Efficient Use Research Articles

Optimal strategy to reduce energy waste in an electricity distribution network through direct/indirect bulk load control

In recent decades, the ever-increasing demand for electricity in large cities is leading the electricity distribution network (EDN) to an operational state of fatigue, especially at peak load times. In this context, load congestion, technical losses, and voltage deviations across the EDN can contribute to the high waste of electricity as well as to the worsening of the supply service. To face this problem, this paper proposes a mixed integer linear programming (MILP) model that aims to reshape the demand profile (i.e., load reduction in peak periods without load rebound in the remaining periods of the day) of total consumers while the voltage deviations and technical losses are minimized. In the proposed model, the demand profile reshaping is carried out through direct (DC) and indirect (IC) bulk control of residential, commercial, and industrial loads, while the load factor (LF), i.e., indicator related to the efficient use of electricity, is improved. Due to the scheduling of these loads at certain times of the day, the occurrence of voltage deviations and technical losses can be mitigated by the efficient control of capacitor banks (CBs). To corroborate the applicability of the proposed MILP model, the 33-node IEEE test system was used. The results show the technical and economic gains for the distribution company (DISCO) and the total number of consumers.

Thoughts on sustainability in the use of iodinated contrast media in CT: a practice-oriented review based on the example of a hospital and a private practice.

Iodinated contrast media (CM) have become indispensable in computed tomography (CT), angiography, and cardiac cathlab as well as in other X-ray-based procedures, for example in urology. In this context, iodinated CM are released into the environment in particular via patient excretions along with other trace substances. At the same time, the use of iodinated CM also involves CM leftovers as well as packaging and consumables.In order to reduce the discharge of iodinated CM into the environment and to promote efficient use of resources, awareness of the sustainable and responsible use of iodinated CM and associated consumables is essential. A number of effective measures can contribute to this in the short, medium, and long term. Based on the literature and quantitative data from our own routine, aspects of sustainability when dealing with CM in computed tomography are discussed in this review using the example of a hospital and a private practice.When planning and performing contrast-enhanced CT examinations, personalized CM protocols can make CM use more efficient. Some CM manufacturers offer recycling programs for CM leftovers. The collection of CM excretions after CM injections using urine bags might have a major impact on reducing the discharge of iodinated CM into the environment. In addition, responsible use of consumables and packaging material, in particular the use of multi-patient systems, can make a valuable contribution to waste avoidance and resource conservation. All of these measures can ultimately be fully effective in terms of protecting the environment and resources if they can be implemented on a broad basis. For this purpose, an even greater focus on the topic of sustainability among all parties involved is desirable. · Sustainable and responsible use of iodinated contrast media is desirable.. · Various measures can be taken today to reduce the environmental impact and conserve resources.. · CM use can be made more efficient by optimizing contrast-enhanced CT examinations.. · Recycling programs for CM leftovers enable their further use.. · Urine bags might have a major impact on reducing the environmental impact..

Biotechnological Utilization of Agro-Industrial Residues and By-Products-Sustainable Production of Biosurfactants.

The importance and interest in the efficient use and valorization of agro-industrial residues and by-products have grown due to environmental problems associated with improper disposal. Biotechnological production processes, including microbial biosurfactant production, represent a sustainable way to utilize agro-industrial residues and by-products, which are applied as substrates in these processes. Biosurfactants produced by microorganisms using renewable resources are a viable alternative to traditional petrochemical surfactants and have several potential uses in a wide range of industrial sectors due to their minimal ecotoxicity, easy biodegradability, and moderate production conditions. The common applications of biosurfactants, besides in food industry as food additives and preservatives, are in agriculture, environmental protection, the cosmetics and pharmaceutical industry, wastewater treatment, the petroleum industry, etc. This review aims to summarize the comprehensive scientific research related to the use of various agro-industrial residues and by-products in the microbial production of biosurfactants, as well as to emphasize the present state and the importance of their sustainable production. Additionally, based on the available biosurfactant market analysis datasets and research studies, the current situation in science and industry and the future perspectives of microbial biosurfactant production have been discussed.

A Fast Power Spectrum Sensing Solution for Generalized Coprime Sampling

With the growing scarcity of spectrum resources, wideband spectrum sensing is necessary to process a large volume of data at a high sampling rate. For some applications, only second-order statistics are required for spectrum estimation. In this case, a fast power spectrum sensing solution is proposed based on the generalized coprime sampling. The solution involves the inherent structure of the sensing vector to reconstruct the autocorrelation sequence of inputs from sub-Nyquist samples, which requires only parallel Fourier transform and simple multiplication operations. Thus, it takes less time than the state-of-the-art methods while maintaining the same performance, and it achieves higher performance than the existing methods within the same execution time without the need to pre-estimate the number of inputs. Furthermore, the influence of the model mismatch has only a minor impact on the estimation performance, allowing for more efficient use of the spectrum resource in a distributed swarm scenario. Simulation results demonstrate the low complexity in sampling and computation, thus making it a more practical solution for real-time and distributed wideband spectrum sensing applications.

OXIDATION OF CO WITH THE PARTICIPATION OF ALUMINUM-COPPER-CHROME OXIDE CATALYSTS IN A BED REACTOR

Bed reactors are critical components widely used in industrial processes. Because these reactors often operate under heavy workloads, they face high power and durability requirements.re However, heavy workloads and continuous use can lead to deterioration of the material properties of the reactor. The most important of these problems is the accumulation of carbon monoxide (CO) in the structural components of the reducer. CO is a toxic gas released into the atmosphere as a byproduct of industrial processes. Controlling this gas is important for both environmental and occupational health and safety. In this context, ensuring CO oxidation in fluidized bed reactors is an important area of research to both increase energy efficiency and reduce environmental impacts. This work aims to investigate the catalytic effects of aluminum, copper and chromium to enhance CO oxidation in hot bed reactors. Understanding the effect of incorporating catalytic materials on CO oxidation kinetics will be an important step towards improving reactor stability and performance. The research aims to contribute to a more sustainable and efficient use of fluidized bed reactors in industrial processes. A unique aspect of the study is to systematically investigate the effect of aluminum, copper and chromium on the CO oxidation process in reactors. It should be noted that the results obtained for this purpose are important in terms of their use and potential effects in industrial applications. This research aims to help make industrial processes more sustainable and environmentally friendly by filling the knowledge gaps related to CO control and oxidation in fluidized bed reactors. Keywords: hot-bed reactor, carbon monoxide, oxidation, copper, chromium, aluminum, catalytic effects.

Positive time use: a missing link between time perspective, time management, and well-being.

The notion of satisfaction with the use of one's time has not been operationalized previously. Based on qualitative interviews, we propose a concept of positive time use comprised by four components: self-congruence of daily activities, balance between activities, efficient use of time, and a sense of mastery over one's time. Using data from two UK adult samples (N = 173 and N = 357), we developed a new measure, Positive Time Use Inventory (PTUI), and investigated its structural and convergent validity. The associations of positive time use with balanced time perspective, affect balance, satisfaction with life, sense of coherence, and self-reported satisfaction with time use indicate convergent and discriminant validity of the new measure. Positive time use partially explained the associations of balanced time perspective with subjective well-being and fully mediated the effects of future time perspective and time management on subjective well-being. We propose positive time use as a new model of temporal well-being, which brings together the notions of work-life balance, time efficiency, and time mastery in a single comprehensive framework, helping to inform the time management coaching interventions.

From Lab to Bouquet: The Biotechnological Frontier in Modern Floriculture for Sustainable and Resilient Flower Farming

Modern floriculture faces unprecedented challenges in meeting the rising global demand for flowers while addressing environmental concerns and the need for sustainability. This paper explores the transformative role of biotechnology in revolutionizing flower farming practices, offering solutions for sustainable and resilient cultivation. The integration of biotechnological tools such as genetic engineering, tissue culture, and molecular breeding techniques has opened new avenues for enhancing the efficiency and resilience of flower crops. Genetic modification allows the development of varieties with improved traits, such as disease resistance, longer vase life, and enhanced stress tolerance. Tissue culture facilitates the rapid propagation of elite plant material, ensuring consistent and high-quality flower production. Furthermore, molecular breeding enables the precise selection of desirable traits, accelerating the traditional breeding process. The use of molecular markers for disease resistance, flower colour, and fragrance can streamline the development of new flower varieties tailored to market preferences. Additionally, advanced omics technologies, including genomics, transcriptomic, and metabolomics, provide valuable insights into the molecular mechanisms underlying flower development and responses to environmental stress. Biotechnological interventions extend beyond genetic improvements, encompassing sustainable cultivation practices. Precision agriculture, enabled by sensor technologies and data analytics, optimizes resource utilization, minimizing environmental impact. Smart irrigation systems, nutrient management, and pest control strategies contribute to the efficient use of resources and reduced ecological footprint. The biotechnological frontier in modern floriculture not only addresses current challenges but also positions the industry to adapt to future uncertainties. Climate change, emerging pests, and shifting market demands necessitate resilient flower farming systems. Biotechnology offers the tools to develop adaptable flower varieties and sustainable production methods, promoting long-term ecological and economic viability.

Clarifying Cognitive Control Deficits in Psychosis via Drift Diffusion Modeling and Attractor Dynamics.

Cognitive control deficits are prominent in individuals with psychotic psychopathology. Studies providing evidence for deficits in proactive control generally examine average performance and not variation across trials for individuals-potentially obscuring detection of essential contributors to cognitive control. Here, we leverage intertrial variability through drift-diffusion models (DDMs) aiming to identify key contributors to cognitive control deficits in psychosis. People with psychosis (PwP; N = 122), their first-degree biological relatives (N = 78), and controls (N = 50) each completed 120 trials of the dot pattern expectancy (DPX) cognitive control task. We fit full hierarchical DDMs to response and reaction time (RT) data for individual trials and then used classification models to compare the DDM parameters with conventional measures of proactive and reactive control. PwP demonstrated slower drift rates on proactive control trials suggesting less efficient use of cue information. Both PwP and relatives showed protracted nondecision times to infrequent trial sequences suggesting slowed perceptual processing. Classification analyses indicated that DDM parameters differentiated between the groups better than conventional measures and identified drift rates during proactive control, nondecision time during reactive control, and cue bias as most important. DDM parameters were associated with real-world functioning and schizotypal traits. Modeling of trial-level data revealed that slow evidence accumulation and longer preparatory periods are the strongest contributors to cognitive control deficits in psychotic psychopathology. This pattern of atypical responding during the DPX is consistent with shallow basins in attractor dynamic models that reflect difficulties in maintaining state representations, possibly mediated by excess neural excitation or poor connectivity.

Evaluating the Effect of Deficit Irrigation on Yield and Water Use Efficiency of Drip Irrigation Cotton under Film in Xinjiang Based on Meta-Analysis.

Water scarcity constrains the sustainable development of Chinese agriculture, and deficit irrigation as a new irrigation technology can effectively alleviate the problems of water scarcity and water use inefficiency in agriculture. In this study, the drip irrigation cotton field under film in Xinjiang was taken as the research object. Meta-analysis and machine learning were used to quantitatively analyze the effects of different farm management practices, climate, and soil conditions on cotton yield and water use efficiency under deficit irrigation, to investigate the importance of the effects of different factors on cotton yield and water use efficiency, and to formulate appropriate optimization strategies. The results showed that deficit irrigation significantly increased cotton water use efficiency (7.39%) but decreased cotton yield (-15.00%) compared with full irrigation. All three deficit irrigation levels (80~100% FI, 60~80% FI, and 40~60% FI; FI: full irrigation) showed a significant decrease in cotton yield and a significant increase in water use efficiency. Under deficit irrigation, cotton yield reduction was the smallest and cotton water use efficiency increased the most when planted with one film, two tubes, a six-row cropping pattern, an irrigation frequency ≥10 times, a nitrogen application of 300~400 kg·ha-1, and a crop density ≥240,000 per hectare, and planted with the Xinluzhong series of cotton varieties; deficit irrigation in areas with average annual temperature >10 °C, annual evapotranspiration >2000 mm, annual precipitation <60 mm, and with loam, sandy soil had the least inhibition of cotton yield and the greatest increase in cotton water use efficiency. The results of the random forest showed that the irrigation amount and nitrogen application had the greatest influence on cotton yield and water use efficiency. Rational irrigation based on optimal management practices under conditions of irrigation not less than 90% FI is expected to achieve a win-win situation for both cotton yield and water use efficiency. The above results can provide the best strategy for deficit irrigation and efficient water use in drip irrigation cotton under film in arid areas.

Stability of Traffic Equilibria in a Day-to-Day Dynamic Model of Route Choice and Adaptive Signal Control

Adaptive traffic signal control has the potential to promote the efficient use of road intersections, thus contributing to the effectiveness of urban traffic management schemes. However, the reaction of drivers to repeatedly updated signal settings and the ensuing route choice dynamics may trigger the emergence of various kinds of network instability. In this study, the joint evolution of traffic flows and adaptive signal settings in a road network is investigated at the level of day-to-day dynamics with an explicit focus on the stability issue. We show how a Logit form signal control policy can be used, in interaction with route choice, to counter the emergence of instabilities possibly arising as a consequence of various behavioral factors and network conditions. After providing a general formulation of the model as a discrete time, deterministic nonlinear dynamical system, an explicit analysis of fixed-point stability is carried out for a simple network. Numerical results obtained from the implementation of the model on two example networks are presented in order to support the analytical findings of this study. We conclude that, in an integrated traffic management and information system, a properly calibrated adaptive signal control policy has the potential to offset the destabilizing effect of highly accurate driver information supplied by navigational aids. Our findings also suggest that the Logit-like control policy performs better than the Equisaturation signal setting method, in terms of average intersection delay at equilibrium, for all levels of driver information and travel demand tested in the experiment.

Farmers’ Knowledge on Agricultural Irrigation Programs: The Case of Altınekin District of Konya Province

Climate change-induced droughts have various negative impacts on different sectors, especially on agricultural sector. Altınekin District, where the research was conducted, has the lowest precipitation in Konya Province, therefore is expected to be most affected by drought. For sustainable use of water resources, each stage of agricultural production should be carried out within the framework of a specific program. With this study, knowledge level of farmers engaged in irrigated agriculture in Altınekin district regarding irrigation and irrigation programs they applied were determined through a face-to-face survey. Present findings revealed that 38.7% of the participant farmers are aged 50 years and over and a large proportion of them (54.7%) are primary school graduates. Participant farmers were all (100%) using groundwater resources in agricultural production and 88% of them stated that they did not receive any training on irrigation. While 32% of the farmers participating in the survey stated that they had knowledge about the concept of irrigation program, 68% reported that they did not have any knowledge. Incorrect and improper practices regarding efficient use of irrigation water in the region, especially regarding the irrigation program, were identified and solutions were proposed for these problems.

Optimal Spectral Resolution for Infrared Studies of Solids and Liquids.

Due to a legacy originating in the limited capability of early computers, the spectroscopic resolution used in Fourier transform infrared spectroscopy and other systems has largely been implemented using only powers of two for more than 50 years. In this study, we investigate debunking the spectroscopic lore of, e.g., using only 2, 4, 8, or 16 cm-1 resolution and determine the optimal resolution in terms of both (i) a desired signal-to-noise ratio and (ii) efficient use of acquisition time. The study is facilitated by the availability of solids and liquids reference spectral data recorded at 2.0 cm-1 resolution and is based on an examination in the 4000-400 cm-1 range of 61 liquids and 70 solids spectra, with a total analysis of 4237 peaks, each of which was also examined for being singlet/multiplet in nature. Of the 1765 liquid bands examined, only 27 had widths <5 cm-1. Of the 2472 solid bands examined, only 39 peaks have widths <5 cm-1. For both the liquid and solid bands, a skewed distribution of peak widths was observed: For liquids, the mean peak width was 24.7 cm-1 but the median peak width was 13.7 cm-1, and, similarly, for solids, the mean peak width was 22.2 cm-1 but the median peak width was 11.2 cm-1. While recognizing other studies may differ in scope and limiting the analysis to only room temperature data, we have found that a resolution to resolve 95% of all bands is 5.7 cm-1 for liquids and 5.3 cm-1 for solids; such a resolution would capture the native linewidth (not accounting for instrumental broadening) for 95% of all the solids and liquid bands, respectively. After decades of measuring liquids and solids at 4, 8, or 16 cm-1 resolution, we suggest that, when accounting only for intrinsic linewidths, an optimized resolution of 6.0 cm-1 will capture 91% of all condensed-phase bands, i.e., broadening of only 9% of the narrowest of bands, but yielding a large gain in signal-to-noise with minimal loss of specificity.

Creating a new yellow and blue combination transparent film for Panax ginseng C.A. Meyer growth based on orthogonal designs

Panax ginseng C.A. Meyer originates from old-growth forest environments, where the light intensity and spectrum reaching the forest bed are influenced by the canopy and humidity. In farmlands, suitable light intensity for cultivation is achieved by controlling the light transmission rate using shading nets, while light quality is regulated by a cover of yellow or blue transparent film. Such films have a light quality distinct from that produced by old-growth forests. Herein, a large composite film was developed by alternating small pieces of yellow and blue transparent film. An orthogonal array was used to evaluate the influence of the small transparent film area (STFA), yellow transparent film (YTF) number, and blue transparent film (BTF) number on the associated changes in ginseng in a range of fluorescence-, photosynthesis-, morphology-, and crop quality-related factors. Our results showed that light intensity was influenced primarily by STFA, which caused an overall decrease, while the light quality ratio was affected primarily by YTF number, which increased the proportion of red light and decreased that of blue light, with corresponding influence on different growth parameters. Based on these observations, an improved yellow and blue combination transparent film (YBCTF) with the following characteristics was established: STFA: 15 × 15 cm, YTF: two pieces, and BTF: three pieces. The improved YBCTF facilitated efficient light energy use by the plants, and led to an increase in leaf area, the per leaf photosynthetic rate, dry root weight, and the per root single ginsenoside yield. The findings present a relatively low-cost approach for optimising the light environment of ginseng cultivated in farmland and other crops in large-scale agricultural settings.

A Robust HPLC Approach for Quantitation of Camptothecin in Mesoporous Silica Nanoparticles Matrix and in the Presence of Its Degradation Products.

Camptothecin is a potent anticancer drug used for the treatment of various cancers. The goal of this research investigation was to develop and validate a new stability-indicating HPLC technique for the quantitative assessment of camptothecin in in-house developed mesoporous silica nanoparticles, a novel nanoformulation matrix for the treatment of cancer. The Waters Inertsil® HPLC column (C18) was used for the chromatographic separation, with a flow rate of 1 mL/min, a column oven temperature of 40°C, an injection volume of 10 µL, a detection wavelength of 216 nm, and a 10 min runtime overall. An isocratic blend of phosphate buffer (10 mM, pH7.0) and acetonitrile (60:40, v/v) served as the mobile phase. Various stress conditions including acid, alkali, oxidative, photolytic, thermal, and humidity environments were tested for the quantitative estimation of the camptothecin through the proposed method. The results demonstrated that the proposed method is specific (peak purity ≥0.999), accurate (99.69-100.64% w/w), precise (RSD, % <2.0), and sensitive (LOD-0.17 µg and LOQ-0.56 µg) in accordance with ICH guideline Q2 (R1). Any unidentified degradation products did not interfere with the drug's estimation. Furthermore, the current method of analysis has eliminated any excipient interference from the matrix effect caused by the numerous excipients of the formulation matrix. To quantify camptothecin for routine assay purposes, this research work offers a novel and straightforward HPLC methodology with optimized chromatographic parameters, contributing to the research and development community while ensuring an appropriate and efficient use of the drug through a variety of nanoformulation for cancer treatment. The stability-indicating HPLC method was found to be specific and suitable for routine analysis of camptothecin. The absence of any interference from excipients was confirmed by forced degradation studies.

Seismic performance of a frame‐supported shear wall over‐track building through shaking table test

SummaryThis research deals with a frame‐supported shear wall for urban over‐track building of vehicle depot in Chisha, Guangzhou, China, which is characterized by its remarkable height of 160.8 m. Technical issues are commonly encountered in these kinds of buildings due to discontinuous vertical structural rigidity, large podium, and structural transition. These challenges significantly impact the engineering process, especially when the rigidity difference between transfer story exceeding the threefold, as well as the building height exceeds limit as in code. In this paper, a shaking table test was developed based on a 1:10 scaled model of the structure. Using similarity theory, the dynamic similarity relationship was established for the design of the model. Subsequently, the experimental model was constructed with the configuration of critical parameters such as mass design, sensor placement, and seismic test conditions. This was followed by in‐depth analysis, recording component failures and investigating key aspects such as dynamic characteristics, that is, acceleration and displacement responses and shear force distribution under different earthquake intensities. A theoretical seismic response of the prototype structure was derived from the test results. The shaking table tests confirmed that the structure met the stringent seismic design requirements as prescribed in the Chinese standards, with no damage under minor earthquakes, repairability under moderate earthquakes, and collapse prevention under rare earthquakes. The results of the study provide valuable insights along with improvement measures for the design and development of similar urban over‐track buildings, potentially contributing to more efficient land use in urban China.

Societal Involvement in Household Waste Sorting Behavior in the Context of the Circular Economy: A Case Study of Poland

Population growth and the increasing demand for raw materials with the expanding amount of waste in the environment have resulted in the need to change the production–consumption model based on a one-way flow of materials (from raw materials through products to waste). An alternative to the linear model of production and consumption is the circular economy model (CE), which assumes more efficient use of resources, waste recovery (including municipal waste), and the reuse of materials. One of the important elements of this system is recycling, which will not efficiently function without public participation in the waste sorting system. The aim of the survey study was to examine the motivation, knowledge, and behavior of Polish respondents regarding the sorting of household waste and related problems. The survey results showed that almost 90% of respondents declared waste sorting, mostly because of the threat to the environment (34%) and the desire to contribute to the recycling process (34%), despite respondents’ problems with assigning certain types of waste to appropriate containers. This indicates the need for further education in this area, which should be conducted primarily online—the main sources of information about waste sorting, according to the respondents, are social media (33%) and websites (22%). The research results can help in designing educational campaigns both at the national (Ministry of the Environment and non-governmental organizations) and regional (municipal) levels, as these results indicate in which areas citizens have the most problems with waste separation.

Innovations and Technological Development in the Financial Sector of Ukraine: SWOT Analysis and Comparison of Opportunities

In today's conditions, the competitiveness of the economy in the long term depends on sustainable economic growth, improvement of the quality of life and welfare of the population. Achievement of such results is facilitated by the efficient use of the resource, scientific, technical, and financial potential, commercialisation of research and development, and active introduction of innovative goods and services into business practice. In this regard, there is a growing interest of the state and corporate structures in studying the experience of forming innovation systems; financing innovation activities on a global scale; and the country's transition to a new stage of development. Financing of innovation activity in the financial sector can ensure qualitative transformations in all spheres of economic life, so the relevance of this issue can hardly be overestimated. Given the critical relevance of the topic for the Ukrainian economy under martial law, the purpose of the article is to recognise the need to specify the strengths and weaknesses, as well as to diagnose the opportunities and threats to technological development of the financial sector. In order to achieve this goal, the following issues should be addressed: to outline the areas of the introduction of innovations and modern information technologies in the financial sector; to analyse statistical material on the introduction of innovations in the modern financial sector; to analyse the strengths, weaknesses, opportunities, and threats to technological and innovative development of the financial sector. As a result of the study, a statistical analysis was conducted, which showed that the modern financial sector has the potential for significant innovative development, but there are also significant risks in this area. The analysis revealed that the main risks in the area of innovative development of the financial sector are related to data protection and military operations in Ukraine. Therefore, the requirement for further development is a systemic nature and a comprehensive approach to introducing innovations in the financial sector.

Advancing Solar Magnetic Field Extrapolations through Multiheight Magnetic Field Measurements

Nonlinear force-free extrapolations are a common approach to estimate the 3D topology of coronal magnetic fields based on photospheric vector magnetograms. The force-free assumption is a valid approximation at coronal heights, but for the dense plasma conditions in the lower atmosphere, this assumption is not satisfied. In this study, we utilize multiheight magnetic field measurements in combination with physics-informed neural networks to advance solar magnetic field extrapolations. We include a flexible height-mapping, which allows us to account for the different formation heights of the observed magnetic field measurements. The comparison to analytical and simulated magnetic fields demonstrates that including chromospheric magnetic field measurements leads to a significant improvement of our magnetic field extrapolations. We also apply our method to chromospheric line-of-sight magnetograms from the Vector Spectromagnetograph (VSM) on the Synoptic Optical Long-term Investigations of the Sun (SOLIS) observatory, in combination with photospheric vector magnetograms from the Helioseismic Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). The comparison to observations in extreme-ultraviolet wavelengths shows that the additional chromospheric information leads to a better agreement with the observed coronal structures. In addition, our method intrinsically provides an estimate of the corrugation of the observed magnetograms. With this new approach, we make efficient use of multiheight magnetic field measurements and advance the realism of coronal magnetic field simulations.

4.6-Bit Quantization for Fast and Accurate Neural Network Inference on CPUs

Quantization is a widespread method for reducing the inference time of neural networks on mobile Central Processing Units (CPUs). Eight-bit quantized networks demonstrate similarly high quality as full precision models and perfectly fit the hardware architecture with one-byte coefficients and thirty-two-bit dot product accumulators. Lower precision quantizations usually suffer from noticeable quality loss and require specific computational algorithms to outperform eight-bit quantization. In this paper, we propose a novel 4.6-bit quantization scheme that allows for more efficient use of CPU resources. This scheme has more quantization bins than four-bit quantization and is more accurate while preserving the computational efficiency of the later (it runs only 4% slower). Our multiplication uses a combination of 16- and 32-bit accumulators and avoids multiplication depth limitation, which the previous 4-bit multiplication algorithm had. The experiments with different convolutional neural networks on CIFAR-10 and ImageNet datasets show that 4.6-bit quantized networks are 1.5–1.6 times faster than eight-bit networks on the ARMv8 CPU. Regarding the quality, the results of the 4.6-bit quantized network are close to the mean of four-bit and eight-bit networks of the same architecture. Therefore, 4.6-bit quantization may serve as an intermediate solution between fast and inaccurate low-bit network quantizations and accurate but relatively slow eight-bit ones.

Optimizing Energy Efficiency in EAF Steel Production: A Data-Driven Approach

The article’s main research mission is making predictions about energy usage within an EAF steel production operation and being able to reliably predict energy consumption. Besides, we analysed the relationship between energy consumption in electric arc furnace (EAF) production processes by the method of data mining, so we could obtain accurate forecasts to optimize production costs and maximize energy efficiency. Last but not least, by using decision tree, random tree algorithms and multilayer perceptron models, we can easily achieve the intended goals of efficient use of energy and provide a better plan for electric arc furnace (EAF).