Mammarenavirus Wenzhouense (WENV) is broadly distributed in Asia, while the he dynamics process of WENV infection remains unclear. A field derived strain of WENV was used to inoculate Sprague-Dawley (SD) rats by intramuscular injection, the process of virus infection was de-tected by controlling time for 28 days. Viral RNA became detectable in the blood at 3 d pi, and remained detectable for about 12 d. In most organ tissues, viral RNA peaked at 7 d pi, then began to decline by 14 d, however remained detectable in intestine and brain tissues at 21 and 28 d pi. Virus shedding had been detected from fecal samples for 5 days from 6 to 11 d pi using qRT-PCR, and was recovered from feces collected at 8 d pi. Horizontal contact infection occurred among cage-mates at 14 and 21 d pi. Antibodies against the nucleocapsid were detected at 5 dpi, next increased and persisted until the end of experiment. The results enabled to discriminate the kinetic of viremic response, virus shedding in feces and horizontal transmission, as well as the potential sites for WENV replication or maintenance of the virus in nature.

To address the response of small RNAs (sRNAs) biogenesis to drought stress, we identified sRNAs biogenesis genes, including 11 encoding argonauts (AGO), 8 encoding dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNAs biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNAs biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are drought tolerance and sensitive, respectively. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach.

Violence against healthcare workers (HCWs) is a widespread, underreported and inadequately prevented problem. Only a few companies have efficient systems for assessing the extent of the phenomenon. In 2005, the health surveillance service of a public health company introduced a system that monitored violence experienced by HCWs by means of three items from the Violent Incident Form (VIF), integrated with departmental in-depth analyses using the participatory ergonomics group technique. In 2005, the annual rate of physical assaults was 8.2%, that of threats 12.0%, while the harassment rate was 19.6%. Over the past twenty years of observation (2005-2024), the percentage of workers who reported experiencing a physical attack in the previous year at their periodic medical examination, has fluctuated between 5.8% and 11.1%, except for the years 2020 and 2021 when, during the COVID-19 pandemic, the rate was 3.9% and 3.2%, respectively. During the same pandemic period, the annual threat rate that ranged from 9.4% to 20.1%, dropped to 7.7%, while the prevalence of harassment, that was between 13.5 and 19.6, fell to 7.2%. HCWs believe that (i) limiting visitor access (ii) a better balance of the demand for services and (iii) a better attitude towards HCWs were the causes of the reduced rate of violence during the pandemic. Recording the violence experienced during health surveillance is an economical, reliable and sustainable risk assessment method.

Pharmacists and pharmacies are highly visible and accessible to the public and have long been regarded as a source for immunization services in the United States. As international travel continues to increase and grow in popularity in this country, there is a pressing need for expanded access to preventative health services including routine and travel vaccinations and medications for prophylaxis or self-treatment of conditions that may be acquired overseas. In the United States, the scope of pharmacy practice continues to expand and incorporate these preventable health services to varying degrees on a state-by-state level. As a result, pharmacists can help to increase access to and awareness of the need for these services to insure that patients remain healthy while traveling abroad and that they do not acquire a travel-related disease while on their trip. For those pharmacists interested in starting a travel health service, considerations should be undertaken that ensures that they have the necessary training, education, and skill set in order to provide this specialty level of care and that their practice setting is optimally designed to facilitate this service. Outcomes from studies that have evaluated pharmacy-based travel health services are positive, which further supports the role of the pharmacist in this setting. Therefore, the purpose of this paper is to highlight United States pharmacy laws and regulations, pharmacist training, travel clinic considerations, and patient care outcomes from pharmacy-based travel health services.

Drought negatively affects the growth and development of barley. To explore the genetic variation in barley under drought stress, ten breeding genotypes were tested using polyethylene glycol-6000 to simulate drought conditions. We observed that drought stress adversely affected germination-related traits across all barley genotypes and this impact varied between genotypes, suggesting genotype-specific drought tolerance. The drought tolerance index was an ideal criterion for selecting drought-tolerant genotypes as it well characterized the gradient responses of barely genotypes to drought stress. Based on this indicator, genotype OB1878-ON-50 is recommended as a significant germplasm resource for breeding programs under lower precipitation conditions due to its superior tolerance to drought stress.

The increasing frequency and severity of phytoplankton blooms worldwide highlight the need for advancements in monitoring technologies. Optical remote sensors, such as Landsat, have proven to be a cost-effective method for large-scale, near-real-time assessments of phytoplankton biomass in lakes. However, its effectiveness is often compromised by atmospheric interferences like clouds, dust, and wildfire smoke, which can obscure the clear-sky conditions essential for accurate remote sensing. While partial atmospheric correction (removing only the Rayleigh effect) is commonly applied to address these interferences, it remains inadequate for mitigating the impact of wildfire smoke. This study investigates the potential of Landsat's coastal/aerosol band (B1) for assessing wildfire smoke interference effects on Chlorophyll-a (Chl-a) retrieval models, which serve as proxies for phytoplankton biomass. We employed cluster analysis of B1 values to create a screening system based on aerosol reflectance, categorizing smoke interference into low, moderate, and high levels. Subsequently, we applied both partial (Rayleigh-corrected reflectance) and full (Landsat 8 Level 2 surface reflectance) atmospheric corrections before developing the Chl-a retrieval models. Excluding high wildfire smoke interference (B1 > 0.07) from the Chl-a calibration dataset significantly enhanced model performance, increasing the r-squared value from approximately 0.55 to 0.80. Moderate smoke interference (0.05 < B1 < 0.07) yielded results comparable to low-interference conditions. Notably, Rayleigh-corrected reflectance, even without additional aerosol band filtering, achieved higher r-squared values for the Chl-a retrieval model than full atmospheric correction. B1 thus proves to be a valuable tool for identifying low smoke-impacted observations, offering an effective method to monitor phytoplankton biomass amid increasing wildfire activity and improving the capacity to monitor aquatic environments in a changing global landscape.

Tomato brown rugose fruit virus (ToBRFV) is a causal agent of severe emergent diseases in Solanaceae hosts with agronomic relevance, such as tomato and pepper. Herein, we analyzed the seed transmission rate and efficacy of different seed disinfection treatments and performed a comparison of molecular biology techniques seeking rapid and sensitive detection in seed lots. We evaluated several total RNA extraction and RT-PCR protocols using a distinct combination of PCR primers to test for the presence of the ToBRFV Mexican strain in tobacco host. Our results showed that the percentage of seed and seedlings transmission was less than 1% and that a 3% sodium hypochlorite solution was effective as a seed disinfection treatment. Finally, the most sensitive molecular method identified for virus detection consisted of a CTAB-Trizol RNA extraction followed by nested PCR using primers reported by Dovas et al. (2004). Additionally, we tested potential natural hosts in selected Cucurbitaceae and Solanaceae species. Our results showed that the ToBRFV Mexican strain is capable of experimentally infecting eggplant (Solanum melongena), tomatillo (Physalis ixocarpa), and tobacco (Nicotiana rustica).

Pyrolyzed organic matter – commonly referred to as biochar – generally has positive effects on plant growth and can enhance early seedling development. Biochar-based seed coatings may thus be beneficial, specifically under adverse soil conditions such as high soil salinity. We evaluated germination and early plant development in radish (Raphinus sativa) seeds coated with conifer-feedstock slow-pyrolysis biochar; following the precedent of prior studies, polyvinyl acetate (PVAc) was used as the binding agent. Biochar-based seed coatings reduced germination rates and radicle extension in Petri dish trials; however, leaching of coated seeds largely eliminated this effect. PVAc applied in solution inhibited seed germination to a similar extent, suggesting that toxicity of PVAc or chemical products derived from it is the main mechanism for germination inhibition; a meta-analysis of published literature also indicates negative effects of biochar-based seed coatings using PVAc. In greenhouse trials the same biochar seed coatings improved aspects of plant growth and physiological status relative to controls, specifically enhancing root development. We conclude that biochar-based seed coatings have promise in promoting early seedling growth, and in combating salinity stress in agronomic and restoration applications. However, our findings contraindicate PVAc use as a binding agent. Further research is needed to test non-phytotoxic, readily biodegradable binding agents and to optimize biochars and seed coating processes for specific applications in agronomy and ecological restoration.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

We analyze a time-delayed SIQR model that considers the transportation-related infections and entry-exit screening. This model aims to determine the measures for preventing and controlling major emergent infectious diseases and the associated costs. We calculate the basic reproduction number (R0), apply the linearization method, and construct an appropriate Lyapunov function to determine the stability of the disease-free equilibrium in the local and global. We collect COVID-19 infection data from two regions in the United States in 2020 for data fitting, obtain a set of optimal parameter values, and show that the model is suitable for simulating the outbreak and spread of emerging infectious diseases. We find that transportation-related infections increase the basic reproduction number, enhancing the impact on disease spread. Entry-exit screening effectively suppress the spread of disease by reducing the basic reproduction number. Furthermore, we investigate the influence of the incubation period on disease and find that a shorter incubation period results in a shorter duration but a larger scale of infection, and the peaks are reduced. We conduct a sensitivity analysis of the R0 and propose three measures to prevent the spread of new infectious diseases based on the most sensitive parameters: wearing masks, implementing urban closures, and administering medication to sick but not yet hospitalized patients promptly. In the case of COVID-19, we use Pontryagin’s minimum principle to get time-varying control measures to control the spread of the outbreak. Optimal control effectively controls the development and deterioration of the disease. Finally, several control measures are compared through cost-effectiveness analysis, and the results show that wearing masks is the most cost-effective measure. Our study provides some practical guidance for controlling the spread of major emerging infectious diseases.

Seedling establishment is often a critical bottleneck to revegetation of mine tailings and similar substrates with a low capacity to retain water and plant nutrients. Biochar and deactivated yeast are potential sustainable, low-cost materials with high nutrient- and water-holding capacity that could be used in this context as seed coatings to aid in seedling establishment on challenging sub-strates. We conducted a greenhouse study to assess the effectiveness of biochar and deactivated yeast, applied alone in a factorial combination, as seed coatings, on the germination, establish-ment, and early growth of white clover (Trifolium repens) and purple prairie clover (Dalea pur-purea). Coated seeds were applied to a mine tailing, a coarse granitic sand, and potting soil mix substates; seedling establishment and growth were monitored over 75 days. Results indicate strong interactive effects of seed coatings with species and substrate. Biochar coatings enhanced seedling establishment of Trifolium, with biochar or biochar plus yeast coatings giving the best results. In some cases, these effects persisted throughout the experiment: biochar coatings resulted in a ~5-fold increase in Trifolium biomass at harvest for plants in the potting soil mix but had neutral effects on sand or tailings. Biochar seed coatings also enhanced Dalea germination in some cases, but benefits did not persist. Our results indicate that biochar-based seed coatings can have lasting effects on plant growth well beyond germination, but also emphasize highly spe-cies-specific responses that highlight the need for further study of broader patterns and mecha-nisms.

The seed habit is the most complex and successful method of sexual reproduction in vascular plants. It represents a remarkable moment in the evolution of plants that afterwards spread on land. In particular, seed size had a pivotal role as for evolutionary success and agronomic trait, especially in the field of crop domestication. Given that crop seeds constitute one of the primary products for consumption, it follows that seed size represents a fundamental determinant of crop yield. This adaptative feature is strictly controlled by genetic traits from both maternal and zygotic tissues, although seed development and growth are also affected by environmental cues. Despite being a highly exploited topic for both basic and applied research, there are still many issues to be elucidated as for developmental biology as well as for agronomic science. This review addresses a number of open questions related to cues that influence seed growth and size, and how developmental processes are influenced by them. Besides, new insights on the genetic-molecular control of this adaptive trait are presented.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono-and polyunsaturated fatty acids balance, as well as sesame's resilience to water stress makes, make it a promising candidate for global agricultural expansion. However, sesame production faces challenges such as low yields, poor response to agricultural inputs, and losses due to capsule dehiscence. To enhance yield, traits like determinate growth, dwarfism, high harvest index, non-shattering capsules, and photoperiod sensitivity are needed. These traits can be achieved through variation or induced mutation breeding. Traditional breeding methods often result in unwanted genetic changes. The CRISPR/Cas9 technology has the potential to suppress detrimental alleles and improve the fatty acid profile by inhibiting polyunsaturated fatty acid biosynthesis. Even though sesame is an orphan crop, it has entered the genomic era, with available sequences assisting molecular breeding efforts. This progress aids in associating single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) with key economic traits, as well as identifying genes related to adaptability, oil production, fatty acid synthesis, and photosynthesis. Additionally, transcriptomic studies can reveal genes involved in abiotic stress responses and adaptation to diverse climates. Quantitative trait loci (QTL) mapping can identify loci linked to crucial traits such as capsule size, seed count per capsule, and capsule number per plant. This paper reviews recent advances in sesame breeding, discusses ongoing challenges, and explores potential strategies for future improvement. Hence, integrating advanced genomic tools and breeding strategies provides promising ways to enhance sesame production to meet global demands.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

Background: The study demonstrates the sustainable synthesis of translucent zinc oxide (ZnO) nanowires using Moringa seed extract, highlighting eco-friendly and sustainable approaches. Methods: Characterization techniques such as X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) confirmed the formation of ZnO nanostructures with diverse morphologies, including nanowires and spherical clusters. Results: The synthesized ZnO nanowires exhibited remarkable photocatalytic activity, achieving over 89% degradation efficiency of methylene blue (MB) under UV light within 80 minutes, demonstrating their potential for wastewater treatment applications. Conclusions: The research findings support Sustainable Development Goals (SDGs) related to clean water, climate action, and life below water and on land, highlighting the role of eco-friendly nanostructures in environmental remediation. The dual advantage of Moringa seed extract, providing both a sustainable synthesis route and health benefits due to its rich content of vitamins and phytochemicals, underscores the potential of integrating natural resources in nanotechnology for environmental and health applications.

Abstract. This paper proposes a Second Order Terminal Sliding Mode (2TSM) approach to the trajectory tracking of Differential Drive Mobile Robot (DDMR). Within this cascaded control scheme, the 2TSM dynamic controller, at the inner most loop, tracks the robot’s velocity quantities; while a kinematic controller, at the outer most loop, regulates the robot’s positions. In this manner, chattering is greatly attenuated and finite time convergence is guaranteed by the second order TSM manifold which involves higher order derivatives of the state variables, resulting in inherently robust as well as fast and better tracking precision. The simulation results demonstrate the merit of the proposed control methods.

Abstract Bacteria and fungi are both used in biological seed treatments. While all have potential uses, some organisms are more widely and successfully used than others. Shelf life is an important consideration. For this reason, organisms that lack cell walls are more difficult to use than ones with long-lasting spores. Bacillus and Trichoderma are both widely effective, have good shelf life, and are frequently used. However, Rhizobiacae lack cell walls, which is a limitation; they are widely used because their symbiosis with legumes facilitates nitrogen fixation which is an important factor that provides economic, agricultural and environmental sustainability. For all organisms, proper formulation is critical for success; this is especially true for Rhizobiacae and other gram-negative bacteria. There are several specialized processes to deliver microbial agents or to enhance their biological activity, such as solid matrix priming and hydroseeding. Biorational chemicals derived from microorganisms are also frequently used. Both living organisms and biorationals provide benefits to plant agriculture. They can control diseases and increase resistance to abiotic stresses such as drought, temperature, salt, and flooding. They also can enhance mineral nutrition and photosynthesis. For these applications, the most effective ones colonize roots internally and provide season-long benefits. These endophytes induce systemic changes in plants’ gene expression and encoding of proteins.

The traditional receiver employs scalar tracking loops, resulting in degraded navigation performance in weak signal and high dynamic scenarios. An innovative design of a vector tracking receiver based on nonlinear Kalman filter (KF) tracking loops is proposed in this paper, which combines the strengths of both vector tracking and KF tracking loops. Firstly, a comprehensive description of the vector tracking receiver model is presented, and unscented Kalman filter (UKF) is applied to nonlinear tracking loop. Secondly, to enhance the stability and robustness of the KF tracking loop, we introduce square root filtering and an adaptive mechanism. The tracking loop based on square root UKF (SRUKF) can dynamically adjust its filtering parameters based on signal noise and feedback Doppler error. Finally, the proposed method is implemented on a software-defined receiver (SDR), and the field vehicle experiment demonstrates the superiority of this method over other receivers in complex dynamic environments.

Seed germination is the most sensitive stage to abiotic stress, including salt stress (SS). SS affects plant growth and performance through ion toxicity, decreases seed germination percentage, and increases the germination time. Several priming treatments were used to enhance germination under SS. The objectives of this study are to 1) identify priming treatments to shorten the emergence period; 2) evaluate priming treatments against the SS; 3) induce synchronized seed germination. Salt-sensitive “Burpee bibb’ lettuce seeds were treated with 0.05% Potassium nitrate, 3 mM Gibberellic acid, and distilled water (HP). All the primed and non-primed seeds were subjected to 100 mM NaCl or 0 mM NaCl. The 7-day experiment arranged in a complete randomized block design with four replications was conducted in a growth chamber maintained with 16/8 h photoperiod (light/dark), 60% relative humidity, and day/night temperature of 22/18 °C. The result indicated that HP seeds were better synchronized under SS. Similarly, FM and DM of cotyledon, hypocotyl, and radicle were highest in HP lettuce regardless of SS. Electrolyte leakage was the lowest in the HP lettuce, while other priming methods under SS increased membrane permeability leading to osmotic stress and tissue damage. Overall, the HP can be a suitable priming method to synchronize germination and increase FM and DM by creating the least osmotic stress and ion toxicity in lettuce under SS.

Rice prolamins are categorized into three groups by molecular size (10, 13, or 16 kDa), while the 13 kDa prolamins are assigned to four subgroups (Pro13a-I, Pro13a-II, Pro13b-I, and Pro13b-II) based on cysteine residue content. Here, we generated four knockout strains of rice using CRISPR-Cas9, each of which demonstrated selectively reduced expression of specific subgroups of the 13 kDa prolamins. These four mutant rice lines also demonstrated compensatory expression of glutelins and non-targeted prolamins, which resulted in low grain weight, altered starch content and atypically-shaped starch granules and protein bodies. Transcriptome analysis identified 746 transcripts that were differentially expressed in the mutant rice lines during development. These transcripts played roles primarily in RNA processing, protein synthesis, stress response, and transport. After selective suppression/knockout of genes in the Pro13a-I subgroup, compensatory upregulation of genes in the Pro13a-II and Pro13b-I/II subgroups was observed. Compensatory expression of 9 ER stress and 17 transcription factor genes was also observed in mutant rice in which expression of 13 kDa prolamin genes was suppressed. Our results provide valuable insight into the regulatory mechanisms underlying rice seed development and the specific roles played by 13 kDa rice prolamins and their target genes.

This study investigates the possibility of using machine learning models created in DeepLabCut and Create ML to automate aspects of behavioral coding and aid in behavioral analysis. Two models with different capabilities and complexities were constructed and compared to a manually observed control period. The accuracy of the models was assessed before being applied to 7 nights of footage of the nocturnal behavior of two African elephants (Loxodonta africana). The resulting data was used to draw conclusions regarding behavioral differences between the two elephants and between individually observed nights, thus proving that such models can aid researchers in be-havioral analysis. The models were capable of tracking simple behaviors with high accuracy, but had certain limitations regarding detection of complex behaviors, such as the stereotyped behavior sway, and displayed confusion when deciding between visually similar behaviors. Further expansion of such models may be desired to create a more capable aid with the possibility of automating behavioral coding.

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins and carbohydrates in their seeds, distinctly dominate modern agronomic practice. Indeed, these plants play an essential role in the food industry and fuel production. Therefore, the seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, not only seed development and germination, but also age- and stress-related alterations in seed vigor, longevity, nutritional value and safety can be addressed by a broad panel of analytical, biochemical and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes, accompanying plant development, senescence and response to biotic or environmental stress. Among individual methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. Here we discuss the main methodological approaches employed by seed proteomics in the context of physiological changes related to seed development, ageing and response to environmental stress.

This paper proposes a novel hybrid control strategy for quadrotor unmanned aerial vehicles (UAVs) based on bio-inspired neural dynamics. This strategy addresses the velocity jump issue prevalent in traditional backstepping control and the control signal chattering problem common in traditional sliding mode control. The control system comprises an outer-loop bio-inspired backstepping controller and an inner-loop bio-inspired sliding mode controller, ensuring smooth trajectory tracking even in the presence of external disturbances. The stability of the quadrotor UAV control system is rigorously analyzed using Lyapunov stability theory. Extensive comparative simulation experiments are conducted to assess the robustness and effectiveness of the control system. Results demonstrate superior trajectory tracking performance of the proposed control system compared to other control systems for quadrotor UAVs.

To elucidate mesenchymal stromal cells (MSC)-tumor intricate and ambiguous interactions, the reliable cell labeling and tracking techniques are imperative. Traditional methods of cell labelling have limitations mostly relevant to need for genetic modification what demands the exploration for alternative strategies. Here, we propose using fluorescent photoconvertible microcapsules containing Rhodamine B (RhB) to study mMSC migration in brain tumors. These 3 μm sized microcapsules are readily internalised by cells and undergo photoconversion under 561 nm laser exposure with fluorescence blue shift on demand. Optimal photoconversion was achieved with a laser irradiation duration of 0.4 ms, which provide a maximal brightness of photoconverted label without an excessive laser exposure on cells. Capsules modified with polyallylamine hydrochloride demonstrated the best potential for intracellular uptake without significantly affecting cell viability, motility, or proliferation. The optimal ratio of 20 capsules per mMSC was determined for labeling. Moreover, migration of individual mMSCs within 2D and 3D glioblastoma cell (EPNT-5) colonies over 2 days and in vivo tumor settings over 7 days was tracked. Our study unveils a robust platform for investigating MSC-tumor dynamics, offering insights into therapeutic strategies. Photoconvertible microcapsules could also become an indispensable tool for studying complex fundamental processes of cell-cell interactions for a wide range of problems in biology and medicine.

Intraoperative load sensors have been developed with the aim of balancing the soft tissue in the knee during Total Knee Replacements (TKRs). Literature has shown success in soft tissue bal-ancing however, concerns regarding the accuracy of these sensors remain. For this reason, pre-vious research has attempted to create robust sensors for intraoperative use. The design of the sensor in this research has aimed to address the concerns outlined in the literature to create a new and novel smart-sensor for soft-tissue balancing. This new intraoperative load sensor included design features to increase accuracy while artificial intelligence allowed for comprehensive sensing across the entirety of the sensor, providing unparalleled insight during the operation. Notably, the sensor was designed to withstand loads of at least 450 N, ensuring robust perfor-mance of the sensor. To optimize the design process while minimizing cost, Finite Element Analysis was employed. This approach ensured the design features fulfilled their function while maintaining structural integrity to withstand loads. Moreover, the novelty of using training data from simulated data will reduce the iterative process of the labor-intensive collection of training data for the artificial intelligence while reducing human error associated with it. Results from the evaluation demonstrated the ability of this design to successfully bridge the current gap in the market by fulfilling all essential design criteria established within the literature. This innovative smart-sensing tool will in turn enhance patient outcomes and alleviate financial burdens to pa-tients and the healthcare systems by reducing the need for early revision surgeries associated with improper joint tension.

With the development of Global Navigation Satellite Systems (GNSS), the quality and anti-jamming capability of satellite navigation signals are crucial. Binary Offset Carrier (BOC) modulation faces issues of false locking due to multi-peak ambiguity in its autocorrelation function, limiting its application. This paper examines FH-BOC modulation, which integrates BOC with frequency hopping technology, significantly improving anti-jamming, anti-multipath performance, and spectral efficiency. To meet the high dynamic tracking demands of FH-BOC signals, this study explores three types of carrier tracking loops: the traditional second-order frequency-locked loop assisted a third-order phase-locked loop, a linear Kalman filter-based tracking algorithm, and an adaptive Kalman filter-based tracking algorithm. A composite code tracking loop is also proposed. Simulations show that the adaptive Kalman filter algorithm achieves high-precision carrier tracking in dynamic environments and quickly converges during transitions. The composite code tracking loop, aided by the carrier loop, ensures precise synchronization of pseudocode and frequency-hopping subcarrier phases, demonstrating the superior performance of FH-BOC modulation in dynamic environments.

The paper addresses the challenging issue of trajectory tracking for uncertain quadrotor UAVs, particularly under the constraints of input saturation and external disturbances. It introduces adaptive laws for managing uncertainties in mass and inertia moments without requiring prior knowledge, ensuring effective control even with varying system parameters. To counteract the effects of input saturation, the study incorporates an auxiliary system designed to compensate for these limitations. Additionally, a disturbance observer(DO) is utilized to manage and mitigate the impact of time-varying external disturbances. The proposed control strategy integrates a sliding mode adaptive control approach with an inner-outer loop structure, enhancing robustness and adaptability. Numerical simulations demonstrate the effectiveness of the designed control strategy.

The next generation network requires not only ultra high data rate, global coverage and connectivity, but also reducing network deployment costs and energy consumption. The emergence of reconfigurable intelligent surface (RIS) technology provides an effective way to improve efficiency and reduce cost, while the passive elements bring new challenges of channel estimation (CE) and beam tracking. For a RIS-aided multiple-input and single-output (MISO) system, in this paper, to achieve the channel state information (CSI), we propose a principle component analysis (PCA) based staged channel estimation method. Based on the estimated channel, we propose a deep learning (DL) based beam tracking scheme to realize low-complexity RIS reflection coefficient design, which effectively improves the signal-to-noise ratio (SNR) at the user side. Simulation results verify our proposed channel estimation scheme based on PCA and beam tracking scheme based on DNN for the semi-active RIS-aided MISO systems can obtain approximate performances with much lower computational complexity.

Organic fertilizer application in agricultural land is known to improve soil microbial processes, fertility, and yield. In particular, stable changes in soil chemical composition through multi-year fertilization of organic fertilizers are thought to cause changes in the microbial community. Here, the effects of oil cake amendments (OC) on soil bacterial diversity, community profile and enzyme activity were evaluated and compared to those amended with chemical fertilizer (NPK). The comparison of diversity indices between OC and NPK amended soils shows that application of oil cake has increased microbial diversity potentially with an increase in the number of different microbial groups. The ordination plot distinguished and clustered both treatments showing differential effects of soils chemical factors on the microbial communities of each treatment. Proteobacteria, Verrucomicrobia and Bacteriodetes were significantly abundant in OC amended soil than in the NPK received soil, indicating alterations in community structure, composition, and diversity con-current to the changes in pH, Ca and Mg contents of the soil. These shifts in bacterial community structure and composition could also be observed from the phylum to the genus level in both NPK and OC amended soils partially explained by differences in soil chemical factors. The OC soil compared to the NPK amended soil also contain significantly higher abundance of predicted genes corresponding to enzymes related to biogeochemical cycling, decomposition and plant growth promotion. Collectively, these results support the use of an unconventional organic fertilizer positively altering bacterial populations in jujube orchards. The application of oil cake-based organic fertilizer improved microbial diversity and enhanced potential ecosystem functions related to bio-geochemical cycles, mineralization and plant growth promotion.

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine Operation and Maintenance (O&M). Incorporating machine learning in developing condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Base Density for the Support Vector Machine (BDSVM) and the evolutionary Fourier spectra of vibrations. This method allows smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the BDSVM to timely determine the magnitude, frequency, and place of the failure occurring in wind turbine drive.

Aflatoxin contamination (AC) increases as the severity of drought stress increase in peanut. Identifying drought-tolerant (DT) genotypes with resistance to Aspergillus. flavus in semi-arid tropics may aid in development of peanuts that minimizing aflatoxin contamination. The goal is to identify the DT genotypes and resistant to aflatoxin contamination. The experiments curried out at ICRISAT Sahelian Center on fifty-five genotypes assessed in adjacent intermittent water-stressed (WS) from 60th day after sowing to maturity and well-watered (WW) conditions in a randomized complete block design. The yields and components, incidence of A. flavus colonisation, aflatoxin contamination and the seed coat total pthe olyphenol (SCTPP) were estimated. Water deficit reduced pod yield, seed yield, and haulm yield up to 19.49%, 27.24% and 22.07% respectively and increased the immature pods plant-1, (IMPN) and aflatoxin contamination up to 67.16% and 54.95%. The genotypes ICG 2106, ICG 311, ICG 4684, ICG 4543, and ICG 1415 maintained high yield under WS, less of IMPN and the lowest AC variation between WW and WS. The drought tolerant genotypes showed the relationship with aflatoxin resistance and SCTPP (r2=0.80; r2=0.82) under WW and WS. These findings can be used to select the genotype that combine drought tolerance and minimizing aflatoxin contamination.

Underwater natural gas pipelines constitute critical infrastructure for energy transportation. Any damage or leakage in these pipelines poses serious security risks, directly threatening marine and lake ecosystems and potentially causing operational issues and economic losses in the energy supply chain. Due to the difficulty in detecting deterioration over time and regularly inspecting these submerged pipelines by divers, the use of unmanned underwater vehicles (UUVs) becomes crucial in this field. In this study, an underwater pipeline tracking experiment was carried out by providing autonomous features to a remote-controlled unmanned underwater vehicle. During the tracking of the underwater pipeline, damages were identified, and the locations of these damages were determined. The navigation information of the underwater vehicle, including orientation in the x, y, z axes (roll, pitch, yaw) from a gyroscope integrated with magnetic compass, speed and position information in the three axes from an accelerometer, and the distance to the water surface from a pressure sensor, was integrated into the vehicle. Pre-tests determined the necessary pulse width modulation values for the thrusters of the vehicle, enabling autonomous operation by providing these values as input to the thruster motors. In this study, the vehicle moves in 3D was achived by the vertical thruster of the vehicle was activated to maintain a specific depth, and applying equal force to the vehicle’s right and left thrusters forward movement, while differential force induced deviation angles. In pool experiments, the unmanned underwater vehicle autonomously tracked the pipeline as intended, identifying damages on the pipeline using images captured by the vehicle's camera. The images for damage assessment were processed using a convolution neural network (CNN) algorithm, which is a deep learning method. The position of the damage relative to the vehicle was estimated from the pixel dimensions of the identified damage. The location of the damage relative to its starting point was obtained by combining these two positional pieces of information from the vehicle's navigation system. The all study was performed within the Python environment.

Soybean is the primary oilseed crop in the United States, with significant industrial value. Understanding the molecular mechanisms of heat stress tolerance in soybean is critical for developing stress-resistant cultivars. Current knowledge about the role of fatty acid desaturases (FADs) in modulating membrane fluidity under abiotic stress prompted this investigation into the impact of mutations in the FAD genes on seed germination from heat-stressed plants. In soybean, exposure to heat stress during anthesis is known to significantly reduce seed germination. In silico expression analysis indicated high levels of expression of the soybean FAD2 and FAD3 genes in leaves. Therefore, a detailed expression analysis of these genes was conducted using qRT-PCR from leaf tissue. Generally, downregulation of these genes was observed in the mutants; however, two genes, FAD3A and FAD2-3, showed a more than 2-fold increase in expression in six out of ten mutants under heat stress. This upregulation was particularly pronounced (7-fold) in mutant S17CR-170. Correlation analysis revealed a positive correlation (0.5) between the expression level of FAD3A, FAD3B, FAD3C, and FAD2-3 and the decline in germination from heat-stressed plants. This suggests these FAD genes may act as negative regulators of germination under heat stress conditions.

A new quinazolinone alkaloid, named peniquinazolinone A (1), as well as eleven known com-pounds, 2-(2-hydroxy-3-phenylpropionamido)-N-methylbenzamide (2), viridicatin (3), viridicatol (4), (±)-cyclopeptin (5a/5b), dehydrocyclopeptin (6), cyclopenin (7), cyclopenol (8), methyl-indole-3-carboxylate (9), 2,5-dihydroxyphenyl acetate (10), methyl m-hydroxyphenylacetate (11), conidiogenone B (12), was isolated from the endophytic Penicillium sp. HJT-A-6. The chemical structures of all compounds were elucidated by comprehensive spectroscopic analysis, including 1D, 2D NMR, and HRESIMS. The absolute configuration at C-13 of peniquinazolinone A (1) was established by applying the modified Mosher’s method. Compounds 2, 3, and 7 exhibited an op-timal promoting effect on the seed germination of Rhodiola tibetica at a concentration of 0.01 mg/mL, while the optimal concentration for compounds 4 and 9 to promote Rhodiola tibetica seed germination was 0.001 mg/mL. Compound 12 showed optimal seed-germination-promoting activity at a concentration of 0.1 mg/mL. Compared with the positive drug 6-benzyladenine (6-BA), compounds 2, 3, 4, 7, 9, and 12 could extend the seed-germination period of Rhodiola tibetica up to the 11th day.

Viral variant analysis is a bedrock of the disease surveillance. When combined with temporospatial analysis variant analysis can further the knowledge of disease spread in a study area. This paper suggests a method to perform the analysis in an operational setting which will allow for real-time surveillance of viral variants and allow local public health professionals to rapidly respond to changes in the evolution of the disease. This method includes three main subprocesses: preprocessing, analysis, and rendering. This method can be performed across multiple software platforms. A use case is given in which it was found that this method helped a hospital system understand the spread of SARS-CoV-2 in Northeast, Ohio.

Plant community assembly is the central issue in community ecology. As plant traits differ in different life history stages, the form, intensity and mechanism of interspecific interactions may change with the ontogenetic process of plants. However, our understanding of interspecific interaction mechanisms during germination is still limited. Here, we conducted a laboratory germination experiment using 5 dominant species in Chongming Dongtan (Spartina alterniflora, Scirpus mariqueter, Phragmites australis, Suaeda glauca and Tripolium vulgare) to assess their germination performance in control (monoculture), allelopathy and mixture treatments. The results indicated that seeds could affect germination performance of neighbours through both allelopathy and microenvironment modification. Salinity of the solution in petri dishes after germination decreased in all treatments, and was negatively correlated with the number of total germinated seeds. Seed leachate of invasive Spartina alterniflora inhibited the germination of native Scirpus mariqueter and Phragmites australis, but not the two halophytes Suaeda glauca and Tripolium vulgare. The salt absorption by Spartina alterniflora seeds had the opposite effects compared with that of its seed leachate. On the other hand, seed leachate of native species promoted the germination of invasive Spartina alterniflora. The effect of microenvironment modification of Scirpus mariqueter and Phragmites australis was positive, whereas that of Suaeda glauca and Tripolium vulgare was neutral or negative. Considering seed-to-seed interactions is an important perspective to understand the underlying mechanisms of community dynamics, species diversity maintenance and invasion of alien species, and can improve the effectiveness in the management of invaded coastal wetlands.

Automated lying-posture tracking is important in preventing bed-related disorders such as pressure injuries, sleep apnea, and lower-back pain. Prior research studied in-bed lying posture tracking using sensors of different modalities (e.g., accelerometer and pressure sensors). However, there remain significant gaps in research about how to design efficient in-bed lying posture tracking systems. These gaps can be articulated through several research questions as follows. First, can we design a single-sensor, pervasive, and inexpensive system that can accurately detect lying postures? Second, what computational models are most effective in the accurate detection of lying postures? Finally, what physical configuration of the sensor system is most effective for lying posture tracking? To answer these important research questions, in this article, we propose a comprehensive approach to design a sensor system that uses a single accelerometer along with machine learning algorithms for in-bed lying posture classification. We design two categories of machine learning algorithms based on deep learning and traditional classification with handcrafted features to detect lying postures. We also investigate what wearing sites are most effective in accurate detection of lying postures. We extensively evaluate the performance of the proposed algorithms on nine different body locations and four human lying postures using two datasets. Our results show that a system with a single accelerometer can be used with either deep learning or traditional classifiers to accurately detect lying postures. The best models in our approach achieve an F-Score that ranges from 95.2% to 97.8% with a coefficient of variation from 0.03 to 0.05. The results also identify the thighs and chest as the most salient body sites for lying posture tracking. Our findings in this article suggest that because accelerometers are ubiquitous and inexpensive sensors, they can be a viable source of information for pervasive monitoring of in-bed postures.

In a dynamic production processes, mechanical degradation poses a significant challenge, impacting product quality and process efficiency. This paper explores a novel approach for monitoring degradation in the context of viscose fiber production, a highly dynamic manufacturing process. Using causal discovery techniques, our method allows domain experts to incorporate background knowledge into the creation of causal graphs. Further, it enhances the interpretability and increases the ability to identify potential problems via changes in causal relations over time. The case study employs a comprehensive analysis of the viscose fiber production process within a prominent textile industry, emphasizing the advantages of causal discovery for monitoring degradation. The results are compared with state-of-the-art methods, which are not considered to be interpretable, specifically LSTM-based autoencoders, showcasing the alignment and validation of our approach. This paper provides valuable information on degradation monitoring strategies, demonstrating the efficacy of causal discovery in dynamic manufacturing environments. The findings contribute to the evolving landscape of process optimization and quality control.

Worldwide the severity of abiotic stress like heat, drought, salinity, cold, waterlogging, etc. are being increased because of global warming. Wheat crops must adapt to harsh environments through physiological, molecular, and genetic manipulation. Because of abiotic stress, reactive oxygen species (ROS) and reactive nitrogen species (RNS) produced in wheat plants break down DNA and RNA bases, protein, lipid, and other macro- and micromolecules, resulting in stunted growth and yield decline. Abiotic stress also induces the crop's molecular functions, physiological, biological, and cellular processes, and their compositions. Different stressors like high light intensity, heat, drought, and salinity also impair photosynthesis damaging various pigments. Antioxidant enzymes, such as catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), and ascorbate peroxidase (APX), etc. synthesized in harsh environments can ameliorate ROS/RNS produced in oxidative stress. Under abiotic stress, heat shock proteins (HSPs) heat shock transcription factors (HSFs) in heat stress, and dehydration-responsive element binding proteins (DREBs) in drought stress are activated to synthesize proteins to mitigate the deleterious effects of those stressors. Na⁺ exclusive genes (NAX1, NAX2) and Na⁺/H⁺ (K⁺) antiporter genes (NHX1, NHX2) hinder those ions from uptake into leaf sheaths and blades of wheat resulting in the declination of salinity in plants. Exogenous hormones like gibberellic acid, salicylic acid, and melatonin, etc., and osmoprotectants like proline, and gene manipulation in plants through genetic engineering are being employed to mitigate the toxic effects of abiotic stress on plants, as portrayed in many literatures. The review depicts how abiotic stress affects phenotypic, physiological, and molecular structures and functions of wheat crops, and their mitigation strategies to lessen their noxious effects on wheat.

Aiming at the APF algorithm in the collision-free path planning and LQR algorithm tracking process, there are problems such as unreachable target points, local optimization, low safety coefficient of autonomous lane change collision avoidance tracking control and poor stability, this paper proposes an optimized APF method, which solves the defects of the traditional artificial potential field method by adding the distance adjustment factor, the safety distance protection model and the sub-target virtual potential field, and at the same time generates the autonomous driving car collision-free path. The path tracking control system is designed based on feed-forward control and DLQR controller, in which the vehicle dynamics state space model is used as the basis, the model is linearized and discretized, and the corresponding constraint variables are set to minimize the control command objective cost function under the constraints, and the objective of the DLQR controller.The objective is to accurately determine the steering angle in order to achieve path tracking and eliminate the lateral error between the reference path and the actual path caused by external interference.Finally, the simulink model and CarSim parameter configuration joint simulation platform are built, and different obstacle scenarios and different speeds are selected for collision-free path planning and tracking motion simulation research and analysis, which verifies the accuracy and practicability of the algorithm, and shows more obvious advantages in obstacle avoidance ability, path smoothing degree, and collision avoidance safety stability. The ideas proposed in this paper are expected to be further extended and popularized to actual path planning problems, which has important practical significance and engineering value.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Lentil (Lens culinaris Medik.) is an essential legume crop providing healthy and nutritious food for people in low- to middle-income countries, worldwide. Lentil roots support symbiotic interactions with soil rhizobia species fostering nitrogen fixation; however, assemblage and diversity of the complete microbial rhizosphere community and the effect of seed genotype and origin remains largely unexplored. In this study we examined with metagenomic analysis, the effects of seed origin on the rhizosphere’s communities in samples of the famous Greek lentil landrace Eglouvis derived from different local farmers and farming systems including a Gene Bank sample, in comparison to a commercial variety. The landrace exhibited higher rhizosphere microbiome diversity compared to the commercial variety for all indexes. A core microbiome comprised of 158 taxa was present in all samples, while higher number of unique bacterial taxa was recorded in the landrace samples compared to the commercial cultivar. Noteworthy, landrace samples originated from organic farming had more than double unique taxa compared to conventional counterparts. The study revealed higher diversity of N2 fixers and archaea, Crenarchaeota and Thaumarchaeota, in landrace samples and particularly in those derived from organic farming, underpinning the distinct recruiting efficiency of beneficial soil microbes by the landrace.

The DOF (DNA binding with one finger) family of plant-specific transcription factors (TF) was first identified in maize in 1995. Since then, DOF proteins have been shown to be present in the whole plant kingdom including the unicellular alga Chlamydomonas reinhardtii. The DOF TF family is characterised by a highly conserved DNA binding domain (DOF domain), consisting of a CX2C-X21-CX2C motif which is able to form a zinc finger structure. Early in the study of DOF proteins it became clear their relevance for seed biology. Indeed, the Prolamine Binding Factor (PBF), one of the first DOF proteins characterised, controls the endosperm-specific expression of the zein genes in maize. Subsequently, several DOF proteins from both monocots and dicots have been shown to be primarily involved in seed development, dormancy and germination, as well as in seedling development and other light-mediated processes. In the last two decades the molecular network underlying these processes have been outlined, and the main molecular players and their interactions have been identified. In this review, we will focus on the DOF TFs involved in these molecular networs, and on their interaction with other proteins.

This work is aimed at promoting a healthier means of livelihood by investigating insignificant areas of pollution. In this work, soy candles produced from soybeans were proven as healthier alternatives to paraffin candles. Soxhlet extraction method was used with hexane as solvent. The extracted oil were then solidified. The wax was moulded into candle and tests were carried out to prove its claims as a safer alternative to paraffin wax. The results supported this claims that soy candles is more economical and produced lesser soot than the paraffin candles.

In Thailand, parking time violation is a major problem, especially for mini-marts. At present the task of detecting parking time violation is mainly conducted manually using Closed-Circuit Television (CCTV). This method requires additional human labour to track incoming and outgoing vehicles. Therefore, low cost time violation tracking is needed. To the best of our knowledge, there has not been any research for parking violation detection and tracking conducted for parking time limits. This paper introduces a novel parking time violation detection algorithm using the Yolov8 and DeepSORT tracking algorithms to track vehicles in consecutive frames. The presented parking violation tracking algorithm can provide a guideline for research in parking time violation detection.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

In recent years many different deep neural networks were developed, but due to a large number of layers in deep networks, their training requires a long time and a large number of datasets. Today is popular to use trained deep neural networks for various tasks, even for simple ones in which such deep networks are not required. The well-known deep networks such as YoloV3, SSD, etc. are intended for tracking and monitoring various objects, therefore their weights are heavy and the overall accuracy for a specific task is low. Eye-tracking tasks need to detect only one object - an iris in a given area. Therefore, it is logical to use a neural network only for this task. But the problem is the lack of suitable datasets for training the model. In the manuscript, we presented a dataset that is suitable for training custom models of convolutional neural networks for eye-tracking tasks. Using data set data, each user can independently pre-train the convolutional neural network models for eye-tracking tasks. This dataset contains annotated 10,000 eye images in an extension of 416 by 416 pixels. The table with annotation information shows the coordinates and radius of the eye for each image. This manuscript can be considered as a guide for the preparation of datasets for eye-tracking devices.

Chilling injury (CI), which causes seed browning in pepper, may arise following long-term cold storage, and is a major cause of postharvest losses. To explore potential strategies of minimizing the associated postharvest losses, the present study investigated the optimal pepper harvest time that could reduce levels of seed browning, in addition to the relationship between fruit maturity and seed browning. Fruit harvested 15 days after flowering (DAF) were sensitive to cold storage at 4°C and exhibited 100% seed browning (CI index, 4.0); in contrast, the seed browning rate of fruit harvested 35 DAF was 10% (CI index, 0.4) within 7 d of cold storage. Seed antioxidant activity was higher in seeds harvested at early stages (15 DAF to 20 DAF) than in seeds harvested at later stages (40 DAF to 50 DAF) at the beginning of storage. Pericarps of fruit harvested at 50 DAF exhibited the highest antioxidant activity. Lipoxygenase, catalase, and peroxidase activity, and the expression levels of cell wall-related genes, pectin methylesterase-like protein, and endo-β-1,4-glucanase were higher in seeds of immature fruit harvested 15 DAF than in seeds of mature fruit harvested 35 DAF. The endosperm separated from the seed coat in fruit harvested 35 DAF and the seeds did not brown under low-temperature storage. The lack of seed browning observed in mature fruit under low-temperature storage could be attributed to physical protection provided by the seed coat rather than cold stress resistance conferred by antioxidants.

Despite their prevalence in almost all publicly orientated conservation settings, sign design receives limited attention in the research literature. We used a remote eye-tracking device to test how visitors read educational signs, maps, and species signage. Three designs, plus a plain-text control sign, were tested for each sign type. Sign content was based on Brackenhurst Botanic Garden, Kenya and included four different information texts (156-256 words long) and a species information text (64 words long). Four presentations of extinction threat-status were also tested as were depictions of trail routes on maps. Data were collected from 51 participants at six cultural venues across Nottingham, UK. Signs positioned centre-left of an exhibit were read first. Information on the left-hand side of signs was read first and dwelled upon the longest. Signs with a single large image and a single block of text were generally preferred, and images were most frequently recalled. Extinction threat-status was most frequently viewed and best recalled from green-red thermometer diagrams and least from the IUCN red-list diagram. Map routes were clearest when presented as coloured solid lines. This study indicates the potential benefit of eye-tracking research for measuring sign use and assisting in sign design.

Lentil (Lens culinaris Medik) is an annual herb that belongs to family Fabaceae, it is one of the most ancient food crops that has been grown in the world, and originated from southwestern Asia as early as 7000 BC. In Spain lentil acreage raised 42,200 ha in 2022, two authonomous regions Castilla-León and Castilla-La Mancha are traditionally the large producers. Lentils have the capacity to fix atmospheric N2 in symbiosis with rhizobia and, additionally it is considered moderately tolerant to drought which in turn makes this pulse a low water and carbon fingerprint crop. The aim of this study was to assess the symbiotic responsiveness to rhizobia strains of several lentil accessions from the Spanish germplasm bank, to determine the nutritional value and mineral seed composition and, to evaluate the agronomic performance of six selected accessions in two regions under rainfed conditions and different management systems. The protein content of all genotypes was higher than 25%, with two outstanding seeds from accessions: BGE025596 and BGE026702 which account for >30% of protein and <2% of fat. Accessions BGE016362 and, BGE026702 had an exceptional Fe content, > 1 g/100 g of seed flour. The agronomic performance varied depending upon the cropping región.

Variable and sometimes contrasting effects of using artificial rhizobium inocula to increase grain legume performance have been reported. The objectives of this systematic review and meta-analysis were therefore to (i) estimate the overall effect of rhizobium inocula on grain yield and protein content and (ii) identify potential confounding factors that explain the observed variation. A web of Science database literature search was carried out in 2016. Data from all field experiments, greenhouse and pot experiments that compared grain yields and protein contents in Rhizobium/Bradyrhizobium-inoculated with non-inoculated control crops were extracted and analyzed using previously described unweighted and weighted meta-analysis protocols. GRADE assessments of the strength of evidence of results from the weighted meta-analyses were carried which included an assessment of the risk of publication bias. Results: For unweighted meta-analyses we identified eligible data in 236 and 36 studies for grain yield and protein content respectively. For weighted meta-analyses we identified eligible data in 92 and 8 studies for grain yield and protein content respectively. Rhizobium inoculation was found to (i) significantly increase grain yield in both the unweighted (mean percent difference: 41%, 95%CI 36,46, p&lt;0.0001) and weighted meta-analysis (Standardized mean difference: 1.56, 95%CI 1.26,1.87, p&lt;0.0001) and (ii) significantly increase protein content in the unweighted meta-analysis (mean percent difference: 11%, 95%CI 5,18, p&lt;0.0001), but not the weighed meta-analyses which only detected a trend (0.1&gt;p&gt;0.05) towards higher protein content in inoculated grain legume crops. Multi-level model-based weighted meta-analyses suggest that the (i) type of experiment, (ii) type of fertilizer used in experiments, (iii) grain legume type/species and (iv) the country in which experiments were carried out, were confounding factors. The main limitation of the evidence is that a large number of publications did not report measures of variation and could therefore not be included in the more scientifically sound weighted meta-analyses. However based on the large evidence-base available for grain yield it can be concluded that overall Bradyrhizobium/Rhizobium seed inoculation results can increase grain yield by ~40% compared with non-inoculated grain legume crops.

The objective of this study was to analyze the mental workload using EEG and eye tracking data and classify it using machine learning algorithms. The machine learning model was developed based on the simultaneous recording of eye tracking and EEG measurements during the experimental process. The experiments involved 15 university students, consisting of 7 women and 8 men. Throughout the experiments, the researchers utilized the n-back memory task and the NASA-Task Load Index (TLX) subjective rating scale to assess various levels of mental workload. The findings revealed that as the task difficulty increased, there was an increase in the diameter of both the right and left pupils, the number of fixations, the number and duration of saccades, and the number and duration of blinks. Conversely, variables related to fixation duration decreased. The EEG results indicated that theta power in the prefrontal, frontal, and front central regions increased with task difficulty. Additionally, alpha power increased in the frontal regions but decreased in the temporal, parietal, and occipital regions as the task became more challenging. Furthermore, low beta power significantly decreased in almost all brain regions as the task difficulty increased. In terms of the four-class classification problem, the mental workload level can be predicted with an accuracy rate of 76.59% using 34 selected features. This study has made a significant contribution to the literature by presenting a four-class mental workload estimation model that utilizes different machine learning algorithms.

Basic features of seed dormancy are illustrated. The seed overall regulatory network governs seed metabolism and development, and it is coordinated by plant hormones. A functional model focused on abscisic acid (ABA), the foremost plant hormone in dormancy, is used as a framework to critically discuss the literature. Gibberellins (GAs) have a main role in germination, and the ABA – GAs balance is a typical feature of the seed state: ABA dominates during dormancy and GAs prevail through germination. Thus, the literature converges toward envisaging the development switch between dormancy and germination as represented by the ABA/GAs ratio. The ABA – GAs antagonism is based on mutual inhibition, a feature of the regulatory network architecture that characterizes development trajectories based on a regulatory circuit with a bistable switch. Properties of such kind of regulatory architecture are introduced step by step, and it is shown that seed development – towards either dormancy or germination – is more properly represented by a tristable regulatory circuit, whose intermediate metastable states ultimately take one or the other development trajectory. Although the ABA/GAs ratio can conveniently represent the state of the seed overall regulatory network along the seed development trajectory, specific (unknown) dormancy factors are required to determine the development trajectory. The development landscape is shown to provide a well-suited representation of seed states travelling along developmental trajectories, particularly when the states are envisioned as regulatory circuits. Looking at seed dormancy in terms of regulatory circuits and development landscapes offers a valuable perspective to improve our understanding of this biological phenomenon.

Flaxseed has been recognized as a valuable source of nutrients and bioactive compounds, including proteins that possess various health benefits. In recent years, studies have shown that flaxseed proteins, including albumins, globulins, glutelin, and prolamins, possess anti-cancer properties. These properties are attributed to their ability to inhibit cancer cell proliferation, induce apoptosis, and interfere with cancer cell signaling pathways, ultimately leading to the inhibition of metastasis. Moreover, flaxseed proteins have been reported to modulate cancer cell mechanobiology, leading to changes in cell behavior and reduced cancer cell migration and invasion. This review provides an overview of the anti-cancer properties of flaxseed proteins, with a focus on their potential use in cancer treatment. Additionally, it highlights the need for further research to fully establish the potential of flaxseed proteins in cancer therapy.

The paper examines rational Darboux-Crum transforms (RDCTs) of the Jacobi-reference (JRef) potential on the line, with an emphasis on the transformations using only normalizable seed solutions. The Cooper-Ginocchio-Khare (CGK) potential constitutes the simplest example of this rich family of exactly solvable one-dimensional (1D) potentials. It was explicitly confirmed that that an arbitrary Darboux-Crum transformation (DCT) of the given Sturm-Liouville equation (SLE) can be represented as a chain of sequential Darboux deformations of the associated Liouville potentials. If the rational SLE (RSLE) under consideration is exactly solvable and the transformation function (TF) used at each step is nodeless then each RSLE constructed in such a way was proven being exactly solvable itself. The exact solvability of RDCTs of the JRef canonical SLE (CSLE) was also confirmed for the DCTs using pairs of juxtaposed eigenfunctions (an extension of the renowned Adler theorem to the RCSLEs of our interest). By re-expressing the reference polynomial fraction (RefPF) of the transformed CSLE in terms of the Krein determinant (KD), instead of Crum Wronskian (CW), it was shown that the eigenfunctions under consideration are expressible in terms of polynomial solutions of a generalized Heun equation with positions of the most poles dependent on the exponent parameters. The outlined technique was extended to two isospectral SUSY partners of the JRef potential (as well as to its third sibling with the inserted new lowest-energy level) which, by analogy with the CGK potential, are quantized by polynomial solutions of the 2-Heun equation with all four poles at some fixed positions on the real axis.

Ampelography, the botanical discipline dedicated to the identification and classification of grapevine cultivars, was grounded on the description of morphological characters and more recently is based on the application of DNA polymorphisms. New methods of image analysis may help to optimize morphological approaches in ampelography. The objective of this study was the classification of representative cultivars of Vitis vinifera conserved in the Spanish collection of IMIDRA according to seed shape. Thirty eight cultivars representing the diversity of this collection were analyzed. A consensus seed silhouette was defined for each cultivar representing the geometric figure that better adjusted to their seed shape. All the cultivars tested were classified in ten morphological groups, each corresponding to a new model. The models are geometric figures defined by equations and similarity to each model is evaluated by quantification of percent of the area shared by the two figures, the seed and the model (J index). The comparison of seed images with geometric models is a rapid and convenient method to classify cultivars. A large proportion of the collection may be classified according to the new models described and the method permits to find new models according to seed shape in other cultivars.

Directed Energy Deposition (DED) processes necessitate a consistent material flow to the melt pool, typically achieved through pneumatic conveying of metal powder via thin pipes. This study aims to record and analyze the multiphase fluid-solid flow. An experimental setup utilizing a high-speed camera and specialized optics was constructed, the flow through thin transparent pipes was recorded. The resulting information was analyzed and compared with coupled Computational Fluid Dynamics - Discrete Element Modeling (CFD-DEM) simulations, with special attention to the solids flow fluctuations. The paper details the experimental design, video analysis using Particle Tracking, and a novel method for deriving volumetric concentrations and flowrate from flat images. The findings confirm the accuracy of the CFD-DEM simulations and provide insights into the dynamics of pneumatic conveying, which could be used to enhance the efficiency of DED processes.

Studies on particulate air pollution indicate that a new type of pollutant should be considered from mainly fossil fuel combustion and automobile exhaust emissions, i.e. environmentally persistent free radicals. These radicals, ubiquitous in the environment, have a long life span and are capable of producing harmful reactive oxygen species. Samples of dandelion were collected in 2020 and 2021 in spring and late summer. Roots, leaves, flower stalks, and inflorescences of Taraxaum sp., were collected from 6 sites with 3 plants each, along with monitoring of PM air pollution. The free radical content in each part of the plant was measured by electron paramagnetic resonance. The leaf was selected as the most appropriate part of the plant for the measurement of carbon-derived free radicals. The geff value and the total number of spins were calculated. Relationships were found between location, season, and measurements. The electron paramagnetic resonance spectrum consists of at least two components, which can be attributed to C-type radicals, and mixed C+O radicals. Their increase in numbers in the fall seasons, compared to the spring seasons, is also noticeable. It has also been observed that leaves collected in autumn have a higher geff value, which is probably related to the higher amount of oxygen- and carbon-derived free radicals.

In tracking-by-detection paradigm for multi-target tracking, target association is modeled as an optimization problem that is usually solved through network flow formulation. In this paper, we proposed combinatorial optimization formulation and used a bipartite graph matching for associating the targets in the consecutive frames. Usually, the target of interest is represented in a bounding box and track the whole box as a single entity. However, in the case of humans, the body goes through complex articulation and occlusion that severely deteriorate the tracking performance. To partially tackle the problem of occlusion, we argue that tracking the rigid body organ could lead to better tracking performance compared to the whole body tracking. Based on this assumption, we generated the target hypothesis of only the spatial locations of person’s heads in every frame. After the localization of head location, a constant velocity motion model is used for the temporal evolution of the targets in the visual scene. Qualitative results are evaluated on four challenging video surveillance dataset and promising results has been achieved.

In order to reduce negative effects of application of chemical agents, biological control is becoming increasingly important. This paper therefore focused on research of effects of certain types of seed beetles on control of invasive plant species in Serbia. Numerous sources suggest that for legumes and seed beetles Bruhinae: Chrysomelidae the rule of coexistence in pairs applies in all ecozones. The species rely on one another, primarily in terms of geographical origin or association, thus one plant species is frequently attacked by only one type of seed beetle. Being confirmed to be expressly monophagous, bruchins have proven to be excellent potential agents of control of invasive and harmful host plants (to date, false indigo-bush in Serbia), as is the case of the seed beetle of Persian silk tree, which has been registered as monophagous in Serbia for the first time, making it the number one potential agent in control of the host plant – Persian silk tree in Greece. Standard entomological methods were used, from sample collections, to experiments in photo-eclectors, during dissection counting and placing the seed for development inside by the method 1 flacon – 1 seed, to maintain precise records of the origin of the emerged insects and their numbers, within standard laboratory conditions. The conditions favoring the expansion of the plant have already developed due to climatic circumstances (changes in terms of heat extremes – global warming and precipitation), and it is now gradually becoming invasive. Parasitoid accumulation of roughly one-third (30%) of the total number of false indigo-bush pods makes the false indigo-tree seed beetle a viable candidate for the status of a bioagent. The species has the extreme potential for the application of biological measures which is now quickly gaining importance, all for the purposes of developing the integral control of the plants. Species Acanthoscelides pallidipennis and Bruchidius terrenus have been recorded in this research for the first time in Serbia, while calendars of development have been made for the researched bruchin species, which represents a significant scientific contribution.

Mee (Madhuca longifolia) is an important economic tree growing throughout the subtropical region of the Indo-Pak subcontinent. Mee seed constituents have distinctive chemical properties and thus provide nutritional and functional characteristics to the mee fat. The mee seed fat is an edible fat which can provide fat requirement of human diet in an economical way. Research on potential utilizations, understanding on the chemical composition, nutritional value and industrial applications of mee fat is important for efficient use mee seed fat. There were some reports available on potential applications of mee fat in food processing industry. But presently mee fat can be considered as an underutilized seed fat. In India mee fat used for edible purposes for a certain extent with compare to Sri Lanka. Therefore, more scientific researches should conduct on Sri Lankan mee varieties on edible purposes and popularized edible uses of Mee fat in Sri Lanka. Scientific knowledge and agricultural tools should effectively apply to make mee fat beneficial for its commercial applications. This chapter summarizes recent research work and studies available on botany, phytochemistry, functional properties, processing as well as food and non-food industrial applications of mee fat and other valuable parts of mee tree.

Medicinal and aromatic plants are gaining more importance because of their potential application in food, pharmaceutical and fragrance industry. Medicinal and aromatic plants have been used in cosmetics, perfumery, pharmaceuticals and food flavoring since ancient times, because of the presence of essential oils and different components. Seeds are of immense economic and biological importance, and they contain high oil, protein and starch reserves. The seeds of medicinal and aromatic plants are stores of important and active secondary metabolites that have been economically and commercially beneficial and helpful for medicine and pharmacy. The seeds of fennel are highly nutritious, and the seeds contain different minerals such as calcium, magnesium, and potassium. The seeds are helpful in weight loss and cancer prevention. They can also improve digestive health, regulate blood pressure, improve skin appearance, and promotes lactation. The main chemical components of lavender are linalool, linalyl acetate, 1,8-cineole, β-ocimene, camphor and terpinen-4-ol. The lavender essential oil has anxiolytic, anti-inflammatory, antimicrobial, antioxidant and antinociceptive activities.The main components of thyme are p-cymene, γ-terpinene and thymol. Thyme can help to improve eyesight, and it has high anti-bacterial and anti-inflammatory activities. The main compounds of Echinacea species are chlorogenic acid, caftaric acid, cynarin, echinacoside and cichoric acid. The keyword searches for Fennel, Lavender, Thyme, Echinacea, Seed biology, Traditional medicinal science and seed anatomy were performed by using Web of Science, Scopus, PubMed and Google scholar. The aim of this article review is to survey the pharmacological and health benefits of seeds of important medicinal plants.

Cotton seeds as the main by-product of cotton are not only an important raw material for edible oil and feed but also a source of biofuel. The quality of cotton seeds directly affects cotton planting and is closely related to the yield and fiber quality. However, the molecular mechanism governing cotton seed size remains largely unexplored. This study investigates the regulatory mechanisms of cotton seed size by focusing on two cotton genotypes, N10 and N12, which exhibit notable phenotypic variations across multiple environments. Developing seeds were sampled at various stages (5, 20, 30, and 35 DAP) and subjected to RNA-seq. The temporal pattern clustering and WGCNA on differentially expressed genes identified 413 candidate genes, including these related to sugar metabolism that were significantly enriched in transcriptional regulation. A genetic transformation experiment indicated that the overexpression of the GhUXS5 gene encoding UDP-glucuronate decarboxylase 5 significantly increased seed size, suggesting an important role of GhUXS5 in regulating cotton seed size. This discovery provides crucial insights into the molecular mechanisms controlling cotton seed size, helping to unravel the complex regulatory network and offering new strategies and targets for cotton breeding to enhance the economic value of cotton seeds and overall cotton yield.

Protein hydrolysates are plant biostimulants containing amino acids, oligopeptides, and peptides in their composition. When supplied to plants, protein hydrolisates (PH) have been identified to improve nitrogen metabolism, enhance the activity of antioxidant enzymes, boost plant defence response to stresses, and positively impact the quantity and quality of products. Soybean is a crucial global commodity, with nitrogen being the primary nutrient for crop development as it directly affects productivity. This study aimed to evaluate the effect of a HP-based biostimulant on the N metabolism in nodulated soybean plants and their productivity. A greenhouse experiment was conducted to test two modes of application of the 0.20% HP-based biostimulant. Soybean plants, growing in pots, were treated with HP 0.20% either via seed treatment or foliar application (at growth stages V3 and V5). Activities of enzymes and compounds related to N metabolism, gene expression, and productivity components were analysed. It was observed that the mode of application did not significantly influence the results. The application of HP increased the concentration of nitrate, amino acids, and ureides in soybean leaves. It also positively altered the expression of genes such as nitrate reductase, urease, and asparagine. Additionally, it enhanced productivity, resulting in plants with a greater number and weight of pods and grains. Therefore, it is possible to consider HP as a stimulator for increasing soybean productivity, even under non-stressing conditions.

In this work, the degassing process of corn seeds was experimentally and numerically analyzed by removing air or other gases from around the seeds, specifically from the seed coating, in a rough vacuum chamber. The two complementary variants are employed to understand and optimize this process to improve the quality and germination rate of the seeds. Several experiments were conducted with well-established durations and masses of corn seeds at different temperatures to observe and record the behavior of the system, facilitating the modeling of the degasification process in the vacuum compartment. Modeling the degasification operation in the vacuum chamber allowed for determining the pressure profiles on the vacuum chamber and its lid. Numerical simulations were either conducted using a simulation program developed in the Visual Basic Applications (VBA) language for Microsoft Excel to model the degassing process in the vacuum chamber, or with the assistance of specialized software (transient structural analysis and simulation program in the ANSYS Workbench environment). Statistical analysis of the correlation between experimental and estimated pressure values revealed that both the proposed mathematical model and the solution method are well-chosen, with differences expressed through the absolute error (EA) being very small. Structural dynamic analysis carried through the Finite Element Method (FEM) highlights that the chosen materials for manufacturing the vacuum chamber vessel (316 stainless steel) or the chamber lid (transparent acrylic plastic) are durable and capable of withstanding the desired pressure and temperature demands in the seed treatment process. Additionally, through structural dynamic analysis, it was possible to study the deformation of system components, providing a detailed perspective on their structural distribution.

Knowledge about pharmacological benefits of different seeds is an important factor for cultivation and application of medicinal herbs and plants. The seeds of medicinal plants are stores of valuable and active secondary metabolites that have been commercially and economically beneficial and helpful for medicine and pharmacy. The major parameter of reproduction and preservation of plants are also seeds which have a functional role in the distribution and establishment of plant in different regions. Five important seeds which have tremendous medicinal and pharmacological benefits are anise, basil, borage, cilantro and chamomile. Anise seed is used as a spice, either whole or ground, and its essential oil and extract are also obtained from the seeds. Basil seeds have a long history of usage in Chinese and Ayurvedic medicine, which are the good source of minerals, high in fiber including pectin, rich is flavonoids and other polyphenols. Borage seed oil is used for skin disorders such as seborrheic dermatitis, atopic dermatitis, and neurodermatitis. Cilantro is an annual herb that is part of the Apiaceae family. The seeds are rich in iron, zinc, copper and essential minerals which can decrease bad cholesterol and improves good cholesterol in the body. Chamomile can be considered for treatment of insomnia, hemorrhoids, anxiety, diarrhea and may help with wound healing and skin irritation. The keyword searches for Anise, Seed, Basil, Borage, Cilantro, Chamomile, Seed biology, Traditional medicinal science and seed anatomy were performed by using Scopus, Web of Science, PubMed and Google scholar. The aim of this article review is to survey the pharmacological and health benefits of seeds of five important medicinal plants.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

Açaí, a fruit from the Amazon, is valuable both economically and nutritionally. Its seeds, often discarded, can be transformed into bio-oil through pyrolysis (a thermochemical degradation process of residual biomass), providing a sustainable alternative to fossil fuels. This study investigates how temperature and molarity influence the antimicrobial, antioxidant, and cytotoxic activities of the produced bio-oil. Tests were conducted using Gas Chromatography-Mass Spectrometry (GC-MS) and assays to evaluate antimicrobial, antioxidant, and cytotoxic activities at different temperatures (350, 400, and 450 °C) and molarities (0.5 M, 1.0 M, and 2.0 M). Phenolic compounds were the most abundant in the bio-oil (55.70%), followed by cyclic and aromatic hydrocarbons (11.89%) and linear hydrocarbons (9.64%). Despite a reduction in oxygenated compounds, the bio-oil maintained bacteriostatic activity against Escherichia coli and Staphylococcus aureus across various temperature ranges, particularly at 350 °C. Antioxidant activity was highest at 350 °C and at lower molarities. Additionally, lower concentrations of acid impregnation exhibited cytotoxic effects at higher temperatures. Thus, bio-oil from açaí seeds produced via pyrolysis demonstrates potential for antioxidant and antimicrobial activities, suggesting viability for further testing at dilutions with lower cytotoxicity.

The event camera generates an event stream based on changes in brightness, retaining only the characteristics of moving objects, addresses the high power consumption associated with using high-frame-rate cameras for high-speed eye tracking tasks. However, the asynchronous incremental nature of event camera output has not been fully utilized, and there are also issues related to missing event datasets. Combining the temporal information encoding and state-preserving properties of spiking neural network (SNN) with event camera, a near-range eye tracking algorithm is proposed as well as a novel event-based dataset for validation and evaluation. According to experimental results, the proposed solution outperforms artificial neural network (ANN) algorithms, while computational time remains only 12.5\% of that of traditional SNN algorithms. Furthermore, the proposed algorithm allows for self-adjustment of time resolution, with a maximum achievable resolution of 0.081ms, enhancing tracking stability while maintaining accuracy.

This study presents a novel kinematic tracking model, designed for a networked exoskeleton system that is asynchronously taught by a remote therapist. On the server side, the therapist’s rehabilitation exercises are quantitatively assessed using a monocular passive vision system. The resultant analytical metrics are then transmitted asynchronously over the network to patients equipped with exoskeletons. On the client side, the exoskeleton utilizes these analytical metrics as reference paths for exercises, complemented by electromyography (EMG) feedback. This work introduces a calibration approach aimed at estimating angular positions by utilizing EMG observations. The calibration model establishes real-time correlations between polynomial reference positions. This calibration mechanism is integrated into simulations of both upper and lower limb exoskeletons. We further explore redundant kinematics, incorporating an EMG observer for linear, time-variant rehabilitation tracking control. Our methodology is validated using vision-based metric data and experimental EMG measurements for various exercises, including shoulder flexion, elbow flexion, and rowing-like movements. This work also includes computer simulations for tracking the control of rehabilitation exercises, demonstrating the adaptability of the system in reliably, robustly, and effectively following desired trajectories.

Intelligent ship technology is currently an international research hotspot, and model predictive control is widely used in the path-tracking control of intelligent vehicles. To construct an intelligent ship anti-disturbance path-tracking control method, firstly, an environmental disturbance model was constructed with the actual meteorological data of the target sea area. Secondly, the Fossen ship equation of motion is linearized and discretized as the ship motion model. Thirdly, the expression of the prediction equation is derived from the ship motion model. Fourthly, the cost function is constructed by using the polar diameter and polar angle values of the ship. Fifth, the power function in the cost function is replaced with an exponential function to obtain an improved cost function. Sixthly, according to the Lyapunov theory and the MPC terminal constraint theory, the stability of the improved cost function is verified. Seventh, different test paths are set up, the environmental disturbance model is taken as the external disturbance, the ship motion model, the prediction equation, and the improved cost function are used to design the anti-disturbance path-tracking control algorithm according to the model prediction control idea for simulation experiments. Finally, different MATLAB simulation results show that the improved cost function can resist disturbance of the external wave, current, and wind, and effectively track the target path. Therefore, this study provides a reference for improving the navigation safety of ship path-tracking.

Concentrator photovoltaic (CPV) technology offers an alternative to conventional photovoltaic systems, focusing on the concentration of solar radiation through the optics of the system onto smaller and more efficient solar cells. However, the surface on which the solar beam is incident must remain oriented towards the position of the sun, which requires the use of large and heavy external elements known as solar trackers. In addition to their size, these elements must be as accurate as possible to avoid misalignment. To avoid the need of these solar trackers, the concept of tracking-integrated concentrating systems has been developed. This technology has been researched to make CPV systems accessible in places where conventional systems are not viable, such as building roofs or agrivoltaic fields. This review presents a detailed classification of the existing designs in the literature and providing an overview of this type of system. By eliminating the need for external solar trackers, tracking-integrated CPV systems offer a promising solution to increase the adoption of this technology. Therefore, it is expected that these systems will be a viable and effective option for solar power generation.

Previous studies investigated the effects of seed rates and seed recycling practices on the yield and yield related variables. However, higher yield does not always guarantee cost-efficiency. This study aimed at investigating the yield effects of plot-level seed rate along with the cost-benefit analysis of seed recycling practices. This study has introduced the dose-response model to the existing analytical methods used in analyzing the effect of different agrochemicals on crop yield. A multi-stage stratified sampling technique was used to select a total of 450 sample respondents. Data was gathered using a mix of data collection tools. Descriptive statistics along with the dose-response model have been applied for data analysis. Farmers of the study were found to be dissimilar in terms of their seed rate application. The dose-response analysis indicated that the highest average wheat yield has been associated with a seed rate of 50 kg ha-1 above what is recommended. The yield effect of seed recycling has also been assessed and a one-time seed recycling has caused a yield decline of 665 kg ha-1 as compared to the non-recycled seeds. The cost reduced by using recycled seed is by far lower than the economic gains associated with using unrecycled and fresh seeds. The cost-benefit analysis made clear that farmers can reduce their seed costs through seed recycling but their yields and net income can be best improved by using unrecycled CBWS. Thus, farmers must be encouraged to make use of unrecycled seed by establishing agricultural credit schemes geared towards seed procurement and seed price subsidy as key strategies to reduce economically wasteful seed recycling practices.

Advances in accelerator technology have enabled the use of exotic and intense radioactive ion beams. Enhancements to tracking detectors are necessary to accommodate increased particle rates. Recent advancements in digital electronics have led to the construction or planning of next-generation detectors. To conduct kinematically complete measurements, it is essential to track and detect all particles produced as a result of the reaction. Furthermore, the need for high-precision physics experiments has led to significant developments in the detector field. In recent years, highly efficient and highly granular tracking detectors have been developed. These detectors significantly enhance the physics programme at dedicated facilities. An overview of the charged-particle tracking detectors in low-energy nuclear physics will be given.

With the vast amount of goods being shipped around the world, there is a need to track and manage various types of assets, particularly shipping containers. Logistics industries dealing with small facilities, shipments, equipment, and vehicles must be tracked. There are many applied asset tracking systems such as Radio-Frequency Identification (RFID), Bluetooth Low Energy (BLE) Beacon, and Long-Range Radio (LoRa). This paper presents these systems and focuses on locating assets using LoRaWAN technology, which has a positive impact on the responsive and sustainable cities in Egypt. IoT-based Long Range (LoRa) is a low-power, wide-area communication technology that uses radio frequencies to transmit data over long distances. The extended range, low power consumption, low maintenance, and the ability to store location data when the end node that needs to connect to the asset is out of the gateway's coverage make LoRa a good choice for developing asset-tracking applications. This paper introduces a real-time tracking experiment as a result of a project implementation, whose goals are aligned with industry, innovation, and infrastructure and Sustainable Cities and Communities, the Sustainable Development Goals (SDGs) No. 9 and 11.

Sorghum (Sorghum bicolor L.) ranks fifth as the most crucial cereal crop globally, yet its seed morphology remains relatively unexplored. This study investigated seed morphology in sorghum based on 115 mini core and 130 Senegalese germplasms. Eight seed morphology traits encompassing size, shape, and color parameters were assessed. Statistical analyses explored potential associations between these traits and resistance to three major sorghum diseases: anthracnose, head smut, and downy mildew. Furthermore, genome-wide association studies (GWAS) were conducted using phenotypic data from over 24,000 seeds and over 290,000 publicly available single nucleotide polymorphisms (SNPs) through the Genome Association and Prediction Integrated Tool (GAPIT) R package. Significant SNPs associated with various seed morphology traits were identified and mapped onto the reference sorghum genome to identify novel candidate defense genes.

The research improves the strength of plastic using avocado seed starch and PLA. The effect of blending avocado seed starch and PLA was optimized using the RSM approach by using two variables: water absorption and biodegradability. Mixing them using RSM gave the best result: 1.8 g of starch and 3 g of PLA. Degradable plastic has a (tensile strength of 10.1 MPa; elongation at break of 85.8%; young modulus of 190 MPa). Infrared spectroscopy showed that the plastic had a -OH bond at 3273.20 cm-1, 3502.73 cm-1, 3647.39 cm-1, a CH2 bond at 2953.52 cm-1, 2945.30 cm-1, 2902.87 cm-1, a C=C bond at 1631.78 cm-1, and a C-O bond at 1741.72 cm-1. The plastic decomposed in soil. It was organic and hydrophilic. Thermal tests, the plastic can withstand heat well, losing weight at 356.86°C to 413.64°C, forming crystals and plastic melts at 159.10°C—the same as PLA. Melt flow test, sample melts before measurement, therefore not measurable—process conditions that affect. Water absorption of 5.763% and biodegradation rate of 37.988% decomposed for 12 days. In morphology analysis, the starch and PLA fused to form a smooth surface. RSM found value was close to 1. RSM gave the best process parameters.

The commercialization of historic streets constitutes a pivotal aspect of urban cultural heritage, and the comprehension of their visual perception serves as a valuable asset to urban planning and cultural conservation efforts. However, current research concerning the disparities in visual perception among diverse demographics within historic streets, as well as their spatiotemporal dynamics, remains insufficient. This study aims to utilize mobile eye-tracking technology to delve deeply into the visual perception characteristics of diverse demographics within commercialized historic streets, while also analyzing their spatiotemporal dynamics. We explore the disparities in visual perception of historic streets among groups with varying degrees of architectural knowledge and professional literacy. Through meticulous observation using mobile eye-tracking technology, we elucidate the visual perception patterns of different demographic characteristics through statistical analysis and spatiotemporal modeling. The findings reveal significant discrepancies in visual attention and perception among various groups. Participants with a higher understanding of architecture tend to focus more on architectural details and structures within the streetscape compared to those with a lower understanding, who exhibit greater interest in elements such as shops and signage. Moreover, during the process of perceiving the streetscape, participants’ eye movements transition from surrounding landscapes and historical edifices upon initial entry to the district, gradually shifting towards the commercial activities and distinctive architecture within the district. This study delves deeply into the visual perception characteristics and spatiotemporal dynamics of commercialized historic streets, providing invaluable insights for urban planning and cultural preservation endeavors. By revealing the impact of different demographic characteristics on the visual perception of historic streets, it offers new insights for urban planning and cultural heritage conservation.

Breeding early-maturing cultivars is one of the most important objectives for pear breeding. Very early-maturing pear provides an excellent parental material for crossing, while the immature embryo and low seed germination of its hybrid progenies often limit the selection and breeding of new early-maturing pear cultivars. In this study, we choose a very early maturing pear cultivar ‘Pearl Pear’ as study object, and investigate the effects of cold stratification, culture medium and seed coat on the germination and growth of early maturing pear seeds. Our results show that cold stratification (4℃) treatment could significantly improve the germination rates of early maturing pear seeds. A 100 days of low temperature pre-treatment and germination on White medium could increase the germination rate up to 84.54%. We also observe that seed coat removal could improve the germination activity of early maturing pear seeds, and middle seed coat removal (MSR) represents an optimal method with its high germination rate and low contamination. The results of our study established an improved protocol for seed germination of early-maturing pear seeds, which will greatly facilitate the breeding of new very early-maturing pear cultivars.

Coagulant lectin from Moringa oleifera seeds (cMoL) was characterized by potentiometry and scanning electron microscopy (SEM) using MOF, Metal-Organic Frameworks of [Cu3(BTC)2.H2O)3]n, to immobilize cMoL and construct biosensors. Developed aluminum-air batteries degraded indigo carmine dye formulated similar to a textile effluent; biosensors investigated cMoL interaction with specific galactose and monitored residual dye. SEM revealed components of electrode assembly steps. Oxide reduction reactions of batteries generated Al(OH)3 promoting dye electrocoagulation. Cyclic voltammetry showed differentiated redox peaks related to dye residue quantification by cMoL. Electrochemical systems evaluated cMoL interaction with ligand and efficiently degraded dye; biosensors could be used for lectin characterization and monitoring dye residues in environmental textile effluents.

Farmer’s right and their sovereignty is an important issue related with intellectual property rights and agrobiodiversity management. To boost farmer’s right, a conceptual hypothesis is proposed where they choose either a new high yielding variety or the existing one and apply conventional breeding approaches to select the seed for next years in their own fields. Although farmers produce seeds traditionally from several years, they have not been guided with scientific discipline to produce sufficient amount of quality seeds. This new concept suggests trained farmers can use breeding approaches to produce quality seed for their own use.

Seed viability is routinely measured on seeds that fail to germinate at the end of an experiment. Together with the number of germinants, this is used to estimate viability of the seeds at start of the experiment (i.e., initial viability) and provides the comparative basis on which germination success is determined. Perusal of the literature shows that sometimes (perhaps often, as the problem has yet to be recognized or reported) prolonged duration in the treatment, especially the control where little germination occurs, can lead to loss of viability. This results in underestimation of initial viability if that treatment is used. I caution against the routine use of end-of-trial germination and viability of ungerminated seeds as an estimate of initial viability in determining germination success of various treatments. I explore ways to deal with the problem but the preference is for estimates of initial viability to be undertaken on a separate sample of seeds concurrently with the experiment as this avoids the risk of seed death during the trial.

Current effort with light field displays is mainly concentrated on the widest possible viewing angle, while a single viewer only needs to view the display in a specific viewing direction. To make light field display a practical practice, a super multi-view light field display is proposed to compress the information in the viewing zone of a single user by reducing the redundant viewpoints. A quasi-directional backlight is proposed and a lenticular lens array is applied to achieve the restricted viewing zone. Eye-tracking technique is applied to extend the viewing area. Experimental results show that the proposed scheme can present vivid 3D scene with smooth motion parallax. Only 16.7% conventional light field display data are required to achieve 3D display. Furthermore, an illumination power of 3.5 watt is sufficient to lighten a 31.5-inch light field display，which takes up 1.5% of the illumination power required for planar display of similar configuration.

The dynamic factors in the environment violate the static environment assumption of the SLAM algorithm, leading to a decrease in the accuracy of camera positioning. In recent years, many studies have attempted to address dynamic objects by combining semantic constraints and geometric constraints, but issues such as poor real-time performance, the potential for mistakenly treating humans as rigid objects, and subpar performance in high-dynamic scenes still persist. This paper proposes a dynamic scene visual SLAM algorithm called Dynamic SLAM based on target tracking and multi-view geometry (TKG-SLAM), based on object detection, Kalman filters, and multi-view geometry. This algorithm takes into consideration both real-time performance and algorithm accuracy. It combines semantic constraints and multi-view geometry constraints, selectively running the algorithm in different scenarios, filtering and preserving static points for camera pose estimation. Experimental results demonstrate that, compared to current state-of-the-art dynamic SLAM methods, our approach achieves optimal performance in some scenarios and exhibits stronger real-time capabilities.

This paper is regarding design and program an Micro-controller Arduino Uno board by using Arduino software to work as a photo-sensor(Active) single axial solar tracker system(SASTS). A solar panel, two photo-resistors (LDR) in two sides (north/south) of the photo-voltaic(PV) and a servo motor are connected to the Uno board, which is running a code that prepared by Arduino software IDE in advanced then it works as a tracking system. Here, the LDRs send the signal of presence or absence of the light to the board and based on that sent signal the Uno reflects a new signal to the servo motor to rotate and finds the light source. Lastly, the photo-sensor single axis tracker is made while Continuously, the system tries to face the panel to the sun and whilst changing the irradiance intensity it starts searching to find the angle of highest irradiance. Based on results that are extracted from the data, the tracker system significantly boosts the output efficiency of the solar panel. By using the Micro-controller Uno board, LDRs, servo motor and special designed mechanical base, the tracking system is constructed, based on acquired data the influence of the STS on the increasing the solar panel efficiency is more obvious. Significantly, the tracker system rises the efficiency of the PV .

The size of seeds is particularly important for agricultural development, as it is a key trait that determines yield. It is controlled by the coordinated development of the integument, endosperm, and embryo. Large seeds are one of the important ways to improve the ultimate “sink strength” of crops, providing more nutrients for early plant growth and showing certain tolerance to abiotic stresses. There are several pathways for regulating plant seed size, including the HAIKU (IKU) pathway, ubiquitin-proteasome pathway, G (Guanosine triphosphate) protein regulatory pathway, mitogen-activated protein kinase (MAPK) pathway, transcriptional regulators pathway, phytohormone regulatory pathways including auxin, brassinosteroid (BR), gibberellin (GA), jasmonic acid (JA), cytokinin (CK), Abscisic acid (ABA), and MicroRNAs (miRNAs) regulatory pathway. This article summarized the seed size regulatory network and prospected ways to improve yield. We expect to provide valuable reference to researcher in the related field.

The venturi-type UFB-generating system was used to generate air and O2 UFBs in distilled water. The number concentrations of air UFBs were roughly controlled by adjusting the generation time and UFB waters ranging from 1.4 x 108 mL-1 to 1.0 x 109 mL-1 were prepared. Barley seeds were submerged in beakers filled with distilled water and UFB water in a ratio of 10 mL of water per seed. The experimental observation of seed germination clarified the role of UFB number concentration, that is, a higher number concentration induced earlier seed germination. In addition, the excessively high UFB number concentration caused the suppression of seed germination. A possible reason for the positive or negative effect of UFBs on seed germination is thought to be ROS generation (hydroxyl radicals and ∙OH, OH radicals) in UFB water. This was supported by the detection of ESR spectra of the CYPMPO-OH adduct in O2 UFB water. However, the question still remains: how can OH radicals be generated in O2 UFB water?

Korenaga and coworkers present evidence to suggest that 4.3 billion years ago the Earth’s mantle was dry and water filled the ocean to twice its present volume.[2] CO₂ was constantly exhaled during the mafic to ultramafic volcanic activity associated with magmatic plumes that produced the thick, dense and relatively stable oceanic crust. In that setting two distinct major types of sub-marine hydrothermal vents were active: ~400 °C acidic springs whose effluents bore vast quantities of iron into the ocean, and ~120 °C, highly alkaline and reduced vents exhaling from the cooler, serpentinizing crust at some distance from the heads of the plumes. When encountering the alkaline effluents, the iron from the plume head vents precipitated out forming mounds likely surrounded by voluminous exhalative deposits similar to the banded iron formations known from the Archean. These mounds and the surrounding sediments likely comprising nanocrysts of the variable valence FeII/FeIII oxyhydroxide, green rust. The precipitation of green rust, along with subsidiary iron sulfides and minor concentrations of Ni, Co and Mo in the environment at the alkaline springs may have established both the key bio-syntonic disequilibria, and the means to properly make use of them – those needed to drive the essential inanimate-to-animate transitions that launched life. In the submarine alkaline vent model for the emergence of life specifically it is first suggested that the redox-flexible green rust microcrysts spontaneously formed precipitated barriers to the complete mixing of carbonic ocean and alkaline hydrothermal fluids, barriers that created and maintained steep ionic disequilibria; and second, that the hydrous interlayers of green rust acted as 'engines' that were powered by those ionic disequilibria and drove essential endergonic reactions. There, aided by sulfides and trace elements acting as catalytic promoters and electron transfer agents, nitrate could be reduced to ammonia and carbon dioxide to formate, while methane may have been oxidized to methyl and formyl groups. Acetate and higher carboxylic acids could then have been produced from these C1 molecules and aminated to amino acids, and thence oligomerized to offer peptide nests to phosphate and iron sulfides and secreted to form primitive amyloid-bounded structures, leading conceivably to protocells.

In globe artichoke both the edible portion and the waste biomass are recognized as valuable sources of bioactive compounds. For this study, heads with 30 cm-long floral stems, including 2-3 leaves, were harvested from five genotypes which included two traditional vegetatively-propagated varietal types (‘Brindisino,’ and ‘Violetto di Foggia,’) and three "seed"-propagated hybrids (‘Tempo,’ ‘Opal,’ and ‘Madrigal’). The study aimed to determine the total and individual polyphenolic concentrations (measured spectrophotometrically and by HPLC) and antioxidant activity (AA) in different artichoke parts, namely the "hearts" (H), head waste (HW), stem waste (SW), and leaf waste (LW). ‘Brindisino’ SW exhibited the highest accumulation of luteolin (26,317 mg kg−1 F.W.), while ‘Tempo’ H displayed the highest cynarin content (190 mg kg−1 F.W.). ‘Tempo’ HW and H showed the highest levels of apigenin (640 mg kg−1 F.W.), and the greatest source of chlorogenic acid was found in the HW of ‘Opal’ and the H of ‘Brindisino’ (4,300 mg kg−1 F.W.). The hybrids generally exhibited lower total polyphenolic concentrations than the traditional genotypes, particularly evident in the LW. The SW demonstrated the highest concentration of total polyphenols (18,000 mg kg−1 F.W.), followed by the edible H and non-edible HW (12,000 mg kg−1 F.W.), while the LW exhibited the lowest concentration (2,000 mg kg−1 F.W.). Interestingly, the AA did not precisely align with the total polyphenolic concentration, showing slight variations between the examined parts and genotypes.

: The radar multi target tracking (MTT) technique requires prior knowledge of a number of parameters about the sensor, the target and backgrounds. The Integrated Track Splitting (ITS) is a fully automatic track-while-scan (TWS) target tracking algorithm capable of extracting and tracking a target in a dense clutter environment using quality false track discrimination (FTD) methodology. The computational complexity in ITS algorithm is limited, compared to other algorithms they use statistical methods to discriminate between false and true tracks, such as multiple hypothesis tracking (MHT), mainly due to the FTD performed. The paper provides an analysis of tracking parameters that allows determining the limit of the possibility of successful target tracking. Extensive experiments have confirmed that the recursive determination of the probability of the existence of a track during tracking can confirm a true track and reject a false track. The clutter density, number of random occurred targets, targets load during the maneuver and the target detection probability were varied. The results of experiments, carried out via Monte Carlo simulations, shown over representative confirmed true tracks (CTT) diagrams, root mean square error position and normalized tracking efficiency parametric diagrams allow the user to select optimal multi-target tracking parameters for different scenarios and clutter densities.

Clonal evolution and cellular plasticity are the genetic and non-genetic driving forces of tumor heterogeneity that in turn determines the tumor cell response towards therapeutic drugs. Several lines of evidence suggest that therapeutic interventions foster the selection of drug resistant neural crest stem-like cells (NCSCs) that establish minimal residual disease (MRD) in melanoma. Here we established a dual reporter system enabling the tracking of NGFR expression and mRNA stability, providing insights into the maintenance of NCSC-states. We observed that the transcriptional reporter that contained a 1kb fragment of the human NGFR promoter was activated only in a minor subset (0.72±0.49%, range 0.3-1.5) and ~2-4% of A375 melanoma cells revealed stable NGFR mRNA. The combination of both reporters provided insights into phenotype switching and revealed that both cellular subsets gave rise to cellular heterogeneity. Moreover, whole transcriptome profiling and gene set enrichment analysis (GSEA) of the minor cellular subset revealed hypoxia-associated programs that might serve as potential drivers of an in vitro switching of NGFR-associated phenotypes and relapse of post-BRAF inhibitor treated tumors. Concordantly, we observed that the minor cellular subset increased in response to dabrafenib over time. In summary, our reporter-based approach provided insights into plasticity and identified a cellular subset that might be responsible for the establishment of MRD in melanoma.

Onion is not just an edible food but its seeds can also be an important source of valuable oil with various sensitive applications mainly in pharmaceutical, cosmetic and food fields. This has encouraged the use of a supercritical fluid extraction in the present study to obtain oil from local onion seeds, hence avoiding even traces of organic solvents. For several advantages carbon dioxide at supercritical conditions was used as the fluid. The effects of four key operating parameters like pressure, temperature, particle size and CO2 mass flowrate were investigated in ranges of [150, 250 bars], [35, 65°C], [0.25, 0.85mm] and [50, 100g/min], respectively, using a Box-Behnken experimental design, for a constant extraction time of 3 hours. This led to optimal operating conditions of 250 bar, 57°C, 0.25mm and 50g CO2/min for the highest oil extraction yield value of 24.36%. Furthermore, gas chromatography-mass spectrometry (GC-MS) was used to identify qualitatively and quantitatively the chemical composition of the onion seed oils. About ten components were identified in the extracts, but with four major ones, namely 9,12-Octadecadienoic acid ,methyl ester, 9,12-Octadecadienoic acid (Z,Z)-,methyl ester, 9-Octadecadienoic acid (Z)-,methyl ester and Hexadecanoic acid, methyl ester, present with significant percentages, depending on the operating parameters values. These fatty acids are well known for their benefits for human health. Finally the study shows the importance and the merits of fluids when used under particular conditions of pressure and temperature, in very sensitive industrial fields.

The winged bean is an underutilized legume that has the potential to contribute to nutrition and food security globally, especially in sub-Saharan Africa (SSA). However, very little research attention is paid to exploiting its full potential due to a lack of adequate knowledge of the existing genetic diversity in the available winged bean germplasm. To bridge this gap, seed morphometric and selected agro-morphological traits which are crucial for yield and seed quality determination in crop plants were used to assess the genetic diversity of thirty accessions of winged bean sourced from the Gene bank of the International Institute of Tropical Agriculture (IITA), Ibadan. The thirty winged accessions were evaluated under field trials at three agro-ecological zones in Nigeria. The agro-morphological data as well as the seed morphometric dataset obtained from a Multi-Spectral Imaging (MSI) system were subjected to Analysis of Variance (ANOVA), Principal Component (PC) analysis, cluster analysis, and correlation analysis. Significant differences (p &lt; 0.05) were observed among the accessions for all measured traits. The first three PCs accounted for 93% of the variation observed among the accessions for all measured traits. Accessions were grouped into three clusters based on the agro- morphological traits and three clusters under the MSI system. Seed yield per plant had the highest estimates of significant positive correlation with hundred seed weight, pod weight per plant, etc. at both phenotypic and genotypic levels. TPt-31 had the highest seed yield per plant, pod weight per plant, and early maturity while TPt-7 had an extended flowering and maturity period, the highest number of pods per peduncle and pods per plant as well as the lowest seed yield. These accessions could serve as a good resource for future winged bean improvement programs. The result also confirmed that the MSI system is an invaluable tool for discriminating among accessions of the same crop species.

Legume seed protein is an important source of nutrition, but it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defences against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defence or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species and strain dependent. Further research is needed to highlight which changes contribute the most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible, and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry identified peptide breakdown products.

A simple, efficient and stand-alone method for purification of river water using moringa seed powder and copper is discussed. Coagulant property of the seed powder clears turbid raw water and the oligodynamic activity of copper completely destroys E.coli bacteria. Both raw and treated water samples were tested for contaminants to verify the efficacy of the system. Treated water has turbidity in the range 3 NTU - 5 NTU and non-detected (< 1 MPN/100 mL) E.coli count making it suitable for drinking. The technique is very cost effective and can be practiced anywhere using locally available materials. It does not require a power source or any technical assistance. Being a stand-alone system the technique exceptionally useful in providing drinking water as an immediate solution in disaster areas affected by cyclone or floods.

This paper aimed to assess the technical efficiency of maize seed production and the major factors contributing on technical efficiency. Maize is the second most important staple crop in Nepal, but the average yield of maize is very low as compared to other countries having similar agro-climatic requirements. Inefficient use of resources had led to low yield in maize crop. The software Raosoft was used to determine the required sample size and total of 182 samples were selected using simple random technique in June, 2016. Stochastic production frontier model and Tobit model were used to derive the results. The average technical efficiency of maize seed production ranged from 0.25-0.92 with an average of 0.71which revealed the scope of increasing technical efficiency by 29 percent. The majority of the farmers (29.1%) were at higher technical efficiency level of 0.8-0.9 followed by 28.6 percent at 0.7-0.8 and 23.1 percent at 0.6-0.7. Age and schooling of household head, experience on maize seed production, area shared by maize crop and dummies variables such as livestock holding, source of seed and access to extension service had found significantly affecting on the technical efficiency level. For the least developed country like Nepal it would be better to use the available resources wisely and improvement of existing technologies would be more cost effective than that of discovering new technologies. The study recommended that the concerned organizations should focus on mixed agricultural farming system, access to better quality seed and provide technical knowledge which would help in improving technical efficiency.

1. Background: The global COVID-19 lockdowns are unique psychological factors, requiring adjustment and coping. This illustrative, South African case study investigated the influence the COVID-19 lockdown context would have on meditation and physical activity. As these were lifestyle patterns the null hypothesis was of no change. 2. Method: The methodology consisted of quantitative and qualitative phases. The quantitative phase was an empirical, case study review of data from the author’s HeartMath and Fitbit electronic devices, as from 9 November 2019 to 31 July 2021. This consisted of coherence and achievement data from the HeartMath Inner Balance application (app), as well as distance and activity data from the Fitbit app. The qualitative phase consisted of the selection and illustration of meditation sessions documented over lockdown. 3. Results: The highly significant increases in physical activity and meditation coherence and achievement collectively indicated significant health promotion over the COVID-19 Lockdown period. Subtle energetic, experiential descriptions of meditation apprehensions resonated and supported these quantitative findings. 4. Conclusions: COVID-19 lockdown has meant transformation, humility, and reordering of priorities. The meditation descriptions amplified information from the HeartMath and Fitbit electronic devices, together co-creating conscious, embodied, relationship science for discussion, instruction, and further research.

: In this paper, we examine potential methods for autonomously tracking and landing multi-rotor unmanned aerial vehicles (UAVs), a complex yet essential problem. Autonomous tracking and landing control technology utilizes visual navigation, relying solely on vision and landmarks to track targets and achieve autonomous landing. This technology improves the UAV's environment perception and autonomous flight capabilities in GPS-free scenarios. In particular, we are researching tracking and landing as a cohesive unit, devising a switching plan for various UAV tracking and landing modes, and creating a flight controller that has an inner and outer loop structure based on relative position estimation. The inner and outer nested markers aid in the independent monitoring and touchdown of UAV. Optimal parameters are determined via optimized experiments on the measurements of the inner and outer markers. An indoor experimental platform for tracking and landing UAV was established. Tracking performance was verified by tracking three trajectories of unmanned ground vehicle (UGV) at varying speeds, and landing accuracy was confirmed through static and dynamic landing experiments. The experimental results show that the proposed scheme has good dynamic tracking and landing performance.

Due to the advantages of low latency, low power consumption and high flexibility of FPGA-based acceleration technology, it has been more and more widely studied and applied in the field of computer vision in recent years. An FPGA-based feature extraction and tracking accelerator for real-time visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) is proposed, which can realize the complete acceleration processing capability of the image front-end and directly output the feature point ID and coordinates to the backend. The accelerator consists of image preprocessing, pyramid processing, optical flow processing, and feature extraction and tracking modules. For the first time, it implements a hardware solution that combines features from accelerated segment test (FAST) corners with Gunnar Farneback (GF) dense optical flow, to achieve better feature tracking performance and provide more flexible technical route selection. In order to solve the scale invariance and rotation invariance lacking problem of FAST features, an efficient pyramid module with a five-layer thumbnail structure is designed and implemented. The accelerator is implemented on a modern Xilinx Zynq FPGA. The evaluation result shows that the accelerator can achieve stable tracking of features of violently shaking images, and is consistent with the results of MATLAB code running on PC. When operating at 100MHz, the accelerator can process 108 frames per second for 720P images and 48 frames per second for 1080P images. Compared to PC CPUs that consume seconds of time, the processing latency is greatly reduced to the order of milliseconds, making GF dense optical flow an efficient and practical technical solution on the edge side.