Miracle-dz/UniFAR-FTUs huggingface dataset:
Spodoptera frugiperda (Lepidoptera: Noctuidae) Life Table Comparisons and Gut Microbiome Analysis Reared on Corn Varieties

Simple Summary The food preference of an insect host plant affects its life cycle. The dietary needs and unique qualities of plants that act as hosts have an impact on insect pest population. Although Spodoptera frugiperda prefers maize (Zea mays), alternative crops can serve as appropriate hosts if maize crops are not easily available. Considering the six Z. mays cultivars in three different categories, “B: Heukjeom 2-ho” was found to be significantly preferred [F (5174) = 19.817; p = 0.0001] during the larval rearing stage. A metagenomic analysis of biological triplicate samples (6 × 3 = 18, 5th instar larvae reared on six corn cultivars) revealed that Firmicutes was the most prevalent bacterial community, and Proteobacteria was the second leading bacterial phylum. In terms of the bacterial genera, Enterococcus was the most prevalent, followed by Ureibacillus. To prevent the spread of this invasive pest, it is vital to gain a comprehensive understanding of FAW’s feeding preferences and gut microbial community composition. Abstract The fall armyworm (Spodoptera frugiperda, FAW) is an invasive migratory pest that has recently spread to Korea, damaging several corn cultivars with significant economic value. Comparisons of the growth stages of FAW were conducted based on the preferred feed. Therefore, we selected six maize cultivars, including three categories: (i) commercial waxy corn (mibaek 2-ho, heukjeom 2-ho, dreamoak); (ii) popcorn (oryun popcorn, oryun 2-ho); and (iii) processing corn (miheukchal). A significant effect was observed during the larvae period, pupal period, egg hatching ratio, and larvae weight, whereas the total survival period and adult period did not show significant variation among the tested corn cultivars. We identified variations in the FAW gut bacterial community that were dependent on the genotype of the corn maize feed. The identified phyla included Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes. Among these genera, the most abundant bacterial genus was Enterococcus, followed by Ureibacillus. Enterococcus mundtii was the most abundant among the top 40 bacterial species. The intergenic PCR-based amplification and gene sequence of the colony isolates were also matched to the GenBank owing to the prevalence of E. mundtii. These results showed that the bacterial diversity and abundance of particular bacteria in the guts of FAWs were influenced by the six major maize corn cultivars.
Aligning Federated Learning with Existing Trust Structures in Health Care Systems

Patient-centered health care information systems (PHSs) on peer-to-peer (P2P) networks (e.g., decentralized personal health records) enable storing data locally at the edge to enhance data sovereignty and resilience to single points of failure. Nonetheless, these systems raise concerns on trust and adoption in medical workflow due to non-alignment to current health care processes and stakeholders’ needs. The distributed nature of the data makes it more challenging to train and deploy machine learning models (using traditional methods) at the edge, for instance, for disease prediction. Federated learning (FL) has been proposed as a possible solution to these limitations. However, the P2P PHS architecture challenges current FL solutions because they use centralized engines (or random entities that could pose privacy concerns) for model update aggregation. Consequently, we propose a novel conceptual FL framework, CareNetFL, that is suitable for P2P PHS multi-tier and hybrid architecture and leverages existing trust structures in health care systems to ensure scalability, trust, and security. Entrusted parties (practitioners’ nodes) are used in CareNetFL to aggregate local model updates in the network hierarchy for their patients instead of random entities that could actively become malicious. Involving practitioners in their patients’ FL model training increases trust and eases access to medical data. The proposed concepts mitigate communication latency and improve FL performance through patient–practitioner clustering, reducing skewed and imbalanced data distributions and system heterogeneity challenges of FL at the edge. The framework also ensures end-to-end security and accountability through leveraging identity-based systems and privacy-preserving techniques that only guarantee security during training.
Machine learning (ML)-guided OPC using basis functions of polar Fourier transform

With shrinking feature size, runtime has become a limitation of model-based OPC (MB-OPC). A few machine learning-guided OPC (ML-OPC) have been studied as candidates for next-generation OPC, but they all employ too many parameters (e.g. local densities), which set their own limitations. We propose to use basis functions of polar Fourier transform (PFT) as parameters of ML-OPC. Since PFT functions are orthogonal each other and well reflect light phenomena, the number of parameters can significantly be reduced without loss of OPC accuracy. Experiments demonstrate that our new ML-OPC achieves 80% reduction in OPC time and 35% reduction in the error of predicted mask bias when compared to conventional ML-OPC.
Estimation of canopy bidirectional reflectance by using Bidirectional Reflectance Simulator (BiRS)

Bidirectional reflectances obtained from optical satellite sensor is effective for the estimation of vegetation quantity (e.g., above ground biomass) because biomass is related to canopy shape and the information of that canopy shape can be obtained by bidirectional reflectance. The relationships between bidirectional reflectance and canopy shape have been modeled in several studies. However, it is extremely difficult to measure the input parameters (e.g., leaf area index, leaf inclination angle) of those models in the field. Therefore, the bidirectional reflectance predicted by those models does not match with the bidirectional reflectance observed over the canopy. On the other hand, the bidirectional reflectance obtained at top of canopy by airborne or spaceborne platform is affected by limited observation geometry. In this study, we developed bidirectional reflectance simulator (BiRS) which can simulate bidirectional reflectance in any arbitrary observation geometry. BiRS can estimate bidirectional reflectance using digital surface model (DSM) and top of canopy bidirectional reflectance obtained by radio controlled helicopter.
Measurement-Integrated Simulation of Wake Turbulence

Large eddy simulation of wake turbulence was performed by integrating the lidar measurements. Four-dimensional variational method was applied to integrate lidar measurements with the three-dimensional large eddy simulation. In addition, a bogus vortex technique was adopted to ensure the existence of wake vortices in the flow field. The validation of the method was performed by idealized test cases using virtual lidar measurement which is produced by the reference simulation of a vortex pair. The results of the validation cases showed the convergence of vortex parameters such as a circulation to that of reference simulation case. It is also confirmed that the velocity distribution on a measurement plane agrees with reference one.
Fast scattering analysis over a wide frequency band using Clenshaw–Lord-type Pade–Chebyshev approximation

Pade–Chebyshev approximation of Clenshaw–Lord type with method of moments is proposed for wide-band analysis of an arbitrary-shaped perfect electric conductor structure. Moreover, various Chebyshev polynomials, such as first, third, and fourth kinds, are used to express the singular points in the graph to display the expected result for scattering characteristics. The proposed algorithm has a wide radius of convergence due to the use of Chebyshev polynomials and improves calculation speed because Clenshaw–Lord-type Pade approximation requires fewer sampling points than Maehly-type Pade approximation in the derivation of the rational function. The results of the proposed method agree very well with the exact solution and reveal its possibility of obtaining more accurate solution than the asymptotic waveform evaluation technique.
Position and Attitude Tracking Control of a Biomimetic Underwater Vehicle via Deep Reinforcement Learning

This article addresses a deep reinforcement learning (DRL) control method of position and attitude tracking for a biomimetic underwater vehicle (BUV). The BUV is actuated by two biomimetic propulsors. Each propulsor has a thick and flexible fin, which is manipulated by 12 short fin rays and can undulate in multiple wave patterns for propulsion. To achieve position and attitude tracking control on the BUV, a periodic dynamics-reparameterized soft actor-critic (SAC) algorithm is proposed. In detail, the algorithm uses the DRL method of SAC to train the controller by interacting with a simulated BUV, which is based on the propulsion model of the undulatory fin. Considering that the simulated environment may be inaccurate when compared with the real environment, some specially designed tricks are proposed. Simulations and experiments are conducted to prove the effectiveness and robustness of the proposed controller.
Classified Adaptive Filtering to GPS/INS Integrated Navigation Based on Predicted Residuals and Selecting Weight Filtering

In GPS/INS integrated navigation,the number of observations is usually less than that of the state parameters,and the single adaptive factor is usually applied in Kalman filtering,which can lead to precision loss of indirect observational parameters.A new algorithm of classified adaptive filtering is presented based on predicted residuals and selecting weight filtering,and the corresponding formulas are given.Finally,an actual calculation is given.The new algorithm can not only degrade the influence of the disturbances from the state but also avoid the loss of estimated precision of indirect observational parameters,and improve the accuracy of the navigation further.
Biodiversity of forage fishes in the Lower Laguna Madre, southernmost Texas

Coastal estuarine ecosystems serve as nursery habitats for many commercially and recreationally important fishes. Biodiversity is a structural indicator and has been used as a metric for conservation and management. In the hypersaline Lower Laguna Madre of Texas, a variety of organisms makes their living in and around the dominant seagrass vegetation. This study provides a general assessment of forage fishes biodiversity collected seasonally with bag seines in two sites: Holly Beach (HB) and South Bay (SB) within the most southern Texas bay system as part of a broader study on fish biology. A total of 15,880 fishes representing 32 species were collected during four quarterly samplings through a year (11,795 from HB and 4,085 from SB). Both sites are interconnected as no fishes similarities difference were found, nonetheless, the sites’ variable characteristics (i.e. basin area, seagrasses coverage, connection to the Gulf of Mexico) resulted in significant greater species richness, relative abundances, and diversity in HB than SB for most of the year, suggesting differences in habitat quality or at the very least variation in the availability of habitat types, which are known to contribute to differences in fish diversity attributes.
Marigold Flower Blooming Stage Detection in Complex Scene Environment using Faster RCNN with Data Augmentation

—In recent years, flower growing has developed into a lucrative agricultural sector that provides employment and business opportunities for small and marginal growers in both urban and rural locations in India. One of the most often cultivated flowers for landscaping design is the Marigold flower. It is also widely used to create garlands for ceremonial and social occasions using loose flowers. Understanding the appropriate stage of harvesting for each plant species is essential to ensuring the quality of the flowers after they have been picked. It has been demonstrated that human assessors consistently used a category scoring system to evaluate various flowering stages. Deep learning and convolutional neural networks have the potential to revolutionize agriculture by enabling efficient analysis of large-scale data. In order to address the problem of Marigold flower stages detection and classification in complex real-time field scenarios, this study proposes a fine-tuned Faster RCNN with ResNet50 network coupled with data augmentation. Faster RCNN is a popular deep learning framework for object detection that uses a region proposal network to efficiently identify object locations and features in an image. The Marigold flower dataset was collected from three different Marigold fields in the Anand District of Gujarat State, India. The collection includes of photos that were taken outdoors in natural light at various heights, angles, and distances. We have developed and fine-tuned a Faster RCNN detection and classification model to be particularly sensitive to Marigold flowers, and we have compared the generated method's performance to that of other cutting-edge models to determine its accuracy and effectiveness.
Planetary Dynamos: Magnetic Constraints on the Interior Structure and Evolution of a Planet

(Bob) Yunsheng Tian Doctor of Philosophy Department of Physics University of Toronto 2015 Planetary magnetism is a phenomenon that not only protects humanity from the destructive forces of nature, but also provides us with a natural probe into our planet’s deep interior. In this dissertation, I will explore some of the insights concerning planetary interiors that can be gained by combining the techniques of interior structure modelling with constraints provided by planetary dynamo theory. Applications to the dynamical history of the Moon, the interior evolution of Jovian planets, and predicted magnetic fields of planets in our solar system and beyond are considered under this framework. The inferred intensity and longevity of the lunar dynamo from paleomagnetic studies has led to the proposition of mechanical stirring, caused by differential rotation of the inner core and the mantle relative to the fluid outer core, as an energy source alternative to convection. Using fully three-dimensional magnetohydrodynamics (MHD) modelling techniques, I simulated the purported mechanism, and found it to reproduce not only the strength and longevity of the inferred lunar dynamo, but also its precipitous decline later in its history. For the Jovian planets, due to the lack of constraints, there are a wide range of acceptable interior models in the literature. By combining 1-D interior modelling techniques with
Effects of Non-Enzymatic Browning and Lipid Oxidation on Color of Ready-to-Eat Abalone during Accelerated Storage and Its Control

The deepening of color of ready-to-eat (RTE) abalone during storage leads to sensory quality degradation, which seriously affects the shelf life of products and consumers’ purchasing desire. The goal of this study is to look into the causes of non-enzymatic browning and lipid oxidation, as well as how to control them, and their effect on the color of RTE abalone during storage. The control, bloodletting and antioxidants groups (lactic acid, citric acid and 4-hexylresorcinol) of RTE abalone were stored for 0, 20 and 40 days at 40 °C, respectively, to explore the rule and mechanism of the color change in RTE abalone. This research shows that RTE abalone undergoes browning during storage. Meanwhile, the content of reducing sugar, phenols and unsaturated fatty acids decreases, while the formation of lipid hydroperoxides and aldehydes increases during storage. In addition, the color change in RTE abalone during storage is mainly related to the Maillard reaction, while the lipid oxidation mainly forms pyrrole and participates in the Strecker degradation process as part of the Maillard reaction. The quality of RTE abalone can be maintained by controlling browning effectively as well as lipid oxidation through bloodletting and the addition of antioxidants to ensure that RTE abalone has high storage stability. According to our research, bloodletting and the addition of antioxidants to RTE abalone have a good application prospect and popularizing value in the storage of RTE abalone.
Investigation of Sustainable Rural Tourism Activities With Different Risk: A GIS‐MCDM Case in Isfahan, Iran

Development of rural tourism activities improves the quality of life, with many associated benefits for local people. Accordingly, this study aims to prioritize tourism areas in Isfahan province using the multiple‐criteria decision‐making (MCDM) model to provide the best ecosystem services to tourists. Nine rural tourism activities (camel‐riding, hiking, mountaineering, desert tourism, wildlife observation, cycling, canyoning, camping, and horse riding) are assessed based on integrating the priorities of each suitability criteria (fuzzy membership and Analytic Hierarchical Process method) with the different risk levels. The results show that mountaineering (86.48% moderate risk; 91% high risk) and canyoning (70% moderate risk; 97% high risk) represent the best alternatives for development of tourism. According to the results of this research, tourists can make the best decisions about individual activities by determining their priorities based on associated levels of risk.
Characterizing noise in daily GPS position time series with overlapping Hadamard variance and maximum likelihood estimation

We assess the noise characteristics of daily position time series (Jet Propulsion Laboratory global solutions) from 12 International GNSS Service sites located in China, using both overlapping Hadamard variance (OHVAR) and maximum likelihood estimation (MLE). The result shows that OHVAR is computationally cheap, and the dominate power-law noise inferred is in good agreement with the ones inferred by comparing MLE values. However, OHVAR is insufficient to assess the long-period noise characteristics [e.g., random walk noise (RW)]. From the MLE analysis, the RW contribution is likely to be present in 14% of the time series, while the noise of most sites are characterized by a combination of white and flicker (or power law) noise (i.e., FL + WH or PL + WH). Moreover, sites near the northern crest of the equatorial ionization anomaly have larger amplitudes of WH in the vertical component, while no clear latitude dependency is observed in FL amplitudes.
Potential Effects of High Temperature and Heat Wave on Nanorana pleskei Based on Transcriptomic Analysis

Simple Summary Understanding how native amphibians of the Qinghai-Tibet plateau respond to pressures and their copying mechanisms could be essential for predicting their destiny in the face of climate change. A liver transcriptome was constructed to find those coping mechanisms of Nanorana pleskei. Frogs switched into hypometabolic states under high-temperature stress. However, the energy supply was basically normal to sustain the highly energy-demanding metabolic functions during heat waves. Genes were more transcriptionally suppressed for combating these long-term adverse environments to survive. High temperatures are more harmful to frogs than heat waves. Abstract In the context of climate change, understanding how indigenous amphibians of the Qinghai-Tibet plateau react to stresses and their coping mechanisms could be crucial for predicting their fate and successful conservation. A liver transcriptome for Nanorana pleskei was constructed using high-throughput RNA sequencing, and its gene expression was compared with frogs acclimated under either room temperature or high temperature and also heat wave exposed ones. A total of 126,465 unigenes were produced, with 66,924 (52.92%) of them being annotated. Up to 694 genes were found to be differently regulated as a result of abnormal temperature acclimatization. Notably, genes belonging to the heat shock protein (HSP) family were down-regulated in both treated groups. Long-term exposure to high-temperature stress may impair the metabolic rate of the frog and trigger the body to maintain a hypometabolic state in an effort to survive challenging times. During heat waves, unlike the high-temperature group, mitochondrial function was not impaired, and the energy supply was largely normal to support the highly energy-consuming metabolic processes. Genes were more transcriptionally suppressed when treated with high temperatures than heat waves, and the body stayed in low-energy states for combating these long-term adverse environments to survive. It might be strategic to preserve initiation to executive protein activity under heat wave stress. Under both stress conditions, compromising the protection of HSP and sluggish steroid activity occurred in frogs. Frogs were more affected by high temperatures than by heat waves.
Bio-economic indicators of fisheries: impact of variations in landings and fish size on market prices in Istanbul Fish Market

Fisheries are of immense importance to Mediterranean countries, for protein, employment and livelihoods. Studies addressing the factors affecting fish price dynamics are of interest to examine their drivers as prices often dictate target fisheries. This study investigates fish market prices in relation to landings and fish sizes from Türkiye’s largest fish market in Istanbul as the study site. A total of 39 wild marine taxa were examined for their landed catch (kg) and average prices (per unit/TRY) from 2006 to 2019. We found fish prices increased from small pelagic to medium pelagic to demersal fish. GAM model results for inter-species tests showed a strong positive effect of local maximum length (p < 0.01) and a weaker positive effect of trophic level and vulnerability (p < 0.1) on fish market price, but that landings amounts have no significant effect as a single predictor. Monthly price variations of bluefish and bonito were completely different than other species dynamics, as the last substantial commercial medium pelagic fish species left; highest monthly prices were related to the highest monthly landings for bonito and for the non-closure period for bluefish. Market prices as economic indicators for fisheries may have the potential to reveal ecosystem variations as well as socioeconomic drivers. Databases including extensive data for key fish sales centers can be used to help understand fishery dynamics from an ecosystem perspective, especially for data-poor regions like Türkiye.
Eco-Hydrological Modelling of a Highly Managed Mediterranean Basin Using the SWAT+ Model: A Preliminary Approach

: Highly managed Mediterranean river basins are facing considerable environmental management challenges. Water resource managers are increasingly concerned about the allocation of limited water resources, environmental quality concerns, and planning under present and future climatic change and uncertainty. We implemented a watershed-scale eco-hydrological model on the Cervaro river basin (southern Italy) using the Soil and Water Assessment Tool (SWAT+) model at daily timesteps from 1990 to 2019. A high-precision land use map derived from the Integrated Administration and Control System (IACS)/Land Parcel Identiﬁcation System (LPIS) was used to grasp detailed information regarding landscape patterns. This research is a preliminary approach for implementing and running the model with these highly detailed datasets. Future efforts should be oriented to ﬁne-tune the baseline scenario considering agricultural management practices and to evaluate model performances for calibration and validation by assessing the goodness-of-ﬁt objective function values.