capillary-based Western blot analysis. The anti-Fx1A antibody caused proteinuria and podocyte injury. Treatment with the full CoPPIX chelate reduced proteinuria but treatment with either CoCl₂ or PPIX did not. CoPPIX treatment potently induced HO-1 and reduced tissue C3 mRNA and protein levels. It also increased CD55, CD59, and Crry mRNA, with an inconsistent effect on protein levels. The Co moiety was required for HO-1 induction but not for the decrease in C3. This decrease did not significantly correlate with the effects of CoPPIX treatment on CD55 protein levels. Chelation of cobalt to PPIX enhanced its potency to induce HO-1 but reduced that on CD55 induction. These observations distinguish between the effects of CoPPIX and its constituents on proteinuria consequent to complement-mediated podocyte injury and underlying mediators and identify this MP as a potential disease-modifying agent.
Vegetation Structure and Distribution Across Scales in a Large Metropolitan Area: Case Study of Austin MSA, Texas, USA
Jamil, Raihan; Julian, Jason P.; Steele, Meredith K. (MDPI, 2025-03-03)
The spatial distribution of vegetation across metropolitan areas is important for wildlife habitat, air quality, heat mitigation, recreation, and other ecosystem services. This study investigated relationships between vegetation patterns and parcel characteristics at multiple scales of the Austin Metropolitan Statistical Area (MSA), a rapidly growing region in central Texas characterized by diverse biophysical and socioeconomic landscapes. We used LiDAR data to map vegetation types and distributions across a 6000 km² study area. Principal component analysis (PCA) and regression models were employed to explore tree, shrub, and grass cover across parcels, cities, and the MSA, considering home value, age, size, and distance to the city center. At the MSA scale, tree and shrub cover were higher in the Edwards Plateau than in the Blackland Prairie ecoregion. Tree cover increased with parcel size and home value, especially in suburban areas. Older parcels had more mature trees, though less so in the grass-dominated Blackland Prairie. Shrub cover was higher on larger parcels in the Edwards Plateau, while the Blackland Prairie showed the opposite trend. PCA explained 60% of the variance, highlighting links between vegetation and urban development. Our findings reveal how biophysical and socioeconomic factors interact to shape vegetation, offering considerations for land use, housing, and green infrastructure planning.
A Comprehensive Indoor Environment Dataset from Single-Family Houses in the US
Anik, Sheik Murad Hassan; Gao, Xinghua; Meng, Na (MDPI, 2025-03-05)
The paper describes a dataset comprising indoor environmental factors such as temperature, humidity, air quality, and noise levels. The data were collected from 10 sensing devices installed in various locations within three single-family houses in Virginia, USA. The objective of the data collection was to study the indoor environmental conditions of the houses over time. The data were collected at a frequency of one record per minute for a year, combining to a total over 2.5 million records. The paper provides actual floor plans with sensor placements to aid researchers and practitioners in creating reliable building performance models. The techniques used to collect and verify the data are also explained in the paper. The resulting dataset can be employed to enhance models for building energy consumption, occupant behavior, predictive maintenance, and other relevant purposes.
Pilot Study of a Novel First-Line Protocol (THOP) for Intermediate–Large B-Cell Lymphoma in Dogs
Tellez Silva, Alejandra; Yang, Ester; Nightengale, Marlie; Dervisis, Nikolaos; Klahn, Shawna (MDPI, 2025-03-06)
The current standard of care for treatment of intermediate–large B-cell lymphoma in dogs is a CHOP-based chemotherapy protocol. On-protocol disease progression is reported to be temporally associated with cyclophosphamide administration. The objectives of this prospective pilot clinical trial were to describe the adverse event profile and identify early signal of efficacy of a novel cyclophosphamide-free chemotherapy protocol consisting of temozolomide, doxorubicin, vincristine, and prednisone (THOP) as first-line treatment in dogs with diffuse large cell B-cell lymphoma. Treatment-naïve dogs with intermediate–large B-cell lymphoma were enrolled. THOP was administered as a three-week cycle for five cycles. Fourteen dogs were enrolled. All dogs achieved complete remission with a median time to progression (TTP) of 269 days and a median survival of 433 days. There were five grade III and four grade IV hematologic toxicities reported; one grade III gastrointestinal toxicity was observed. THOP appears to be well tolerated and an effective first-line protocol for the treatment of intermediate–large B-cell lymphoma in dogs.
Comparing Reflectivity from Space-Based and Ground-Based Radars During Detection of Rainbands in Two Tropical Cyclones
Matyas, Corene J.; Zick, Stephanie E.; Wood, Kimberly M. (MDPI, 2025-03-06)
With varying tangential winds and combinations of stratiform and convective clouds, tropical cyclones (TCs) can be difficult to accurately portray when mosaicking data from ground-based radars. This study utilizes the Dual-frequency Precipitation Radar (DPR) from the Global Precipitation Measurement Mission (GPM) satellite to evaluate reflectivity obtained using four sampling methods of Weather Surveillance Radar 1988-Doppler data, including ground radars (GRs) in the GPM ground validation network and three mosaics, specifically the Multi-Radar/Multi-Sensor System plus two we created by retaining the maximum value in each grid cell (MAX) and using a distance-weighted function (DW). We analyzed Hurricane Laura (2020), with a strong gradient in tangential winds, and Tropical Storm Isaias (2020), where more stratiform precipitation was present. Differences between DPR and GR reflectivity were larger compared to previous studies that did not focus on TCs. Retaining the maximum value produced higher values than other sampling methods, and these values were closest to DPR. However, some MAX values were too high when DPR time offsets were greater than 120 s. The MAX method produces a more consistent match to DPR than the other mosaics when reflectivity is <35 dBZ. However, even MAX values are 3–4 dBZ lower than DPR in higher-reflectivity regions where gradients are stronger and features change quickly. The DW and MRMS mosaics produced values that were similar to one another but lower than DPR and MAX values.
Effects of Monensin, Calcareous Algae, and Essential Oils on Performance, Carcass Traits, and Methane Emissions Across Different Breeds of Feedlot-Finished Beef Cattle
Guerreiro, Pedro; Costa, Diogo F. A.; Limede, Arnaldo C.; Congio, Guilhermo F. S.; Meschiatti, Murillo A. P.; Bernardes, Priscila A.; Santos, Flavio A. Portela (MDPI, 2025-01-08)
With the growing use of crossbred cattle in Brazilian feedlots and increasing pressure to reduce antibiotic use as growth promoters, this study examines the impact of three feed additives—monensin (MON), monensin with Lithothamnium calcareum (LCM), and a blend of essential oils (BEO)—on the performance of Nellore (NEL) and crossbred (CROSS) cattle. A total of 90 Nellore and 90 crossbred bulls were assigned to a completely randomized block design with a 2 × 3 factorial design for 112 days, and all received the same diet with varying additives. Their methane (CH₄) emissions were estimated. All data were analyzed using the emmeans package of R software (version 4.4.1). Crossbred cattle outperformed Nellore in average daily gain (ADG), hot carcass weight (HCW), and dry matter intake (DMI), though feed efficiency remained unaffected. Across additives, no significant differences were observed in ADG, HCW, or dressing percentage. However, LCM had a lower DMI than the BEO, while MON showed better feed efficiency than the BEO. A breed-by-additive interaction trend was noted for DMI as a percentage of body weight (DMI%BW), with Nellore bulls on LCM diets showing the lowest DMI%BW. Crossbreeds had greater net energy (NE) requirements for maintenance (NEm) and gain (NEg), and MON-fed animals had greater NEm and NEg than the BEO. Crossbred bulls had greater daily methane (CH₄) emissions than Nellore bulls. Animals on the BEO had greater daily CH₄ emissions and greater g CH₄/kg metabolic BW than LCM bulls. In conclusion, the addition of Lithothamnium calcareum to monensin did not enhance performance compared to monensin alone. Monensin outperformed the BEO in feed efficiency and nutrient utilization.
Assessment of 18 Years of Genetic Marker-Assisted Selection and Augmentation of Native Walleye in the Upper New River, Virginia, USA
Harris, Sheila; Palmer, George; Copeland, John R.; Williams, Joe; Hallerman, Eric M. (MDPI, 2025-03-06)
Walleye Sander vitreus is a valued sportfish in eastern North America, including the upper New River of Virginia, where individuals can grow to a large size (>7 kg). After construction of dams, especially Claytor Dam in 1939, the population declined and non-native walleye were stocked. Stocking of non-native walleye was stopped in 1997, and molecular marker data showed that the presumptive native population had persisted. To restore the native stock, selection of broodstock candidates bearing native marker alleles and hatchery-based augmentation have been practiced over a 20-year period. We evaluated the success of the marker-assisted selection and hatchery-based augmentation program. Marker-assisted selection of native New River walleye began with mean frequencies of marker alleles at microsatellite loci Svi17 and Svi33 of ~30%, and continuing selection has driven marker allele frequencies to ~65–70%. Numbers of walleye collected in fall gillnet and spring electrofishing surveys were responsive to augmentations with hatchery fish 2–3 years earlier. Stocking was not practiced in 2012–2013, and a decrease in walleye catch rates was noted in 2016, suggesting that the native New River walleye population still depends upon hatchery-based augmentation. We recommend the development of a small panel of single nucleotide polymorphism markers for more rigorous selection of broodstock representative of the native walleye population.
Deep Learning Ensemble Approach for Predicting Expected and Confidence Levels of Signal Phase and Timing Information at Actuated Traffic Signals
Eteifa, Seifeldeen; Shafik, Amr; Eldardiry, Hoda; Rakha, Hesham A. (MDPI, 2025-03-07)
Predicting Signal Phase and Timing (SPaT) information and confidence levels is needed to enhance Green Light Optimal Speed Advisory (GLOSA) and/or Eco-Cooperative Adaptive Cruise Control (Eco-CACC) systems. This study proposes an architecture based on transformer encoders to improve prediction performance. This architecture is combined with different deep learning methods, including Multilayer Perceptrons (MLP), Long-Short-Term Memory neural networks (LSTM), and Convolutional Long-Short-Term Memory neural networks (CNNLSTM) to form an ensemble of predictors. The ensemble is used to make data-driven predictions of SPaT information obtained from traffic signal controllers for six different intersections along the Gallows Road corridor in Virginia. The study outlines three primary tasks. Task one is predicting whether a phase would change within 20 s. Task two is predicting the exact change time within 20 s. Task three is assigning a confidence level to that prediction. The experiments show that the proposed transformer-based architecture outperforms all the previously used deep learning methods for the first two prediction tasks. Specifically, for the first task, the transformer encoder model provides an average accuracy of 96%. For task two, the transformer encoder models provided an average mean absolute error (MAE) of 1.49 s, compared to 1.63 s for other models. Consensus between models is shown to be a good leading indicator of confidence in ensemble predictions. The ensemble predictions with the highest level of consensus are within one second of the true value for 90.2% of the time as opposed to those with the lowest confidence level, which are within one second for only 68.4% of the time.
ShipNetSim: An Open-Source Simulator for Real-Time Energy Consumption and Emission Analysis in Large-Scale Maritime Networks
Aredah, Ahmed; Rakha, Hesham A. (MDPI, 2025-03-08)
The imperative of decarbonization in maritime shipping is underscored by the sector’s sizeable contribution to worldwide greenhouse gas emissions. ShipNetSim, an open-source multi-ship simulator created in this study, combines state-of-the-art hydrodynamic modeling, dynamic ship-following techniques, real-time environmental data, and cybersecurity threat simulation to quantify and evaluate marine fuel consumption and CO₂ emissions. ShipNetSim uses well-validated approaches, such as the Holtrop resistance and B-Series propeller analysis with a ship-following model inspired by traffic flow theory, augmented with a novel module simulating cyber threats (e.g., GPS spoofing) to evaluate operational efficiency and resilience. In a case study simulation of the journey of an S175 container vessel from Savannah to Algeciras, the simulator estimated the total fuel consumption to be 478 tons of heavy fuel oil and approximately 1495 tons of CO₂ emissions for a trip of 7 days and 15 h within 13.1% of reported operational estimates. A twelve-month sensitivity analysis revealed a marginal 1.5% range of fuel consumption variation, demonstrating limiting variability for different environmental conditions. ShipNetSim not only yields realistic predictions of energy consumption and emissions but is also demonstrated to be a credible framework for the evaluation of operational scenarios—including speed adjustment, optimized routing, and alternative fuel strategies—that directly contribute to reducing the marine carbon footprint. This capability supports industry stakeholders and policymakers in achieving compliance with global decarbonization targets, such as those established by the International Maritime Organization (IMO).
Functional Verification of the Soybean Pseudo-Response Factor GmPRR7b and Regulation of Its Rhythmic Expression
Song, Ziye; Liu, Jia; Qian, Xueyan; Xia, Zhengjun; Wang, Bo; Liu, Nianxi; Yi, Zhigang; Li, Zhi; Dong, Zhimin; Zhang, Chunbao; Zhang, Bo; Tadege, Million; Dong, Yingshan; Li, Yuqiu (MDPI, 2025-03-09)
The pseudo response regulator (PRR) gene is an important component of the core oscillator involved in plant circadian rhythms and plays an important role in regulating plant growth and development and stress responses. In this study, we investigated the function of GmPRR7b by overexpression and gene editing approaches. It was found that GmPRR7b plays a role in delaying flowering. While GmPRR7b overexpressing plants showed significantly delayed flowering compared to untransformed WT, GmPRR7b edited plants flowered earlier than the control WT. On the basis of previous research results and bioinformatics analysis, we re-identified 14 soybean PRR genes and analysed their rhythmic expression. Based on the rhythmic expression pattern, we found that GmPRR5/9a and GmPRR5/9b interacted with GmPRR7b by yeast two-hybrid and bimolecular fluorescence complementation (BiFC) experiments. Combined with the expression regulatory networks of the GmPRR7b, we inferred a possible regulatory mechanism by which GmPRR7b affects flowering through quit rhythm expression. These research elements provide valuable references for understanding growth, development, and circadian regulation in soybean.
Training School-Based Health Clinicians in New Mexico Regarding Adverse Childhood Experiences
Katzman, Joanna G.; Tomedi, Laura E.; Chari, Krishna; Pandey, Navin; Del Fabbro, Anilla; Ramos, Mary; Kazhe-Dominguez, Briana (MDPI, 2025-03-14)
Background: Adverse childhood experiences (ACEs) are potentially traumatic experiences that may promote poor mental health, including substance use and suicidality, as well as chronic pain. Telementoring may be used to provide education to school-based health center (SBHC) clinicians and other health professionals in the community to identify and support youth with ACEs. Methods: This study was an evaluation of the novel ACEs ECHO telementoring program, which incorporates didactics, case-based learning, and a community of practice to serve school-based health clinicians in New Mexico, a rural state with a high prevalence of ACEs. Results: In the program’s first two years, there were 704 unique participants, including SBHC clinicians from 25 of New Mexico’s 33 counties. The pre/post survey demonstrated that the participants reported increases in knowledge in identifying children that experienced ACEs (4.3 versus 3.7, p = 0.001) and confidence in supporting children who may be at high risk (4.1 versus 3.3, p = 0.001) compared with before they began attending the ACEs ECHO program. The participants also reported that they felt more hopeful that they could help youth with ACEs (4.2 versus 3.3, p = 0.001). Conclusions: The ACEs ECHO telementoring program may be considered for other rural states and globally as a capacity-building model to educate SBHC clinicians and other health professionals to identify youth at risk for adverse childhood experiences.
Predicting Dairy Calf Body Weight from Depth Images Using Deep Learning (YOLOv8) and Threshold Segmentation with Cross-Validation and Longitudinal Analysis
Liao, Mingsi; Morota, Gota; Bi, Ye; Cockrum, Rebecca R. (MDPI, 2025-03-18)
Monitoring calf body weight (BW) before weaning is essential for assessing growth, feed efficiency, health, and weaning readiness. However, labor, time, and facility constraints limit BW collection. Additionally, Holstein calf coat patterns complicate image-based BW estimation, and few studies have explored non-contact measurements taken at early time points for predicting later BW. The objectives of this study were to (1) develop deep learning-based segmentation models for extracting calf body metrics, (2) compare deep learning segmentation with threshold-based methods, and (3) evaluate BW prediction using single-time-point cross-validation with linear regression (LR) and extreme gradient boosting (XGBoost) and multiple-time-point cross-validation with LR, XGBoost, and a linear mixed model (LMM). Depth images from Holstein (n = 63) and Jersey (n = 5) pre-weaning calves were collected, with 20 Holstein calves being weighed manually. Results showed that You Only Look Once version 8 (YOLOv8) deep learning segmentation (intersection over union = 0.98) outperformed threshold-based methods (0.89). In single-time-point cross-validation, XGBoost achieved the best BW prediction (R² = 0.91, mean absolute percentage error (MAPE) = 4.37%), while LMM provided the most accurate longitudinal BW prediction (R² = 0.99, MAPE = 2.39%). These findings highlight the potential of deep learning for automated BW prediction, enhancing farm management.
Ground–Surface Water Assessment for Agricultural Land Prioritization in the Upper Kansai Basin, India: An Integrated SWAT-VIKOR Framework Approach
Halder, Sudipto; Banerjee, Santanu; Youssef, Youssef M.; Chandel, Abhilash; Alarifi, Nassir; Bhandari, Gupinath; Abd-Elmaboud, Mahmoud E. (MDPI, 2025-03-19)
Prioritizing agricultural land use is a significant challenge for sustainable development in the rapidly urbanizing, semi-arid riverine basins of South Asia, especially under climate variability and water scarcity. This study introduces a systematic framework combining remote sensing and geospatial data with the Soil and Water Assessment Tool (SWAT) model, morphometric analysis, and VIKOR-based Multi-Criteria Decision Analysis (MCDA) to effectively identify Agricultural Land Prioritization (AgLP) areas in the Upper Kansai Basin, India, while reducing the environmental impact, in line with Sustainable Development Goals (SDGs). The SWAT model simulation reveals varied hydrological patterns, with basin water yields from 965.9 to 1012.9 mm and a substantial baseflow (~64% of total flow), emphasizing essential groundwater–surface water interactions for sustainable agriculture. However, the discrepancy between percolation (47% of precipitation) and deep recharge (2% of precipitation) signals potential long-term groundwater challenges. VIKOR analysis offers a robust prioritization framework, ranking SW4 as the most suitable (Qi = 0.003) for balanced hydrological and morphometric features, in agreement with the SWAT outcomes. SW4 and SW5 display optimal agricultural conditions due to stable terrain, effective water retention, and favorable morphometric traits (drainage density 3.0–3.15 km/km²; ruggedness 0.3–0.4). Conversely, SW2, with high drainage density (5.33 km/km²) and ruggedness (2.0), shows low suitability, indicating risks of erosion and poor water retention. This integrated AgLP framework advances sustainable agricultural development and supports SDGs, including SDG 2 (Zero Hunger), SDG 6 (Clean Water), SDG 13 (Climate Action), and SDG 15 (Life on Land). Incorporating hydrological dynamics, land use, soil properties, and climate variables, this approach offers a precise assessment of agricultural suitability to address global sustainability challenges in vulnerable riverine basins of developing nations.

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