Number Research Articles

Impact of effective micro-organisms (EM) on the yield, growth and bio-chemical properties of lettuce when applied to soil and leaves

BackgroundIn today’s conditions, it is not possible to eliminate chemical inputs without reducing food production. Therefore, integrated methods that reduce the negative effects of chemical inputs are needed. One of the alternatives is the use of beneficial bacteria, which can both improve the yield and quality of vegetable crops and reduce the use of chemical fertilisers. This research was carried out to test the effects of a microbial fertiliser combined with inorganic fertiliser on the growth, biochemical properties and yield of lettuce and whether the use of chemical fertilisers could be reduced. Caipira curly lettuce variety was used as plant material. The microbial fertilizer used contains 7 different microorganisms and 2 different yeasts. The experiment consisted of eight treatments: Control (T0), 100% Chemical Fertilisation (T1), 50% Chemical Fertilisation + Microbial Fertilisation (T2), 75% Chemical Fertilisation + Microbial Fertilization (T3), 100% Chemical Fertilisation + Microbial Fertilisation (T4), Microbial Fertilisation Alone (T5), 50% Chemical Fertilisation + Microbial Fertilisation + Foliar Microbial Fertilisation (T6), 75% Chemical Fertilisation + Microbial Fertilisation + Foliar Microbial Fertilisation (T7).ResultsThe results of the research were statistically evaluated using analysis of variance at a significance level of p < 0.05, and the means were compared using the LSD test. It was observed that the microbial fertiliser did not adversely effect on the growth characteristics of lettuce and even had an ameliorative effect. The highest root dry weights were obtained in the T7, T3, T4 and T1 treatments. T7 treatment had 7.8% and 5.5% more dry weight than T1 and T4 respectively. Biochemical properties were significantly affected by treatments and it was significant that T2 and T4 had similar results. Because chemical fertilizer dose was reduced by 50% in the T2 treatment. The chemical fertiliser dose was reduced by 50% in the T2 treatment. Microbial fertiliser treatments had no negative effect on lettuce colour formation and even greener lettuces were harvested from T1, T7, T3 and T6 treatments. The highest total yield was obtained from T3 (30638.89 kg ha− 1) and T7 (30518.52 kg ha− 1). In other words, when the recommended dose of chemical fertiliser was reduced by 25%, higher yields were obtained. The yields in T3 and T7 were 6.71% and 6.29% higher than in T1, respectively. The marketable yield did not differ statistically between treatments except T0 and T5. Although there was no statistical difference, the highest numerical values belonged to the T7 (28907.41 kg ha− 1) and T3 (28814.82 kg ha− 1) treatments. In terms of marketable yield, T7 and T3 treatments gave 5.05% and 4.71% more than T1, respectively.ConclusionsIt was determined that the microbial fertiliser used had no negative effect on the lettuce crop and even had an ameliorative effect. With the use of microbial fertiliser, both chemical fertilisation was reduced and higher yield and quality values were obtained from T3 and T7 treatments compared to chemical treatment alone (T1). In addition, the ameliorative effects of the foliar application of microbial fertiliser were also noted in the T7 treatment. As a result, this study showed that the use of microbial fertiliser could increase yield and quality and save at least 25% of fertiliser.

LAUKSAIMNIECĪBAS BERAMKRAVU MATERIĀLU TRANSPORTĒŠANAS GLIEMEŽTRANSPORTIERA JAUDAS PARAMETRU PĒTĪJUMI

The article presents the results of theoretical and experimental laboratory investigations of an improved screw conveyor for bulk agricultural materials that has been created, which, instead of a solid spiral winding, fixed to the drive shaft, uses a spiral winding, formed by separate curvilinear planes (blades), which are also separately fixed to the shaft, yet as a whole form a single spiral. An analytical dependence was obtained for determination of the magnitude of the torque on the drive shaft of this transport working element. The numerical values, obtained as a result of the laboratory experiments, made it possible, when conducting a regression analysis, to derive a new analytical expression in the form of a regression equation. The analysis of the regression equation shows that these factors, which have a significant impact upon the increase in the torque, are the factors: x1 (D) – the diameter of the fixed casing in which the screw is installed and x2 (ψ) – the filling factor of the conveyor with the transported bulk material. Increasing the value of the factor x3(n), i.e., the rotation speed of the vane working body leads to a decrease in the torque value.

STUDY OF THE DYNAMICS OF A VIBRATION MACHINE CONSIDERING THE INFLUENCE OF THE PROCESSING MEDIUM

This paper presents the results of studying the dynamics of a vibration machine, takinginto account its interaction with the processing medium based on representing the medium as a continuoussystem. The application of the complex number method significantly simplifies the formation of equations ofmotion for the discrete-continuous system, which is a computational model of the vibration system "machinemedium."The study substantiates and develops a method for considering the mutual influence of the machineand the processing medium, based on representing the medium as a continuous system. The dynamicsof the vibration system "machine-medium" is studied, and oscillation parameters are determined withoutconsidering resistance forces. It is found that the overall motion of the vibration system is described by fourcomponents. The first three describe the natural oscillations of the system, of which the first two are determinedonly by initial conditions, and the third reflects the accompanying oscillations caused by the externalforce applied to the system. The last component defines the forced oscillations following the external force'schange law. This result shows that the oscillations of the vibration system are not strictly harmonic, which isconfirmed by the provided graphs. The dynamics of the "machine-medium" vibration system, consideringresistance forces, are studied, and analytical dependencies for determining oscillation amplitudes and natural and resonant frequencies are obtained. The results of the amplitude calculations of the vibration platform forvarious heights of compacted concrete mixtures reveal the influence of the resistance coefficient and theratio of oscillation frequency to the wave propagation speed in the mixture. Analysis of the obtained graphsshows that the resistance coefficient has a different effect on the amplitude of oscillations for different heightsof the compacting mixture. Certain mixture height zones of the vibration system "machine-medium" operatein a near-resonant mode. A significant influence on the amplitude is exerted by the wave propagation speed,which is included in the analytical formulas for determining the numerical values of the coefficients accountingfor reactive and active components of resistance.

Hydrological Modeling of Stream Drainage Basins: A Case Study on the Magyaregregy Experimental Catchment in Hungary

This paper presents the field measurements, observations, and numerical simulations conducted for a case study of the Magyaregregy experimental catchment in Hungary. Field measurements included the determination of surface runoff and infiltration intensity on an experimental plot and hydrograph measurements that assessed the ratio between surface and subsurface runoff. Soil moisture measurements both during the infiltration experiments and throughout the experimental catchments gave valuable information regarding this critical parameter. A digital terrain model and the aforementioned field measurements allowed the establishment of a numerical model using HEC-HMS 4.3 for the Magyaregregy experimental catchment process. Although the calibration process was straightforward, considerable difficulties were encountered during the model validation. While the calibration procedure gave appropriate numerical values for most calibrated parameters, it did not provide the proper initial conditions. As a possible solution, the validation period was preceded by a simulation of a relatively long time duration to gain appropriate initial conditions. Finally, the hydrological model’s validation reproduced the measured base flow, as well as the maximum values of discharges. Furthermore, the use of composite-corrected radar data for precipitation values proved to be somewhat unreliable. This supports the principle that data from remote sensing (e.g., radar data) should be used with the utmost care and deliberation as input for hydrological models.

Process parameter optimization in polymer powder bed fusion of final part properties in polyphenylene sulfide through design of experiments

AbstractThe Additive Manufacturing (AM) modality of Laser-Based Powder Bed Fusion of Polymers (PBF-LB/P) is an established method for manufacturing semi-crystalline polymers. Like other AM processes, the selection of PBF-LB/P process parameters is critical as it has direct effect on final part properties. While prior research has been predominantly focused on polyamides (e.g., nylon 12), there exists a gap in exploring how process parameters affect higher performance polymers, such as polyphenylene sulfide (PPS). This work aims to explore the effects of PBF-LB/P process parameters on PPS parts printed via PBF-LB/P. While prior PBF-LB/P parameter research primarily relies on evaluating energy input to the system through a single numerical value of energy density, this study investigates the interplay of the print parameters within the energy density equation. To achieve these goals, an analysis was performed on the influence of the laser power, hatch spacing, and beam velocity on ultimate tensile strength (UTS), modulus, and crystallinity of printed parts. A Taguchi L8 array was used in balancing the print parameter combinations allowing for isolation of variance to the specific factors and interactions. Through this approach, print parameter combinations that improved UTS and modulus were identified. Additionally, the study revealed that numerically equivalent energy densities did not lead to equivalent performance, underscoring the significance for including the constitutive process parameters within the energy density equation when establishing process property relationships in printing with PBF-LB/P.

REASONS COLLEGIATE ATHLETES FEEL UNWELL: SELF-REPORTED SLEEP, NUTRITION, AND STRESS

Introduction: Daily assessments of wellness via short quantitative surveys are becoming a mainstay across professional and collegiate sports. The data typically provide a numerical value on a scale indicating negative and positive scores across several wellness domains. However, little has been reported on why athletes indicate negative scores in wellness. Purpose: This study evaluated reasons reported for low wellness scores in sleep quality, stress, and nutrition, as well as differences in reasons for low wellness among sports and by sex. Methodology: Collegiate athletes from women’s volleyball (n=67), men’s and women’s soccer (n=119), men’s and women’s swimming (n=79), and men’s and women’s basketball (n=87) completed daily assessments of wellness. With a negative wellness score (≤ 3 on a 5-point scale), athletes were prompted to provide a reason for feeling unwell. Results: Chi-square analyses indicated a sex difference for reasons provided for poor sleep and a difference by sport for females and males (all p &lt; .001). Reasons cited for poor sleep quality were late night (23.7%) and “other” (22.3%). For stress, analyses showed differences by sex and sport for females and males (all p &lt; .001). Academic/work stress was the most common reason for poor stress (60.2%). For nutrition, analyses indicated differences by sex (p &lt; .001) and by sport for females (p &lt; .001) and males (p = .008). Consuming fewer than three meals/snacks per day (26.2%) and low fluid intake (21.9%) were the top two reasons for poor nutrition. Conclusions: These data shed light on reasons why athletes experience low wellness. Coaches and support staff can target specific reasons to enhance athlete wellness and the student-athlete experience.

VERIFICATION OF ENERGY CHARACTERISTICS OF A THREE-PHASE BRIDGE COMPENSATION CONVERTER WITH ONE COMMUTATING LINK

The article considers the issue of reliability of the results of analytical calculation of the feedforward control angle of power electric valves and the commutate angle of a three-phase bridge compensating converter of electric energy with one commutating link. It is noted that the value of these angles determines the capabilities of the converter regarding the generation of reactive energy together with the power supply of the consumer of direct current electric energy. Based on the complexity of the analytical calculation of these characteristics, the issue of verification of the obtained results is relevant, which also confirms the adequacy of the applied research methodology. As a tool for achieving the goal of the work, the authors use circuit simulation in the Micro Cap package. The modeling technique is described in detail, the results of modeling several modes of converter operation are presented, and these results are analyzed. A comparative analysis of the numerical values ​​of the control and commutating angles obtained as a result of analytical calculation and circuit modeling of the same modes of converter operation showed that the discrepancy does not exceed 5%. This indicates the adequacy of the applied modeling technique and the acceptable accuracy of the results of analytical calculations. Refer. 3, fig. 3, table 3.

Numerical Solutions for Radiative MHD Casson Nanofluid Flow with Slip, Heat Source, and Chemical Reactions over a Stretching Surface

MHD Casson nanofluid flow in the presence of viscous dissipation, thermal radiation and chemical reaction past a linear stretching surface is investigated. The problem is subjected to slip boundary conditions. The analysis of heat and mass transfer in the presence of Brownian motion and the thermophoretic diffusion effects are incorporated into heat and mass transfer. Nonlinear partial differential equations model governing the problems are transformed into the dimensionless nonlinear ordinary differential equations via similarity variables, then shooting method with sixth-order Runge- Kutta numerical scheme is used to solve the reduce system of Ordinary Differential Equations (ODE). Maple software is used to perform the simulation. The results are presented graphically and in tabular form and the conclusion is drawn that the flow field and other quantities of physical interest are significantly influenced by these parameters. Comparison between the obtained results and previous works are well in agreement. Numerical values of the local skin-friction, Nusselt number and nanoparticle Sherwood number are computed and analyzed. It is noted that the skin-friction coefficient decreases for the larger values of velocity ratio parameter, slip parameter, and increases with an increasing value of Casson parameter. It is also found that enhancing the chemical reaction parameter leads to decrease in concentration profile

SEISMICITY of AZERBAIJAN and ADJACENT TERRITORIES in 2020

In 2020, the network of seismic stations in Azerbaijan continued to operate without changes and consisted of 35 digital stations. Recordings from three Georgian and two Turkish stations were also used in the processing. To estimate the magnitude of earthquakes, the local magnitude ML Аzr was determined. The total num ber of earthquakes recorded by the network of stations in Azerbaijan was 6619, however, the catalog of earthquakes in Azerbaijan and adjacent territories, published in the appendix to this article, provides the parameters of only 207 earthquakes with a magnitude of ML Аzr3.0. The seismic energy released in the territory of “Azerbaijan” in 2020 (E=2.41013 J) increased by an order of magnitude compared to (E=3.311012 J in 2019, with a slight decrease in the number of earthquakes (N=6619 compared from N=6880 in 2019). The most significant earth quakes directly on the territory of the republic in 2020 were the earthquakes on October 25 with ML Аzr=3.4 and November 4 with ML Аzr=4.2, which were felt with an intensity of 4 points in the nearest settlements.

Put Down the ACE: Low Clinical Utility for Angiotensin-Converting Enzyme Levels in Sarcoidosis: A Single-Center Retrospective Cohort Study

Background/Objectives: ACE (angiotensin-converting enzyme) is considered a serological marker of sarcoidosis as elevated levels have been reported in 30–80% of patients. However, elevated ACE levels are also encountered in other medical conditions, and the clinical correlation between ACE levels and disease activity in sarcoidosis is disputable as well. To determine the significance of elevated ACE levels in the diagnosis and follow-up of sarcoidosis patients. Methods: All electronic patient records in which an ACE level was recorded in a large tertiary hospital were identified using a computerized algorithm. Medical diagnoses, ACE numerical values, and clinical data were also automatically extracted. Furthermore, all records with a diagnosis of sarcoidosis were manually reviewed for ascertainment of the diagnosis and searched for additional clinical manifestations and treatment responses. Results: A total of 1416 records with a documented ACE level were found in the database, and 146 of the records had a diagnosis of sarcoidosis in the medical record. However, the diagnosis was excluded in 27 of these cases after a manual review of the records. Elevated ACE levels were most commonly encountered among patients with sarcoidosis, non-Hodgkin’s lymphoma, cirrhosis, and interstitial lung disease. Elevated ACE levels had a positive predictive value of 12.76% and a negative predictive value of 94.6% for the diagnosis of sarcoidosis in our cohort, with a sensitivity of 63.5% and a specificity of 59.5%. Among patients with sarcoidosis, ACE levels around the time of diagnosis were higher than ACE levels in remission. However, a paired analysis did not find a statistically significant difference in ACE levels between the two timepoints. A positive correlation between lack of cardiac involvement and elevated ACE levels was found on multivariate analysis. Conclusions: ACE levels are a non-specific serological marker with low specificity and sensitivity for sarcoidosis and a poor positive predictive value, but with a negative predictive value of 94.6%. Furthermore, elevated ACE levels correlated poorly with disease activity in our cohort.

A Fuzzing Tool Based on Automated Grammar Detection

Software testing is an important step in the software development life cycle to ensure the quality and security of software. Fuzzing is a security testing technique that finds vulnerabilities automatically without accessing the source code. We built a fuzzer, called JIMA-Fuzzing, which is an effective fuzzing tool that utilizes grammar detected from sample input. Based on the detected grammar, JIMA-Fuzzing selects a portion of the valid user input and fuzzes that portion. For example, the tool may greatly increase the size of the input, truncate the input, replace numeric values with new values, replace words with numbers, etc. This paper discusses how JIMA-Fuzzing works and shows the evaluation results after testing against the DARPA Cyber Grand Challenge (CGC) dataset. JIMA-Fuzzing is capable of extracting grammar from sample input files, meaning that it does not require access to the source code to generate effective fuzzing files. This feature allows it to work with proprietary or non-open-source programs and significantly reduces the effort needed from human testers. In addition, compared to fuzzing tools guided with symbolic execution or taint analysis, JIMA-Fuzzing takes much less computing power and time to analyze sample input and generate fuzzing files. However, the limitation is that JIMA-Fuzzing relies on good sample inputs and works primarily on programs that require user interaction/input.

Prioritisation of infectious diseases from a public health perspective: a multi-criteria decision analysis study, France, 2024.

BackgroundWithin the International Health Regulations framework, the French High Council for Public Health was mandated in 2022 by health authorities to establish a list of priority infectious diseases for public health, surveillance and research in mainland and overseas France.AimOur objective was to establish this list.MethodsA multi-criteria decision analysis was used, as recommended by the European Centre for Disease Prevention and Control. A list of 95 entities (infectious diseases or groups of these, including the World Health Organization (WHO)-labelled 'Disease X') was established by 17 infectious disease experts. Ten criteria were defined to score entities: incidence rate, case fatality rate, potential for emergence and spread, impact on the individual, on society, on socially vulnerable groups, on the healthcare system, and need for new preventive tools, new curative therapies, and surveillance. Each criterion was assigned a relative weight by 77 multidisciplinary experts. For each entity, 98 physicians from various specialties rated each criterion against the entity, using a four-class Likert-type scale; the ratings were converted into numeric values with a nonlinear scale and respectively weighted to calculate the entity score.ResultsFifteen entities were ranked as high-priorities, including Disease X and 14 known pathologies (e.g. haemorrhagic fevers, various respiratory viral infections, arboviral infections, multidrug-resistant bacterial infections, invasive meningococcal and pneumococcal diseases, prion diseases, rabies, and tuberculosis).ConclusionThe priority entities agreed with those of the WHO in 2023; almost all were currently covered by the French surveillance and alert system. Repeating this analysis periodically would keep the list updated.

On Non-Linear Differential Systems with Mixed Boundary Conditions

For the constructive analysis of locally Lipschitzian system of non-linear differential equations with mixed periodic and two-point non-linear boundary conditions, a numerical-analytic approach is developed, which allows one to study the solvability and construct approximations to the solution. The values of the unknown solution at the two extreme points of the given interval are considered as vector parameters whose dimension is the same as the dimension of the given differential equation. The original problem can be reduced to two auxiliary ones, with simple separable boundary conditions. To study these problems, we introduce two different types of parametrized successive approximations in analytic form. To prove the uniform convergence of these series, we use the appropriate technique to see that they form Cauchy sequences in the corresponding Banach spaces. The two parametrized limit functions and the given boundary conditions generate a system of algebraic equations of suitable dimensions, the so-called system of determining equations, which give the numerical values of the introduced unknown parameters. We prove that the system of determining equations define all possible solutions of the given boundary value problems in the domain of definition. We established also the existence of the solution based on the approximate determining system, which can always be produced in practice. The theory was presented in detail in the case of a system of differential equations consisting of two equations and having two different solutions.

Data Measurement, Instruments and Sampling.

Data measurement, instrument selection, and sampling are fundamental elements in quantitative research and data collection. Data measurement is the systematic assignment of numeric values or categories to variables to permit measurement with precision and accuracy. Instrument selection involves selecting the right tool or method to collect data effectively and accurately and ensure the reliability and validity of the data. Sampling is the process of selecting a subset of individuals or items from a larger population to best represent that population, free of bias and generalizable. Understanding these key terms ensures that data collected is valid, reliable, and appropriate for future statistical analysis and interpretation.

Investigating the effect of an inclined magnetic fieldon heat and mass transmission in turbulent squeeze flowof UCM fluid between parallel plates

This paper investigates the effects of an inclined magnetic field on heat and mass transfer in turbulent squeeze flow of a viscoelastic fluid with an upper-convected Maxwell model. Squeezing flow is an important phenomenon in various industrial and mechanical processes related to flows between parallel surfaces. Mathematical modelling for the law of conservation of mass, momentum, heat and concentration of nanoparticles is executed. The study employs a system of partial differential equations to describe the flow issue. Governing nonlinear partial equations are reduced into nonlinear ordinary differential equations. The modelled equations are then solved numerically by utilizing the efficient Adams-Moulton method of the fourth order based on the shooting technique using the Fortran programming language. Numerical results are compared with another numerical approach and an excellent agreement is observed. The effects of various factors on the non-dimensional velocity, temperature, and concentration patterns are presented using graphs, while tables are used to assess the numerical values of the skin friction, Nusselt and Sherwood numbers. It is found that the temperature profile decreases as the compression parameter increases but increases with an increase in the Eckert number. The results of this study could be useful in designing heat and mass transfer equipment for applications in viscoelastic fluid flows under an inclined magnetic field.

R as a Game-Changer in Clinical Trial Reporting: Best Practices for TLF Compliance

In clinical trial reporting, the generation of Tables, Listings, and Figures (TLFs) is crucial for data presentation and regulatory submission. Historically, SAS has been the predominant tool for creating TLFs; however, with the increasing adoption of open-source software in the pharmaceutical industry, R has emerged as a viable alternative. This paper presents a comprehensive approach to creating TLFs using R, focusing on the required R packages, strategies for handling missing values, and methods for rounding numeric values. By leveraging R's capabilities, organizations can achieve greater flexibility and efficiency in their reporting processes, potentially reducing costs associated with software licensing and training. Additionally, the integration of R in clinical workflows can facilitate real-time data analysis and enhance decision-making, positioning R as a powerful tool for the pharmaceutical industry’s evolving landscape. This work demonstrates how R can be effectively used for clinical trial reporting, offering significant advantages compared to traditional tools. Keywords: R packages, ggplot2, dplyr,R Shiny for clinical trials, R in clinical trials, Adverse event tables, Data visualization, Data preparation, Regulatory submission, Tables, Listings, and Figures (TLFs)

Number, size, and space associated in a common system by distinct mechanisms.

The spatial numerical association of response codes (SNARC) effect demonstrates that people respond faster to small numbers with their left hand and faster to large numbers with their right hand. The size congruity effect (SCE) refers to the fact that congruent trials between numerical values and physical sizes are faster than incongruent trials. Previous studies have found that the SNARC effect and SCE are independent when magnitudes or sizes are processed explicitly. This study aimed to explore whether number, size, and space are common and distinct mechanisms using an implicit parity judgment task. The results showed that the SNARC effect, SCE, and SNARC-like effect all co-existed. Furthermore, there was a significant interaction between the SNARC effect and SCE, in which the SNARC effect in the SCE-congruent condition was larger than in the SCE-incongruent condition, whereas SCE merely emerged in the SNARC-compatible trials. However, participants responded to small numbers in large size faster than to large numbers in small size with the left hand in SCE-incongruent trials, which reflected that number-space mapping (SNARC effect) was stronger than size-space mapping (SNARC-like effect). These findings provide new evidence for A Theory of Magnitude (ATOM), which suggests that number, size, and space are associated with a common generalized magnitude system through distinct mechanisms.

A text-based, generative deep learning model for soil reflectance spectrum simulation in the solar range (400–2499 nm)

Soil spectral reflectance is a necessary input for land surface and radiative transfer models, and can be used to infer soil properties. Numerous soil reflectance inversion models have been developed based on mechanistic approaches, each with their own limitations. Mechanistic models based on radiative transfer theory are usually based on only a few input soil properties, whereas data-driven approaches are limited by high non-uniformity of available published datasets that severely limits the amount of data usable for model calibration. To address these limitations, a fully data-driven soil optics generative model (SOGM) for simulation of soil reflectance spectra from soil property inputs was developed based on the denoising diffusion probabilistic model (DDPM). The model was trained on an extensive dataset comprising nearly 180,000 soil spectra-property set pairs from 17 published datasets. The model generates soil reflectance spectra from text-based inputs describing soil properties and their values rather than only numerical values and labels in binary vector format, which means the model can handle variable formats for property reporting. Because the model is generative, it can simulate reasonable output spectra based on an incomplete set of available input properties, which becomes more reliable as the input property set becomes more complete. Two additional sub-models were also built to complement the SOGM: a spectral padding model that can fill in the gaps for spectra shorter than the target solar range (400 to 2499 nm), and a wet soil spectra model that can estimate the effects of water content on soil reflectance spectra given the dry spectrum predicted by the SOGM. It can also be easily integrated with other soil–plant radiation models used for remote sensing research such as PROSAIL and Helios 3D plant modeling software. The testing results of the SOGM on new datasets not included in model training demonstrated that the model can generate reasonable soil reflectance spectra based on available property inputs. Results also show soil clay/sand/silt fraction, organic carbon content, nitrogen content, and iron content tended to be important properties for spectra simulation. Inclusion of some trace minerals like nickel as model inputs decreased model performance because of their low concentrations and large propensity for ground-truth measurement error.

Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm-optimized backpropagation neural network.

Ammonia is widely acknowledged to be a stressor and one of the most detrimental gases in animal enclosures. In livestock- and poultry-breeding facilities, a precise, rapid, and affordable method for detecting ammonia concentrations is essential. We design and develop an electronic nose system containing a bionic chamber that imitates the nasal-cavity structure of humans and canines. The sensors are positioned based on fluid simulation results. Response data for ammonia and ethanol gases and the response/ recovery times of an ammonia sensor under three concentrations are collected using the electronic nose system. Response data are classified and regressed using a sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). The results show that the sensor has a relative mean deviation of 1.45%. The ammonia sensor's output voltage is 1.3-2.05 V when the ammonia concentration ranges from 15 to 300 ppm. The ethanol gas sensor's output voltage is 1.89-3.15 V when the ethanol gas concentration ranges from 8 to 200 ppm. The average response time of the ammonia sensor in the chamber is 13 s slower than that of the sensor directly exposed to the gas being measured, while the average recovery time is 19 s faster. In tests comparing the performance of the SSA-BPNN, support vector machine (SVM), and random forest (RF) models, the SSA-BPNN achieves a 99.1% classification accuracy, better than the SVM and RF models. It also outperforms the other models at regression prediction, with smaller absolute, mean absolute, and root mean square errors. Its coefficient of determination (R2) is greater than 0.99, surpassing those of the SVM and RF models. The theoretical and experimental results both indicate that the proposed electronic nose system containing a bionic chamber, when used with the SSA-BPNN, offers a promising approach for detecting ammonia in livestock- and poultry-breeding facilities.

CALCULATION OF THERMODYNAMIC TEMPERATURES OF CHEMICAL REACTIONS OF STEPWISE IRON REDUCTION PROCESS FROM HEMATITE BY SOLID CARBON

The results of thermodynamic analysis of chemical reactions of stepwise reduction of iron from hematite by solid carbon are presented. The aims of the work are to obtain our own expressions for calculating the numerical values of Gibbs free energy depending on temperature using tabular values of standard enthalpies of formation and entropies of inorganic substances, as well as graphical dependences of Gibbs energy on temperature using formulas from literary sources and using the obtained expressions. Numerical values of boundary temperatures are obtained, above which chemical reactions of stepwise reduction of iron from hematite by solid carbon can thermodynamically proceed. It has been established that: the reduction of magnetite (Fe3O4) from hematite (Fe2O3) by solid carbon C is thermodynamically possible above the boundary temperature, the numerical value of which, according to the obtained formula, is 270°; the reduction of wustite (FeO) from magnetite (Fe3O4) by solid carbon C is thermodynamically possible above the boundary temperature, the numerical value of which, according to the obtained formula, is 658°C; the reduction of iron (Fe) from wustite (FeO) by solid carbon C is thermodynamically possible above the boundary temperature, the numerical value of which, according to the obtained formula, is 703°C, and according to formulas, taken from literary sources, is 774°C, 690°C, 680°C and 609°C, respectively, for each formula. Despite the fact that thermodynamics allows all these chemical reactions to occur above the certain above-mentioned temperature values, each of the reactions of stepwise reduction of iron from its oxides by solid carbon in a shaft reduction furnace either occurs at higher temperatures, and, which is quite obvious, with a change in the aggregate state of the reacting (initial) substances or at least one of them (given that FeO forms low-melting compounds with SiO2, this will be the reaction of reduction of iron from wustite), or does not occur at all (given that Fe2O3 and Fe3O4 do not form low-melting compounds with SiO2, and their melting temperatures are greater than 1500°C, these will be the reactions of reduction of magnetite from hematite and reduction of wustite from magnetite).