Limited Conditions Research Articles

The concept of metamarketing in the experience economy

The new conditions of the digital environment and the formation of the impression economy have caused the transformation of marketing, which involves the introduction of innovative strategies, methods and tools of digital marketing into the activities of enterprises to form a positive immersive experience for customers on the basis of impressions created by enterprises. The aim of the article is to substantiate the concept of metamarketing, which is based on the offer of impressions in the modern conditions of the digital environment. The hypothesis is formulated: the formation of the impression economy in the digital environment has led to the transformation of marketing, which includes digital marketing and impression marketing. The convergence of these types of marketing forms its new concept, in particular metamarketing, which involves the application of digital marketing methods and tools to create and provide impressions in physical and digital space. General scientific and special methods were used: analysis and synthesis, systematic, comparison, logical generalization. The research carried out: substantiation of the importance of impressions for producers and buyers; systematization of strategic directions for ensuring customer impressions; highlighting key elements and principles of the impression economy and formulating the authorʼs definition of the "impression economy in the digital environment"; systematization of the conditions of application, management decisions, limitations and risks of marketing concepts in evolutionary development; substantiation of the concept and formulation of the definition of metamarketing for forming impressions of enterprise customers in the digital environment

Gene ontology defines pre-post- hatch energy dynamics in the complexus muscle of broiler chickens

BackgroundChicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provides a bioenergetic and transcriptomic analyses during the pre-post-hatching period.MethodsWeight and morphology alongside content determination of creatine and glycogen were analysed. Transcriptome identified differentially expressed genes and enriched biological processes associated with hatching muscle development, catabolism, and energy provision. Using gene set enrichment, we followed the dynamics of gene-sets involved in energy pathways of oxidative phosphorylation, protein catabolism, glycolysis/gluconeogenesis, and glycogen metabolism.ResultsResults show several significant findings: (A) Creatine plays a crucial role in the energy metabolism of the hatching muscle, with its concentration remaining stable while glycogen concentration is depleted at hatch and placement. (B) The hatching muscle has the capacity for de-novo creatine synthesis, as indicated by the expression of related genes (AGAT, GAMT). (C) Transcriptome provided insights into genes related to energy pathways under conditions of pre-hatch oxygen and post-hatch glucose limitations (oxidative phosphorylation: NDUF, MT-ND, SDH, UQCR, COX, MT-CO, ATP5, MT-ATP; glycolysis/gluconeogenesis: FBP,G6PC, PFKM; glycogen metabolism: PPP1, PYGL, GYG1). (D) The post-hatch upregulation of protein catabolic processes genes (PSMA, RNF, UBE, FBX), which align with the muscle's weight dynamics, indicates a functional shift from movement during hatching to lifting the head during feeding.ConclusionsThere is a dynamic metabolic switch in the hatching muscle during embryo-to-hatchling transition. When glycogen concentration depletes, energy supply is maintained by creatine and its de-novo synthesis. Understanding the hatching muscle's energy dynamics is crucial, for reducing hatching failures in endangered avian species, and in domesticated chickens.

Дослідження підходів до формування стратегії підвищення інвестиційної привабливості регіону (на прикладі рівненської області України)

The article identifies the main factors influencing the investment attractiveness of the region and groups them in six areas: macroeconomic, political, financial, technological, social and environmental analyses. Isolating the factors influencing the investment attractiveness of the region will allow a comprehensive assessment of various aspects that influence the adoption of sound investment decisions and increase the investment attractiveness of the country or region. The work examines the tools of strategic analysis for assessing the investment attractiveness of the region and their use in the conditions of martial law, and reveals their advantages and disadvantages. The following strategic analysis tools were studied: SWOT analysis, PEST analysis, CANVA, VMOST, SOAR, BKG matrix, Porter's Five Forces, Maturity Models, SPACE analysis and others. The GE/McKinsey matrix was chosen for the analysis of the Rivne region in war conditions, which, in our opinion, is the most effective tool for analyzing the investment attractiveness of the region and will provide a comprehensive approach to market assessment and the competitiveness of the region, will allow prioritization of the region's resources in conditions of limitations and adaptation of industries and production to changes in the external environment, as well as the possibility of assessing the level of risk for each sector of the economy. Since the GE/McKinsey matrix is popular and understandable to international investors, it will help attract international investment and aid to the Rivne region, which has existing natural resources and energy facilities. The McKinsey matrix is based on two factors - market attractiveness and competitiveness. The application of such an analysis in the conditions of the war in Ukraine and economic instability will help identify the main directions for the development, support or rationalization of certain sectors of the economy or enterprises. The paper identifies the main factors influencing the attractiveness of the market and the competitiveness of the industry. The authors studied the dynamics of indicators of socio-economic development of the Rivne region, analyzed them and assessed the attractiveness of the region for investors. Rivne Oblast is located near the border with EU countries and close to economically active regions, namely: Zhytomyr, Volyn, Lviv, Khmelnytskyi and Ternopil. The favorable location of the region will directly affect the development of trade and logistics operations. The Rivne region is known for its amber deposits, forest resources and land for agriculture and other natural resources. These advantages of the region form investment opportunities and attractiveness for attracting investments in the mining industry, agricultural production and wood processing, etc. The GE/McKinsey matrix based on two factors - market attractiveness and competitiveness for key sectors and branches of the economy of the Rivne region was built in the work, and the justification of its choice and benefits in the current conditions for the region was made. The analysis was carried out and strategic conclusions were made for the main directions of the region, and the most attractive industries and sectors of the Rivne region for investment were determined, namely: agriculture, energy and wood processing.

Understanding soil and ecosystem respiration in a dune-meadow cascade ecosystem

Arid and semi-arid regions, which account for more than 30% of the Earth's land area, increasingly dominate the spatiotemporal trends in global carbon fluxes. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the components of the carbon budget in ecosystems under conditions of extreme soil moisture limitations provides a foundation for comprehending the carbon balance in semi-arid ecosystems. The seasonal and diurnal variations in soil respiration (Rs) in semi-mobile dune (SD) and meadow wetland (MW) ecosystems of the Horqin Sandy Land were examined, and the sources of CO2 emissions from Rs were identified using stable carbon isotopes. The responses of Rs and ecosystem respiration (Reco) to environmental temperature, moisture and leaf area index (LAI) were revealed. The results showed that on a seasonal scale, in SD with soil moisture content (Ms) below field capacity (FC), Ms had a greater influence on Rs than soil temperature (Ts) during the growing season. Changes in the LAI during the middle and late growth period affected Rs by altering root carbon supply. In MW, the most favorable Ms for Rs was near FC. The increase in LAI before mowing could effectively promote root and soil microbial respiration, and the decomposition of litter driven by Ts was the main form of Rs at this time. After mowing, root respiration and soil microbial respiration were the main processes contributing to CO2 emissions. On a daily scale, relative humidity (RH) dominated the Rs variation under dry conditions, whereas in other conditions, the Rs was adequately explained by temperature in SD and MW. The overall Reco was larger than Rs, but occasionally Rs was greater than Reco. The effects of temperature, moisture and LAI on Reco and Rs varied with growing season. Adding factors, such as ecosystem type, vegetation growth, water, and heat, to the carbon cycle model can improve predictions of carbon emissions, and aid in further management decisions in arid and semi-arid areas.

Decoding LDPC Codes with a Regular Check Matrix Structure Using the Bit Flip Method

Problem statement: low-density LDPC codes have become very popular in modern communication systems, which make it possible to implement decoders for them in practice. In conditions of severe limitations of equipment performance, the task of searching and researching the characteristics of decoding algorithms for these codes is urgent. The aim of the work is to find a simplified algorithm for decoding LDPC codes and to study the noise immunity of the proposed algorithm. The methods used: to solve this problem computer simulation is used to compare the noise immunity of known decoding algorithms and the proposed algorithm. Scientific novelty: the noise immunity characteristics of the proposed Bit Flip algorithm for decoding LDPC code with a regular structure of the check matrix using gradient descent and the procedure for escaping the local minimum are investigated. Result: a specific variant of the Bit Flip algorithm for LDPC code with a regular structure check matrix using gradient descent and a procedure for escaping the local minimum is proposed. The results of computer simulation are presented. Theoretical significance: the characteristics of noise immunity for the proposed variant of the LDPC code decoding algorithm with a regular structure of the check matrix are investigated. Practical significance: when using the proposed LDPC code decoding algorithm in the receiver, it is possible to calculate the parameters of the communication system based on the available dependencies of the error coefficient on the signal-to-noise ratio.

A dimensional design of tractor seat based on Iranian anthropometric characteristics.

The dimensional seat design process should consider both the users' tasks and their physical characteristics. To use an approach for the design and evaluation of seat dimensions based on the anthropometric characteristics of the Iranian population and the requirements of tractor operators. Some existing equations relating the seat dimensions to anthropometric characteristics were modified according to logical justifications and international standards. A new mathematical-statistical method was used to extract the equations estimating the constant seat dimensions based on the theoretical maximizing of the accommodation level. In addition, an Overall Seat Accommodation Score (OSAS) was developed to represent the mean of seat dimensions accommodation level and dimensional accommodation equality, simultaneously. The dimensional seat design can be affected under different conditions of adjustability, esthetic, and space limitations. However, it was shown that it is possible to improve the design of tractor seats without any significant increase in the final cost and complexity. A new approach was used for tractor seats for a sample of Iranian operators and can be used for the design and evaluation of tractor seats for other target populations.

Scrutinizing black hole stability in cubic vector Galileon theories

In a subclass of generalized Proca theories where a cubic vector Galileon term breaks the U(1) gauge invariance, it is known that there are static and spherically symmetric black hole (BH) solutions endowed with nonvanishing temporal and longitudinal vector components. Such hairy BHs are present for a vanishing vector-field mass (m=0) with a non-zero cubic Galileon coupling β 3. We study the linear stability of those hairy BHs by considering even-parity perturbations in the eikonal limit. In the angular direction, we show that one of the three dynamical perturbations has a nontrivial squared propagation speed c Ω,1 2, while the other two dynamical modes are luminal.We could detect two different unstable behaviors of perturbations in all the parameter spaces of hairy asymptotically flat BH solutions we searched for. In the first case, an angular Laplacian instability on the horizon is induced by negative c Ω,1 2. For the second case, it is possible to avoid this horizon instability, but in such cases, the positivity of c Ω,1 2 is violated at large distances. Hence these hairy BHs are generally prone to Laplacian instabilities along the angular direction in some regions outside the horizon. Moreover, we also encounter a pathological behavior of the radial propagation speeds c r possessing two different values of c r 2 for one of the dynamical perturbations. Introducing the vector-field mass m to cubic vector Galileons, however, we show that the resulting no-hair Schwarzschild BH solution satisfies all the linear stability conditions in the small-scale limit, with luminal propagation speeds of three dynamical even-parity perturbations.

Keeping the market afloat: attachments, circuits of clientele, and personalized commodity exchanges in rural shopkeeping

ABSTRACT This paper questions the conditions of possibility and limits of the most intimate forms of emotional capitalism by studying the everyday working lives of female shopkeepers in rural France. Combining an ethnography of relational work with the sociology of market attachments, it examines how they cultivate customer relationships that border on friendship through affective and caring labor as well as personalized services, without becoming completely entangled in gift-giving exchanges and overwhelming social obligations. Beyond the dynamics of closeness, this article reveals three mechanisms that enable these intimate attachments to operate with little moral or economic tension: a symbolic hierarchization of customers within circuits of clientele; the earmarking of their most personalized commodity exchanges as gifts; and the avoidance of socializing outside the shop and excessive kindness in gift-giving. By expending time and emotions and skillfully balancing closeness with distance, generosity with profitability, shopkeepers can successfully secure a steady income through the personal loyalty of a small group of customers fueled by mutual feelings of affection and indebtedness. Paradoxically, the more emotional capitalism gravitates towards these intimate commercial attachments, the more it requires the simultaneous maintenance of affective and relational distance to preserve the very existence of the market.

Frequency Response of the Diffuse-Charge Dynamics in Electrochemical Systems with a Graphene Electrode

We investigate the frequency response of diffuse-charge dynamics related to a 1:1 symmetric electrolyte containing a graphene electrode by solving the governing Poisson-Nernst-Planck equations subjected to appropriate boundary conditions in the asymptotic limit ε = λ D /H → 0, where λ D is the Debye screening length and H is the half-thickness of the electrolyte. Using the method of matched asymptotic expansion, we first solve the leading order non-linear problem for equilibrium state at a nonzero applied DC voltage in the presence of Stern layer(s). Then, we extend the leading order asymptotic analysis to derive an analytic expression for the impedance of the graphene-based electrochemical cell when a small AC voltage perturbation is added to the applied DC voltage. Finally, we use a suitable scaling of the impedance parameters to expose the impacts of the ion concentration and the DC bias voltage on the frequency response for possible applications involving the graphene-electrolyte interface.

Next-order correction to the Dirac exchange energy of the free electron gas in the thermodynamic limit and generalized gradient approximations

We derive the next order correction to the Dirac exchange energy for the free electron gas in a box with zero boundary conditions in the thermodynamic limit. The correction is of the order of the surface area of the box, and comes from three different contributions: (i) a real-space boundary layer, (ii) a boundary-condition-induced small shift of Fermi momentum and bulk density, and (iii) a long-range electrostatic finite-size correction. Moreover we show that the local density approximation, in addition to capturing the bulk term exactly, also produces a correction of the correct order but not the correct size. Generalized gradient approximation (GGA) corrections are found to be capable of capturing the surface term exactly, provided the gradient enhancement factor satisfies a simple explicit integral constraint. For current GGAs such as B88 and Perdew, Burke and Ernzerhof we find that the new constraint is not satisfied and the size of the surface correction is overestimated by about ten percent. The new constraint might thus be of interest for the design of future exchange functionals.

Mathematical models and algorithms for designing main pipeline for transporting georesources

Relevance. The practical importance of the tasks of utility networks design, namely, the problems of optimizing the structure of the main pipeline according to given criteria, such as efficiency, reliability etc., under conditions of limitations, for example, the compatibility of various types of utilities. Since the main pipeline is laid on the ground with various physical and geological factors, natural and situational conditions, it is advisable to take the reliability of its operation as a global criterion. The task of network optimization is proposed in the form of displaying the main pipeline along the selected routes in three-dimensional space, which considers various existing communications and objects, as well as elevation marks of the area. The paper presents the problems of optimizing networks, both in the continuous case and in the discrete case, and also studies various indicators of the reliability of the operation of the main pipeline. Aim. To develop a model for laying the main pipeline in three-dimensional space, considering the reliability of the pipeline transport; to conduct a comparative analysis for various reliability indicators and topologies of the main pipeline. Objects. Utility communications and networks laid in three-dimensional space. Methods. Calculus of variations, discrete optimization methods, graph theory and hypernet theory methods, network reliability analysis methods. Results. The task of optimizing the main pipeline transport is given taking into account its nesting along the route in three-dimensional space with the choice of an optimization criterion (economic efficiency, reliability, etc.). The problem is presented in the form of continuous and discrete formulations, which is important for its development both within the theory of the calculus of variations and discrete optimization. In this work, the problem was studied within the framework of the theory of graphs and hypernets, which allow, firstly, taking into account the nesting of one structure (main pipeline) into another (a discrete analogue of three-dimensional space) and, secondly, clearly illustrating the results of numerical experiments. It is shown that under the conditions of a given variants for laying a secondary network along the primary channels, various optimal structures are obtained when considering various reliability indicators as a criterion, which can be used to implement a design solution for the construction and operation of pipeline transport for various purposes.

A method to enhance Apache Spark performance based on data segmentation and configuration parameters settings

When using modern big data processing tools, there is a problem of increasing the productivity of using modern frameworks in the context of effective setting of various configuration parameters. The object of the research is computational processes of processing big data with the use of technologies of high-performance frameworks. The subject is methods and approaches to the effective setting of configuration parameters of frameworks in the conditions of limitations of virtualization environments and local resources. The purpose of the study is to improve the performance of Apache Spark and Apache Hadoop deployment modes based on a combined approach that includes preprocess segmentation of input data and setting of basic and additional configuration parameters that take into account the limitations of the virtual environment and local resources. Achieving the set goal involves the following tasks: create a synthesized set of WordCount test data for using input data segmentation methods. Determine the composition of general and specific Apache Spark and Apache Hadoop configuration parameters that most affect the performance of frameworks in Spark Standalone and Hadoop Yarn (FIFO) deployment modes. Justify changes in the values of the configuration parameters (accepted by default) by setting the level of parallelism, the number of partitions of the input file according to the number of processor cores, the number of tasks assigned to each core and the system executor. Conduct experimental research to substantiate theoretical results and prove their use in practice. Methods. The research used the following methods: statistical analysis; a method of generating test data based on defined segmentation characteristics with arbitrary volumes of data; a systematic approach for comprehensive evaluation and analysis of performance of frameworks based on selected configuration parameters. The results. On the basis of the developed system of parameters for evaluating the performance of the studied frameworks, experiments were carried out, which include: the application of the method of segmentation of input data based on the division of the input file into paragraphs (lines) for different values of the ranges of the number of words and the number of letters in each word; setting the main parameters and specific ones, in particular, partitioning and parallelism, taking into account the characteristics of the virtual environment and the local resource. According to the obtained results, a detailed analysis of the use of the proposed methods to improve the performance of the studied frameworks with recommendations for choosing the optimal values of data segmentation parameters and configuration parameters was carried out. You are snowmen. The obtained results of the experiments allow us to conclude that the use of the proposed methods of setting the configuration parameters of Spark and Hadoop will increase the processing productivity: for small files (0.5–1 GB) on average up to 25–30%, for large ones (1.5–2.5 GB ) – up to 10–20% on average. At the same time, the average value of the execution time of one task decreased by 10-15% for files of different sizes and with different number of words in a line.

Development of oil refining and petrochemistry in the Republic of Kazakhstan according to the cluster principle

Oil and gas resources are a non-renewable type of raw material, as a result of which we can talk about their exhaustibility and limitation. The reserves explored so far are limited in volume, many de-posits are at the stage of depletion, which predetermines the need for their careful and rational re-source-saving use. The problems of integrated and rational use of natural resources in order to in-crease their efficiency and reduce the burden on the environment have acquired particular significance in environmental and economic development. Today, contradictions have arisen between limited re-source capabilities and the growing needs of society. Extracted resources are used with low utility. The remaining part is waste, which occupies significant areas; participate in the process of alienation of highly fertile lands; Due to the content of toxic compounds, they cause irreparable harm to the envi-ronment and human health. Industrial production at the present stage is developing at an accelerated pace, as a result of which the need for raw materials is constantly increasing. In conditions of resource limitations of non-renewable raw materials, which include hydrocarbons, there is an urgent need for their rational use. Taking into account the non-renewable and multi-component composition of oil and gas resources, it is necessary to focus on its rational use, aimed at the complete, economically justified extraction of all valuable components contained in it, as well as the use of recyclable materials and production waste, i.e. resource saving. All these aspects directly affect the minimization of environmental risks. The article substantiates the feasibility of the integrated use of hydrocarbon resources in the pro-cess of further development of the domestic oil and gas complex in order to increase its competitive-ness. The authors propose ways to develop petrochemical production that can produce a wide range of commercial products with high added value. The article substantiates the position that with the devel-opment of the petrochemical industry, the oil and gas complex of the republic will acquire the neces-sary stability and will be able to become not only a leading, but also a knowledge-intensive sector of the domestic economy.

Evaluation of the vacuum effect on headspace solid-phase microextraction of volatile organic compounds from aqueous samples using finite element analysis modeling

Headspace solid-phase microextraction (HSSPME) of volatile organic compounds (VOCs) from aqueous samples under vacuum conditions (Vac-HSSPME) allows increasing extraction rates and decreasing detection limits compared to HSSPME under atmospheric pressure. The positive effect of the vacuum on HSSPME of an analyte can be quickly estimated using its Henry's law constant (HLC). According to the two-layer model of evaporation, substantial positive effect of the vacuum can be expected for analytes with HLC lower than 1.6·10−4 atm m3 mol−1 (0.0065 at 25 °C), but the model does not consider possible effects of other important extraction parameters. This research was aimed at the evaluation of the possible effect of vacuum on the equilibration time and extracted amounts of analytes with various HLC and fiber coating-headspace distribution constants (Kfh) using the computational model recently developed in COMSOL Multiphysics® software. It has been proven that HSSPME under vacuum provides faster equilibration of VOCs with all studied Kfh and HLC. The largest vacuum effect on the extracted analyte amount was 3.9–4.0 times at logKfh = 6 and HLC = 10−6–10−3. The substantial (≥1.5 times) vacuum impact should not be expected for analytes with logKfh < 5 for 15-min extraction and logKfh < 5.5 for 30-min extraction. The vacuum impact should be more pronounced when using fiber coatings with a stronger affinity to analytes. The obtained results will be useful for the development of new methods based on Vac-HSSPME and evaluation whether HSSPME is reasonable to conduct under vacuum conditions for faster equilibration and/or lower detection limits.

IMPROVING THE TEMPERATURE IN THE METAL CONVERTER AGGREGATE, WITH USING OF THE MULTI-TIERED TUYERE

The oxygen-converter method is the most common of the industrial production of steel in both Ukraine and the world. According to scientific and statistical sources, from 2017 the fate of oxygen-converting steel in the Ukraine was more than 70 % of the total steel production. To date, in the face of invasion of our sovereign state and a full-scale liberation war in Ukraine, the metallurgical enterprises operating with the oxygen converting way of obtaining steel has conditions for significant resource limitations and increasing the cost of energy, fuel resources. Therefore, there is a need for technological solutions that will increase the energy efficiency of blowing in the bath of converter without the use of external fuel resources and energy. Accordingly was developed and tested in the laboratory with physical high temperature modeling, of the tuyere with multi-tiered construction. The developed technological solution allows to organizeted blowing in the melt for help of supersonic oxygen jets through Laval’s nozzles and forming torches flame of the {CO} to {CO2}, which directly act on the surface of the melt, due to their formation with curtain sonic oxygen jets, who organizated with help of two separate groups of the cylindrical nozzles. Thanks to the video and photography and chemical selection of the melt samples, out gases from the converter and the measurement of the melt temperature, during the entire purification blowing of the melt, established the peculiarities of the conversion of the melt with using of the multi-tiered tuyere in the space of the converter bath. It is confirmed that with the use of the multi-tiered tuyere the course of converting of the melt, as with the classical multi-nozzle tuyere, consists of three main technological periods: the first — slag formation and “ignition of the melt”; the second — intense carbon oxidation; the third — getting of final chemical composition and temperature of the melt. It is established that the main difference in the use of multi-tiered tuyere lies in the more intensive begining and progress of thermodynamic, hydrogasodynamic and cerculation heating processes, along with the appearance of forming torches flame of the {CO} to {CO2} from the moment of “ignition of the melt”. Directly burning {CO} to {CO2} in a mixture of waste gases leads to a release of the large amount of heat 565 kJ/mol O2. At the same time, it should be noted that the temperature during burning {CO} to {CO2} in a mix of the waste converter gases with oxygen streams reaches up to 3000 °C in a created combustion flame torch. The predominant formation of the flame torches {CO} to {CO2} was observed after the “ignition of the melt” at the first period at the expense a lower group of cylindrical nozzles. The highest intensity of the formation of the flame torches {CO} to {CO2} was obtained in the second period at the blowing in the melt in the conditions of intense oxidation of carbon of melt, until the carbon in the melt was from 1.2 % to 0.9 % it is value of the transition concentration. Formation of the flames torches {CO} to {CO2} was be for all sonic jets from cylindrical nozzles of the lower and upper block of the blowing. At the same time, the location of the blowing blocks and the angle of inclination of the cylindrical nozzles to the vertical axis of the multi-tiered tuyere in these blocks are calculated so as to ensure the interaction of the flames torches {CO} to {CO2} with the layers of melt and transfer up to 65 % of the heat formed from flames torches {CO} to {CO2} to the melt. It is established that the use of the multi-tiered tuyere with group of Laval’s nozzles and two groups of cylindrical nozzles was use to create sonic oxygen jets, that allows increases the burning {CO} to {CO2} in the range from 29 % to 43 %, it is exceeding corresponding indicators with the use of a two-tiered tuyere in the range of 14 % to 28 %, and compared to the multi-nozzles tuyere of the classic conctruction from 24 % to 38 %. At the same initial temperature of liquid cast iron and other conditions in laboratory experiments of the high-temperature physical modeling with using a multi-tiered tuyere with group Laval’s nozzels and with two groups of cylindrical nozzles for blowing, the finaly temperature of the liquid semiproduct of the steel was higher comparatively with use classic multi-nozzles tuyere, only thanks to increasing burning {CO} to {CO2} without the use of external fuel resources and energy during blowing of the melt. Accordingly, this indicates an improvement in the energy efficiency of the converter process with helps of the multi-tiered tuyere. Bibl. 23, Fig. 4.

Biomass production and nutritional efficiency in short rotation eucalypt clone plantations for energy in north-east Brazil

Selecting adapted hybrids with greater efficiency in the use and return of nutrients is essential to ensure the success of forestry activities. Although topics on the nutritional sustainability of eucalypt biomass harvesting have frequently been discussed, few studies have focused on short rotation eucalypt clonal plantations (aimed at energy production), especially in conditions of nutrient scarcity and water limitations in Brazil. Therefore, our objective was to evaluate the nutritional efficiency and sustainability (for nitrogen (N), phosphorus (P) and potassium (K)) of six eucalypt clones in short rotation cultivation in the north-east of Brazil, considering different harvesting scenarios and using the Eucalyptus urophylla species as a reference, which is traditionally planted in the study region. Direct quantification of the biomass of 21 trees of each clone was carried out at 5 years of age. The clones did not affect the accumulation of total biomass (on average, 199.9 Mg ha−1). The 1296 and 1355 clones provided lower biomass export and greater nutritional efficiency, favouring an increase in the potential number of rotations (PNR) for P and a reduction in the N removal rate (RR). However, the VM58 clone showed higher biomass export and lower PNR. Thus, clones 1296 and 1355 are more favourable, while clone VM58 is less favourable to nutritional sustainability under the studied conditions. Nitrogen and K may cause productivity limitations in future rotations in whole-tree harvesting systems. Adopting more conservationist harvesting systems with removing only the stemwood or stemwood with bark can optimise the potential of clones, minimise the need to add fertilisers and ensure maintenance of the site’s productivity.

Towards Efficient Neural Decoder for Dexterous Finger Force Predictions.

Dexterous control of robot hands requires a robust neural-machine interface capable of accurately decoding multiple finger movements. Existing studies primarily focus on single-finger movement or rely heavily on multi-finger data for decoder training, which requires large datasets and high computation demand. In this study, we investigated the feasibility of using limited single-finger surface electromyogram (sEMG) data to train a neural decoder capable of predicting the forces of unseen multi-finger combinations. We developed a deep forest-based neural decoder to concurrently predict the extension and flexion forces of three fingers (index, middle, and ring-pinky). We trained the model using varying amounts of high-density EMG data in a limited condition (i.e., single-finger data). We showed that the deep forest decoder could achieve consistently commendable performance with 7.0% of force prediction errors and R2 value of 0.874, significantly surpassing the conventional EMG amplitude method and convolutional neural network approach. However, the deep forest decoder accuracy degraded when a smaller amount of data was used for training and when the testing data became noisy. The deep forest decoder shows accurate performance in multi-finger force prediction tasks. The efficiency aspect of the deep forest lies in the short training time and small volume of training data, which are two critical factors in current neural decoding applications. This study offers insights into efficient and accurate neural decoder training for advanced robotic hand control, which has the potential for real-life applications during human-machine interactions.

Working Smart versus Working Hard: Wireless UT Sensors for Asset Integrity Monitoring

In the 21st century of NDE technology and deployment, monitoring technologies and strategies are completely different than inspection technologies and strategies. Monitoring is no longer sending a technician to a location to take repeated manual data – this is still inspection, just more frequently. Monitoring takes place after a manual/automated inspection has located an anomaly and instrumentation (a sensor in this case), is installed to take recurring readings at that precise location to gather a large sample size of data to be analyzed. These two strategies, when employed in concert, even only on the most critical (10%) circuits/tanks/units, are optimizing asset health, reducing unplanned downtime, and eliminating the need to have people in potentially unsafe situations to the tune of tens of millions of dollars per year. This article will provide real life examples of the ~20% of the best run refineries, chemical, paper, and power plants which have cracked the code and are successfully using an inspect to monitor strategy to change the game of how they implement asset integrity in the 21st century. As you read this article, ask yourself the question, is my facility a part of this ~20%? If not, what can I start doing, and what incremental step changes can I make to my legacy inspection &amp; asset integrity strategy, to use technology to spend my precious budget and resources to be a part of this ~20% in 2024 and beyond? Many asset owners struggle to identify the root cause of fluctuating corrosion rates due to unreliable, infrequent, or sheer lacks of quantity (and quality) of inspection data to make informed decisions on asset health. Facilities worldwide are tasked with monitoring thousands of Condition Monitoring Locations (CMLs) with established NDE techniques such as manual ultrasonic testing and radiography. While these techniques can provide valuable “snapshots” of the condition of particular locations, limitations and inherent errors can compound leading to ill-advised decision making. Manually taken thickness data can vary greatly and result in unwarranted complacency or excessive and costly inspections. Utilizing long range wireless continuous monitoring systems have drastically improved operators understanding of how process changes influence corrosion rates. Installed UT sensors provide near real-time data with a 0.001” accuracy. This influx of data provides a trend line whereas with manually taken data, sometimes only taken a few times a year, only provides a few points scattered across a graph. Asset owners have realized they can use this wealth of new information to validate and discover the effects of operational changes on corrosion rates and make more informed decisions to impact asset extension, retirement, and increasing the efficiency of assets during its useful life.

The Multiscale Hybrid Method with a Localized Constraint. II. Hybrid Equations of Motion Based on Variational Principles

A multiscale modelling framework that employs molecular dynamics and hydrodynamics principles has been developed to describe the dynamics of hybrid particles. Based on the principle of least action, the equations of motion for hybrid particles were derived and verified by using the Gauss principle of least constraints testifying to their accuracy and applicability under various system constraints. The proposed scheme has been implemented in a popular open-source molecular dynamics code GROMACS. The simulation for liquid argon under equilibrium conditions in the hydrodynamic limit (s = 1) has demonstrated that the standard deviation of the density exhibits a remarkable agreement with predictions from a pure hydrodynamics model, validating the robustness of the proposed framework.

Development and validation of a multi-target TaqMan qPCR method for detection of Borrelia burgdorferi sensu lato

Reliable detection of bacteria belonging to the Borrelia burgdorferi sensu lato species complex in vertebrate reservoirs, tick vectors, and patients is key to answer questions regarding Lyme borreliosis epidemiology. Nevertheless, the description of characteristics of qPCRs for the detection of B. burgdorferi s. l. are often limited. This study covers the development and validation of two duplex taqman qPCR assays used to target four markers on the chromosome of genospecies of B. burgdorferi s. l.Analytical specificity was determined with a panel of spirochete strains. qPCR characteristics were specified using water or tick DNA spiked with controlled quantities of the targeted DNA sequences of B. afzelii, B. burgdorferi sensu stricto or B. bavariensis. The effectiveness of detection results was finally evaluated using DNA extracted from ticks and biopsies from mammals whose infectious status had been determined by other detection assays.The developed qPCR assays allow exclusive detection of B. burgdorferi s. l. with the exception of the M16 marker which also detect relapsing fever Borreliae. The limit of detection is between 10 and 40 copies per qPCR reaction depending on the sample type, the B. burgdorferi genospecies and the targeted marker. Detection tests performed on various kind of samples illustrated the accuracy and robustness of our qPCR assays.Within the defined limits, this multi-target qPCR method allows a versatile detection of B. burgdorferi s. l., regardless of the genospecies and the sample material analyzed, with a sensitivity that would be compatible with most applications and a reproducibility of 100% under measurement conditions of limits of detection, thereby limiting result ambiguities.