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The Interactions of Soy Protein and Wheat Gluten for the Development of Meat-like Fibrous Structure.

Consumers who are environmentally and health conscious are increasingly looking for plant-based alternatives to replace animal-based products in their daily diets. Among these alternatives, there is a growing demand for meat analogues that closely resemble the taste and texture of meat. As a result, significant efforts have been dedicated to developing meat analogues with a desirable meat-like structure. Currently, soy protein and wheat gluten are the main ingredients used for producing these meat analogues due to their availability and unique functionalities. This study observed that high moisture extrusion at moisture levels of 50-80% has become a common approach for creating fibrous structures, with soy protein and wheat gluten being considered incompatible proteins. After the structuring process, they form two-phase filled gels, with wheat gluten acting as the continuous phase and soy protein serving as a filler material. Moreover, the formation of soy protein and wheat gluten networks relies on a combination of covalent and non-covalent interaction bonds, including hydrogen bonds that stabilize the protein networks, hydrophobic interactions governing protein chain associations during thermo-mechanical processes, and disulfide bonds that potentially contribute to fibrous structure formation. This review provides case studies and examples that demonstrate how specific processing conditions can improve the overall structure, aiming to serve as a valuable reference for further research and the advancement of fibrous structures.

Application Analysis of Financial Time Series in Stock Market

Time series analysis is a basic tool in number investing. The time-series sequence is a sequence of variables measured in a fixed section sequence over some time. The fluctuation of stock price affects all aspects of social and economic life, so effectively predicting the trend of stock price changes has great economic and social value. Based on the existing research results on time series, this paper takes the stock market as an entry point, and sorts and summarizes the literature from the application fields and application methods of time series. The research results show that the application fields of time series involve the stock market, enterprises, macro economy, etc., among which the application of the stock market is the most commonly used and the most extensive. The research based on time series mainly innovates and corrects the research methods. The research in this paper can provide a theoretical reference value for further research on time series.

Advances in the application of recombinase-aided amplification combined with CRISPR-Cas technology in quick detection of pathogenic microbes.

The rapid diagnosis of pathogenic infections plays a vital role in disease prevention, control, and public health safety. Recombinase-aided amplification (RAA) is an innovative isothermal nucleic acid amplification technology capable of fast DNA or RNA amplification at low temperatures. RAA offers advantages such as simplicity, speed, precision, energy efficiency, and convenient operation. This technology relies on four essential components: recombinase, single-stranded DNA-binding protein (SSB), DNA polymerase, and deoxyribonucleoside triphosphates, which collectively replace the laborious thermal cycling process of traditional polymerase chain reaction (PCR). In recent years, the CRISPR-Cas (clustered regularly interspaced short palindromic repeats-associated proteins) system, a groundbreaking genome engineering tool, has garnered widespread attention across biotechnology, agriculture, and medicine. Increasingly, researchers have integrated the recombinase polymerase amplification system (or RAA system) with CRISPR technology, enabling more convenient and intuitive determination of detection results. This integration has significantly expanded the application of RAA in pathogen detection. The step-by-step operation of these two systems has been successfully employed for molecular diagnosis of pathogenic microbes, while the single-tube one-step method holds promise for efficient pathogen detection. This paper provides a comprehensive review of RAA combined with CRISPR-Cas and its applications in pathogen detection, aiming to serve as a valuable reference for further research in related fields.

A Novel Approach to Satellite Component Health Assessment Based on the Wasserstein Distance and Spectral Clustering

This research presents a multiparameter approach to satellite component health assessment aimed at addressing the increasing demand for in-orbit satellite component health assessment. The method encompasses three key enhancements. Firstly, the utilization of the Wasserstein distance as an indicator simplifies the decision-making process for assessing the health of data distributions. This enhancement allows for a more robust handling of noisy sensor data, resulting in improved accuracy in health assessment. Secondly, the original limitation of assessing component health within the same parameter class is overcome by extending the evaluation to include multiple parameter classes. This extension leads to a more comprehensive assessment of satellite component health. Lastly, the method employs spectral clustering to determine the boundaries of different health status classes, offering an objective alternative to traditional expert-dependent approaches. By adopting this technique, the proposed method enhances the objectivity and accuracy of the health status classification. The experimental results show that the method is able to accurately describe the trends in the health status of components. Its effectiveness in real-time health assessment and monitoring of satellite components is confirmed. This research provides a valuable reference for further research on satellite component health assessment. It introduces novel and enhanced ideas and methodologies for practical applications.

Research on the Application of Prompt Learning Pretrained Language Model in Machine Translation Task with Reinforcement Learning

With the continuous advancement of deep learning technology, pretrained language models have emerged as crucial tools for natural language processing tasks. However, optimization of pretrained language models is essential for specific tasks such as machine translation. This paper presents a novel approach that integrates reinforcement learning with prompt learning to enhance the performance of pretrained language models in machine translation tasks. In our methodology, a “prompt” string is incorporated into the input of the pretrained language model, to guide the generation of an output that aligns closely with the target translation. Reinforcement learning is employed to train the model in producing optimal translation results. During this training process, the target translation is utilized as a reward signal to incentivize the model to generate an output that aligns more closely with the desired translation. Experimental results validated the effectiveness of the proposed approach. The pretrained language model trained with prompt learning and reinforcement learning exhibited superior performance compared to traditional pretrained language models in machine translation tasks. Furthermore, we observed that different prompt strategies significantly impacted the model’s performance, underscoring the importance of selecting an optimal prompt strategy tailored to the specific task. The results suggest that using techniques such as prompt learning and reinforcement learning can improve the performance of pretrained language models for tasks such as text generation and machine translation. The method proposed in this paper not only offers a fresh perspective on leveraging pretrained language models in machine translation and other related tasks but also serves as a valuable reference for further research in this domain. By combining reinforcement learning with prompt learning, researchers can explore new avenues for optimizing pretrained language models and improving their efficacy in various natural language processing tasks.

Investigation and analysis of the safety risk factors of aging construction workers

The proportion of middle-aged and aging workers is increasing year by year in the construction industry. Affected by their physical functions and other conditions, the death rate of aging construction workers is higher than that of the workers in other age groups, which brings higher risks to the safety of the industry. Therefore, the paper aims to determine the main risk factor of safety brought on by the aging construction workers, and the degree of influence of safety risk factor on aging construction workers. Through the design of the questionnaire, the number and type of index to be studied are selected. The 6 first-level indexes and 30 second-level indexes were selected from 100 indexes. The AHP method was used to evaluate the influence of aging construction workers on the safety risk factor. The classification of work contents of aging construction workers in different age groups is proposed to reduce safety risks and provide an effective basis for management. The significance of this study is as follows: (1) The concrete analysis of index affecting the safety risk of aging construction workers has enriched the existing academic research; (2) the quantitative risk index system in the study, provides a reference value for further research in the academic circle; (3) The study of this paper has certain reference significance for construction companies and government regulatory departments to formulate policies and measures, such as job classification of aging workers in different ages and restrictive conditions for high-risk work.

Experimental and modeling investigation of freezing behavior for frozen sand molds

The essence of the freezing process in frozen sand molds is the heat transfer issue within the water-containing porous medium. In this paper, the evolutionary mechanism of the water-ice phase interface in frozen sand molds was studied through simulations and experiments at the mesoscale. Firstly, the evolutions of the phase field and temperature field during the unidirectional freezing process of frozen sand molds with different pore structures were investigated through numerical simulations. Then, utilizing the low-temperature freezing in-situ characterization platform, the nucleation mechanism of ice crystal bonding bridges between sand particles of varying materials was explored. The influence of sand mold characteristics on the freezing behavior of frozen sand molds was evaluated by the unique variable principle. Additionally, power function relationships for freezing time of frozen sand molds with different scales and materials were established, enabling the prediction of the time required for complete freezing of frozen sand molds. According to the results of multiple nonlinear regression analysis, the model showed reliable accuracy in predicting the time for fully frozen. This work will provide a valuable reference for further research on the engineering application of frozen sand molds.

Key Technologies of Plug Tray Seedling Transplanters in Protected Agriculture: A Review

The process of plug tray seedling transplanting is a crucial step in protected agriculture production. Due to issues such as high labor intensity, poor consistency of work quality, and low efficiency, the application of automated transplanting machines has provided a solution to these issues. For the diversity of transplanting operations, various mechanical structures and technological applications have been developed for automated transplanting equipment. Therefore, this paper provides systematic research of current studies on the key transplanter technologies. Firstly, through an analysis of the types of transplanting operations, the technical requirements of automated transplanting equipment for different operation types are elucidated. Subsequently, the key technologies applied in transplanting machines are discussed from the perspectives of substrate physical characteristics, end effectors, integration of multiple end effectors, vision systems, and transplanting path planning. Moreover, an analysis is conducted on the advantages, disadvantages, and application scenarios of different research methods for each key technology. Lastly, the existing problems and technical difficulties of the transplanting machine are summarized, and future research directions are discussed. This analysis provides a valuable reference for further research and development in the field of transplanting machines for plug tray seedlings.

Multi-Omics Revealed the Molecular Mechanism of Maize (Zea mays L.) Seed Germination Regulated by GA3

Maize is a valuable raw material for feed and food production. Healthy seed germination is important for improving the yield and quality of maize. However, the molecular mechanisms that regulate maize seed germination remain unclear. In this study, multi-omics was used to reveal the molecular mechanism of seed germination induced by gibberellin (GA) in maize. The results indicated that 25,603 genes were differentially expressed (DEGs) and annotated in the GO database, of which 2515 genes were annotated in the KEGG database. In addition, 791 mature miRNAs with different expression levels were identified, of which 437 were known in the miRbase database and 354 were novel miRNAs. Integrative analysis of DEGs and miRNAs suggested that carbohydrate, lipid, amino acid, and energy metabolisms are the primary metabolic pathways in maize seed germination. Interestingly, a lipid metabolism-related gene named ZmSLP was found to negatively regulate maize germination. We transformed this gene into Arabidopsis thaliana to verify its function. The results showed that the germination rate of transgenic Arabidopsis seeds was obviously decreased, and the growth of seedlings was weaker and slower than that of WT plants, suggesting that this gene plays an important role in promoting seed germination. These findings provide a valuable reference for further research on the mechanisms of maize seed germination.

Recent Progress on Hydrogen Production from Ammonia Decomposition: Technical Roadmap and Catalytic Mechanism

Ammonia decomposition has attracted significant attention in recent years due to its ability to produce hydrogen without emitting carbon dioxide and the ease of ammonia storage. This paper reviews the recent developments in ammonia decomposition technologies for hydrogen production, focusing on the latest advances in catalytic materials and catalyst design, as well as the research progress in the catalytic reaction mechanism. Additionally, the paper discusses the advantages and disadvantages of each method and the importance of finding non-precious metals to reduce costs and improve efficiency. Overall, this paper provides a valuable reference for further research on ammonia decomposition for hydrogen production.

Novel mutations in TRIP13 lead to female infertility with oocyte maturation arrest.

Oocyte maturation arrest (OMA) refers to a rare clinical phenomenon of oocyte maturation disorder caused by abnormal meiosis, which is also one of the primary causes of female infertility. The clinical manifestations of these patients are often characterized with failure to obtain mature oocytes after repeated ovulation stimulation and/or induced in vitro maturation. To date, mutations in PATL2, TUBB8 and TRIP13 have been demonstrated to be associated with OMA, but studies on the genetic-based factors and mechanisms of OMA are still incomplete. In this study, peripheral blood from 35 primary infertile women characterized with recurrent OMA during assisted reproductive technology (ART) were subjected to whole-exome sequencing (WES). By using Sanger sequencing and co-segregated analysis, we identified four pathogenic variants in TRIP13. Proband 1 had a homozygous missense mutation of c.859A>G appeared on the 9th exon, which resulted in substitution of Ile287 to valine (p.Ile287Val); proband 2 had a homozygous missense mutation of c.77A>G on the 1st exon, which resulted in substitution of His26 to arginine (p.His26Arg); and proband 3 had compound heterozygous mutations of c.409G>A and c.1150A>G on the 4th and 12th exon, which resulted in the substitutions of Asp137 to asparagine (p.Asp137Asn) and Ser384 to glycine (p.Ser384Gly) in the encoded protein respectively. Three of these mutations have not been reported previously. Further, transfection of plasmids harboring the respective mutated TRIP13 in HeLa cells resulted in changes in TRIP13 expression and abnormal cell proliferation as demonstrated by western blotting and cell proliferation assay respectively. This study further summarizes the TRIP13 mutations reported previously and expands the mutation spectrum of TRIP13 pathogenic variants, thereby providing a valuable reference for further research on the pathogenic mechanism of OMA associated with TRIP13 mutations.

Thermal-oxidation degradation of polylactic acid/cellulose nanocrystal composites: Effects of surface chemistry

Cellulose nanocrystal (CNC) is one of the most attractive renewable nano-fillers for polylactic acid (PLA). Depending on the production routes and starting cellulose sources, CNC possesses different surface chemistry, surface charge density, and morphology. However, the effect of the CNC surface chemistry on the thermal-oxidation degradation behaviors of PLA/CNC composites is still elusive, although it is a crucial factor in determining the hot processing and service of composites. In this work, sulfated (CNC-S), carboxylated (CNC-O), and uncharged CNC (CNC-Cl) were produced and compounded with PLA via a two-step masterbatch method, respectively. The thermal-oxidation degradation behaviors of the obtained composites were systematically investigated to elucidate their degradation mechanisms. Results show that the surface uncharged CNC produced by hydrochloric acid hydrolysis contributes to the thermal-oxidation stability of composites, but is more prone to agglomerate due to the lack of electrostatic repulsion. Compared with uncharged CNC, negatively charged CNCs (CNC-S and CNC-O) appear better dispersion state in the PLA matrix. However, PLA/CNC-S composites present relatively lower weight loss temperature and degradation activation energy due to the acceleration of desulfation process on thermal-oxidation degradation. Contrary to expectations, the addition of carboxylated CNC has almost no negative effect on the thermal oxygen stability of PLA because the decarboxylation reaction during melt-processing converts carboxyl groups to volatile by-products. This study sheds light on the thermal-oxidation degradation mechanism of PLA/CNC composites and will be a valuable reference for further research into the degradation of other bio-based polymeric materials.

Basic information about memantine and its treatment of Alzheimer's disease and other clinical applications.

Memantine is a noncompetitive moderate-affinity strong voltage-dependent N-methyl-D-aspartate receptor antagonist. It has been used to treat Alzheimer's disease (AD) since 1989. In 2018, it became the second most commonly used drug for the treatment of dementia in the world. AD is nonreversible, and memantine can only relieve the symptoms of AD but not cure it. Over the past half-century, memantine's research and clinical application have been extensively developed. In this review, the basic composition of memantine, the mechanism and limitations of memantine in the treatment of AD, memantine combination therapy, comparison of memantine with other drugs for AD, and clinical studies of memantine in other diseases are reviewed to provide a valuable reference for further research and application of memantine for the treatment of AD.

Coupling study of supersonic turbine stage and two-dimensional hydrogen/air rotating detonation combustor

The hydrogen/air rotating detonation turbine engine has the advantages of self-supercharging, small entropy increase, high thermal efficiency, high thrust-to-weight ratio, low fuel consumption, and low carbon emissions. However, the high-frequency and high-speed oscillation characteristics of the outflow of the rotating detonation combustor pose challenges for the turbine to extract work efficiently. In this study, a supersonic turbine stage designed using the Python code of the method of characteristics coupled with a two-dimensional rotating detonation combustor is numerically investigated. The propagation characteristics of the detonation wave in the aligned mode and misaligned mode and interaction with the supersonic turbine stage are carefully discussed. The results show that the coupling of the supersonic turbine stage and the rotating detonation combustor will cause the detonation wave to change from a single-wave mode to a three-wave co-propagating mode. The Kelvin–Helmholtz instability of the slip line increases after passing through the induced oblique shock. In the multi-wave mode, the detonation wave is self-adaptive, and multiple detonation waves interact to automatically adjust the propagation velocity, intensity, and distance of each detonation wave, and finally achieve a dynamic balance. The supersonic turbine stage has good operating performance under the condition of rotating detonation flow, its power level can reach 110 kW, and the maximum stagnation adiabatic efficiency of the supersonic turbine stage can reach 86%. The supersonic turbine guide vanes can greatly reduce the oscillation amplitude of the incoming flow. In the aligned mode, the supersonic turbine guide vanes has a more obvious effect of suppressing the amplitude of the incoming flow. The total pressure loss of the supersonic turbine stage is smaller, and the supersonic turbine rotor can extract work more efficiently in the aligned mode. These findings provide a valuable reference for further research on the hydrogen/air rotating detonation turbine engine, ultimately leading to the practical application of an energy-saving, high-efficiency, and low-emission hydrogen/air rotating detonation turbine engine.

A Review of Policy Framework Research on Promoting Sustainable Transformation of Digital Innovation

With the increasing demand for digital innovation scenarios, it is important to complement and improve the policy system for the governance of digital innovation activities. Combining the previous research results on the analysis of antecedent variables, basic effects and potential mechanisms of digital innovation, and based on the citation analysis of digital innovation topics based on the Citespace method, we find that in the past two decades, the topic of digital innovation policy research has gradually shifted from focusing on “constraining policies to control negative impacts” to focusing on “constructive policies to expand positive impacts”. The digital transformation has brought about multidimensional and profound impacts on the governance of innovation activities, and it is necessary to accelerate the theoretical research on policy frameworks for the new areas of technology socialization effects. Summarizing some of the important progresses, we propose a policy framework covering three aspects: policy needs for sustainable transformation of digital innovation, policy orientation and policy dimensions for sustainable transformation of digital innovation, creating R&D opportunities, optimizing R&D organization, building ecological advantages, improving R&D governance, knowledge creation, enabling applications, collaborative promotion, standardizing management, national digital innovation system, digital innovation foundation, data governance capacity, digital security and other aspects of the conceptual framework of the basic policies for sustainable transformation of digital innovation. The research viewpoints and conclusions are of theoretical reference value for further research on key policy conditions for digital innovation, major policy impact effects and digital innovation governance mechanisms.

Study on rheological and micro-structural properties of different modified asphalt by using organic and inorganic modifier

In order to evaluate the high and low temperature rheological properties of different modified asphalt, this paper prepared different types of modifiers and short-term aging modified asphalt (RTFOT), using dynamic shear rheometer (DSR) and bending beam rheological test (BBR) to compare and analyze the deformation resistance and stress sensitivity of different types (organic and inorganic) modified asphalt, determine its PG classification, and evaluate its fitting parameters with the help of Burgers model. The low-temperature mechanical properties of the fitting parameters were evaluated by the Burgers model; the chemical composition of different modified asphalts was analyzed by Fourier transform infrared spectroscopy (FTIR), and the microscopic state of the modified asphalts was observed by fluorescence microscopy. The results show that: with the increase of temperature, the high temperature deformation resistance of organic modified asphalt is better than that of inorganic modified asphalt, and PE modified asphalt is the best, and the low temperature performance of inorganic modified asphalt is poor, and the addition of SBS It will improve the low temperature crack resistance of asphalt. The road performance of different modified asphalts from strong to weak are PE modified asphalt, SBS modified asphalt, diatomite modified asphalt, montmorillonite modified asphalt. The research results have certain reference value for further research on different types (organic and inorganic) of modified asphalt.

ANALYTICAL PROFILE OF BILWADI AGADA

Background: Analytical profile of the drug is essential to assure the drug's safety, quality and efficacy. Objective: The present study was conducted to develop an analytical profile of Bilwadi Agada. Material and Methods: Analytical profile of the Bilwadi Agada tablet was assessed by organoleptic characteristics, physicochemical parameters, pharmaceutical analysis and TLC evaluation. The physicochemical evaluation was done by parameters viz. pH, loss on drying, total ash, water-soluble ash, alcohol-soluble extractive, and water-soluble extractives. Also, pharmaceutical analysis was done by the parameters like hardness, friability, disintegration time, uniformity of weight etc. Results: PH value, Loss on drying, total ash, water-soluble ash, alcohol soluble extractive and water-soluble extractive were 3, 0.068%, 18.5%, 4.5%, 19.2%, and 44%, respectively. The hardness of the tablet and friability was 3.6 kg/cm2 and 0.33%, respectively, whereas the disintegration time of the tablet was less than 15 minutes. Aflatoxins and heavy metals were absent, while no microbial growth was found in 24 hours in the Bilwadi Agada tablet. Discussion and Conclusion: Bilwadi Agada tablets pass all the parametric tests. These values of tests can be used as a reference value for further research on Bilwadi Agada.

Genome-Wide Identification and Expression Analysis of the 4-Coumarate: CoA Ligase Gene Family in Solanum tuberosum

4-coumarate: CoA ligase (4CL) is not only involved in the biosynthetic processes of flavonoids and lignin in plants but is also closely related to plant tolerance to abiotic stress. UV irradiation can activate the expression of 4CL genes in plants, and the expression of 4CL genes changed significantly in response to different phytohormone treatments. Although the 4CL gene has been cloned in potatoes, there have been fewer related studies of the 4CL gene family on the potato genome-wide scale. In this study, a total of 10 potato 4CL genes were identified in the potato whole genome. Through multiple sequence alignment, phylogenetic analysis as well as gene structure analysis indicated that the potato 4CL gene family could be divided into two subgroups. Combined with promoter cis-acting element analysis, transcriptome data, and RT-qPCR results indicated that potato 4CL gene family was involved in potato response to white light, UV irradiation, ABA treatment, MeJA treatment, and PEG simulated drought stress. Abiotic stresses such as UV, ABA, MeJA, and PEG could promote the up-regulated expression of St4CL6 and St4CL8 but inhibits the expression of St4CL5. The above results will increase our understanding of the evolution and expression regulation of the potato 4CL gene family and provide reference value for further research on the molecular biological mechanism of 4CL participating in response to diverse environmental signals in potatoes.

Optimized HPLC extraction method of quercetin and berberine based on response surface analysis.

In order to establish a method for simultaneous determination and extraction of quercetin and berberine in soil, HPLC-PDA multi-wavelength method was used to detect the content of berberine and quercetin in soil solution. The detection wavelength was 210 nm and 347 nm. The column temperature was 30 °C, the mobile phase A was acetonitrile, the mobile phase B was 0.1% phosphoric acid aqueous solution, and the flow rate was 1.0 mL min-1. Under the condition of isocratic elution, quercetin and berberine were completely separated within 20 min. The detection limit concentration of quercetin was 0.078 mg L-1, and the detection limit of berberine was 0.019 mg L-1. Both of them reached the trace level, and the recovery rate was between 97.2% and 107.4%. The response surface method was used to optimize the ultrasonic extraction method. The three main factors of extraction concentration, extraction temperature and solid-liquid ratio were optimized to obtain the highest extraction efficiency. The optimum extraction efficiency was as follows: 1 g soil sample was extracted with 80% ethanol aqueous solution, ultrasonic time was 10 min, ultrasonic temperature was 44 °C, and solid-liquid ratio was 1 : 17 g mL-1. The extracted quercetin and berberine concentrations were close to the predicted values of response surface optimization. The method of extracting and determining berberine and quercetin from soil established in this experiment is simple, fast, low cost and high safety. The feedback of the results also further verifies the feasibility in practical production and application, and provides reference value for further research and analysis of different allelochemicals in soil.

Asinara male donkey (Equus africanus asinus var. Albina) and stallion (Equus ferus caballus) reproductive characteristics: Correlations between testicular blood supply and sperm production

The Asinara donkey is a rare small albino variety of feral donkey listed as "critical" by the Food and Agriculture Organization of the United Nations (FAO) and by the Domestic Animal Diversity Information System (DAD-IS) in 2022. The objectives of the present study were to evaluate the reproductive characteristics of healthy male Asinara donkeys through andrological evaluation and testicular echo-color-Doppler examination to assess correlations between testicular blood supply and sperm production and to compare it with horse reproductive characteristics. Eight healthy donkeys and stallions were subjected to semen collection and evaluation, ultrasound and Doppler evaluation of the testicles and serum testosterone determination. The testosterone concentrations in donkeys were 1.42 ± 0.69 ng/ml while in horses were 1.90 ± 0.63 ng/ml within the normal values reported in these species. Horses had greater mean and total testicular volume, semen gel-free volume, and total sperm number than donkeys (P < 0.001). Blood flow analysis of the testicular artery in both locations was a relatively simple procedure. The waveforms recorded in a convoluted location (-con) of the testicular artery were characteristic of the high-resistance vessel, while in the marginal location (-marg) were of low-resistance. It was also recorded a gradual decrease in peak systolic velocity (PSV), resistive index (RI), pulsatility index (PI), mean velocity (MV) and testicular arterial blood flow (TABF) values along the peripheral course of the testicular artery. Therefore, donkeys had greater PSV-con (P ≤ 0.01), PSV-marg (P < 0.01), MV-con (P < 0.001), MV-marg (P < 0.01), testicular arterial blood flow rate (TABFr-con) (P < 0.001) and TABFr-marg (P < 0.01) than horses. Conversely, pulsatility index (PI-con) was higher in horses (P < 0.05). The comparative analysis between the Doppler parameters and the reproductive/seminal characteristics showed a positive correlation of TTBF-con with Testosterone (ρ = 0.976, p < 0.01 and ρ = 0.905, p < 0.01 in donkeys and horses, respectively), with Total Testicular Volume (ρ = 0.952, p < 0.01 and ρ = 1.000, p < 0.01 in donkeys and horses, respectively), and with Total spermatozoa concentration (ρ = 0.905, p < 0.01 and ρ = 0.813, p < 0.05 in donkeys and horses, respectively). Additionally, only in the donkey there was a positive correlation with Semen gel free volume (ρ = 0.881, p < 0.01) and Spermatozoa concentration × ml (ρ = 0.786, p < 0.05). The testosterone concentration was positively correlated in both species with Total testicular volume (ρ = 0.976, p < 0.01 and ρ = 0.905, p < 0.01 in donkeys and horses, respectively) and Total sperm concentration (ρ = 0.881, p < 0.01 and ρ = 0.976, p < 0.01 in donkeys and horses, respectively). It was also correlated positively with Semen gel free volume (ρ = 0.857, p < 0.01) and spermatozoa concentration (ρ = 0.762, p < 0.05) in donkeys. Finally, the PI-con (ρ = − 0.786, p < 0.05) was negatively correlated with Semen gel free volume in the donkeys. The results of this study show that Total Testicular Blood Flow is the parameter, together with testosterone, most positively correlated with testicular volume and total sperm concentration in both species. Furthermore, differences in both reproductive and testicular hemodynamic characteristics between the Asinara donkey and stallion are highlighted, suggesting that caution should be taken in transferring knowledge from one species to another. New data on reproductive aspects, seminal characteristics, testicular blood flow perfusion in healthy Asinara donkeys were reported and these may represent reference value for further research or clinical applications.