Modeling Experiments Research Articles

An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features

Accurate prediction of natural gas purchase volumes is crucial for both the economy and the environment. It not only facilitates the rational allocation of resources for companies but also helps to reduce operational costs. Although existing prediction methods have achieved some success in addressing the nonlinear relationships in natural gas purchases, there remains potential for further improvement. To address this issue, a stacking ensemble learning model was developed to enhance the ability to handle complex nonlinear problems. This model integrates diverse algorithms and incorporates weather factors, while regionalizing characteristics of natural gas usage, thereby achieving accurate forecasts of natural gas purchase volumes. We selected three distinctly different base models—Informer, multiple linear regression (MLR), and support vector regression (SVR)—for our research. By conducting four different feature combination experiments for each base model, including weather, time, regional, and usage features, we constructed 12 foundational models. Subsequently, we integrated these base models using a meta-learner to form the final stacking ensemble model. The experimental results indicate that the stacking ensemble model outperforms individual models across key metrics, including R2, MRE, and RMSE. Notably, the R2 values improved by 4–15% compared to the 12 base models. The model was subsequently applied to predict natural gas purchase volumes in Pi County, Chengdu, China. In November 2024, a side-by-side comparison of the predicted and actual data revealed a maximum error of just 5.39%. This exceptional accuracy effectively meets forecasting requirements, underscoring the model’s predictive strength in the energy sector.

A Method for Imaging the Ischemic Penumbra with MRI using IVIM.

In acute ischemic stroke, the amount of "local" CBF distal to the occlusion, i.e. all blood flow within a region whether supplied antegrade or delayed and dispersed through the collateral network, may contain valuable information regarding infarct growth rate and treatment response. DSC CBF using a local arterial input function (AIF) is one method of quantifying local CBF (local-qCBF) and correlates with collaterals. Similarly, intravoxel incoherent motion MRI (IVIM) is "local", with excitation and readout in the same plane, and a potential alternative way to measure local-qCBF. The purpose of this work was to compare IVIM local-qCBF against DSC local-qCBF in the ischemic penumbra, compare measurement of perfusion-diffusion mismatch (PWI/DWI), and examine if local-qCBF may improve prediction of final infarct. Eight experiments in a pre-clinical canine model of middle cerebral artery occlusion were performed; native collateral circulation was quantified via x-ray DSA 30 minutes post-occlusion, and collateralization was subsequently enhanced in a subset of experiments with simultaneous pressor and vasodilator. IVIM and DSC MRI were acquired 2.5hr post-occlusion. IVIM was post-processed to return local-qCBF from fD*, water transport time (WTT) from D*, diffusion from D, and the PWI/DWI mismatch. These were compared with DSC parameters processed first with a standard global-AIF and then with a local-AIF. These DSC parameters included time-to-maximum, local MTT, standard-qCBF, local-qCBF and PWI/DWI mismatch. Infarct volume was measured with DWI at 2.5hrs and 4hrs post-occlusion. 2.5hr post-occlusion, IVIM local-qCBF in the non-infarcted ipsilateral territory strongly correlated with DSC local-qCBF (slope=1.00, R2=0.69, Lin's CCC=0.71). Correlation was weaker between IVIM local-qCBF and DSC standard-qCBF (R2=0.13). DSC localqCBF and IVIM local-qCBF in the non-infarcted ipsilateral territory both returned strong prediction of final infarct volume (R2=0.78, R2=0.61 respectively). DSC standard-qCBF was a weaker predictor (R2=0.12). The hypoperfused lesion from DSC local-qCBF and from IVIM local-qCBF both predicted final infarct volume with good sensitivity and correlation (slope=2.08, R2=0.67, slope=2.50, R2=0.68 respectively). The IVIM PWI/DWI ratio was correlated with infarct growth (R2=0.70) and WTT correlated with DSC MTT (R2=0.60). Non-contrast IVIM measurement of local-qCBF and PWI/DWI mismatch may include collateral circulation and improve prediction of infarct growth. AIF: arterial input function, IVIM: intravoxel incoherent motion, qCBF: quantitative cerebral blood flow, WTT: water transport time, MCAO: middle cerebral artery occlusion, MD: mean diffusivity.

Learning Outcomes: How is the Experimentation of the AIR Learning Model?

This study examines how the experimentation of the Auditory, Intellectually, Repetition (AIR) learning model impacts students' learning outcomes in the Islamic Cultural History (SKI) subject at MTs Negeri 1 Bandar Lampung. The research is motivated by students' learning outcomes that have not met the Minimum Competency Criteria (KKM), which may be due to limitations in teaching methods and the influence of other external factors. This study employs a quantitative approach, with the population consisting of all eighth-grade students. The sample includes class VIII(A) as the experimental group and class VIII(B) as the control group. The data were analyzed using an independent t-test, yielding a final significance value of 0.070. This indicates that there is no statistically significant difference between the experimental and control groups. These results suggest that the AIR learning model does not produce significantly different learning outcomes compared to conventional teaching methods in this context. Therefore, further research is needed to optimize the application of the AIR learning model in the Islamic Cultural History (SKI) subject.

Potential Diagnostic Biomarkers in Heart Failure: Suppressed Immune-Associated Genes Identified by Bioinformatic Analysis and Machine Learning

Heart failure (HF) threatens tens of millions of people’s health worldwide, which is the terminal stage in the development of majority cardiovascular diseases. Recently, an increasing number of studies have demonstrated that bioinformatics and machine learning (ML) algorithms can offer new insights into the diagnosing and treating HF. To further discover HF diagnostic genes, we utilized least absolute shrinkage and selection operator (LASSO) and Support Vector Machine (SVM) to identify novel immune-related genes. The HF dataset was obtained from the gene expression omnibus (GEO) database and three candidate genes (LCN6, MUC4, and TNFRSF13C) were finally screened. In addition, the myocardial infarction (MI) modeling experiments on mice were performed to validate the expression of LCN6, MUC4, and TNFRSF13C on experimental HF mice. Altogether, these three candidate genes are promising targets for the prediction of HF with immunological perspective.

Spatiotemporal modeling and projection framework of rainfall-induced landslide risk under climate change

Global warming is expected to exacerbate extreme rainfall events, potentially increasing the risk of landslides. While landslides have been extensively studied, much of the focus has been on developing static frameworks for landslide susceptibility, with relatively little exploration of spatiotemporal modeling. Furthermore, previous studies have often overlooked the spatiotemporal impacts of climate change and dynamic socio-economic factors on landslide susceptibility and risk. This has resulted in a lack of understanding of how landslide risk will evolve in the future. Consequently, this study proposes a modeling approach to simulate the dynamics of landslide susceptibility and exposure population over the next 80 years. The approach involves a series of novel modeling experiments using rainfall-induced landslide data collected over the past decade in Jiangxi Province, using a GAMs that considers the effects of spatial relationships and spatio-temporal cross-validation, with an AUC of 0.885 and an error rate of 15.32%, and combining with the CMIP6 precipitation data to the direct effect of climate change on landslide susceptibility. In addition, a dynamic risk prediction model combining static and dynamic populations was developed to provide a more comprehensive understanding of future landslide impacts. This research framework serves as a scientific foundation and valuable reference for comprehending the effects of climate change on landslide hazards and their management in urban planning and risk mitigation. It aims to inform the development of more effective strategies to mitigate potential losses from future landslide risks.

Some empirical studies for the applications of fractional $ G $-Brownian motion in finance

<p>Since the fractional $ G $-Brownian motion (fGBm) generalizes the concepts of the standard Brownian motion, fractional Brownian motion, and $ G $-Brownian motion, while it can exhibit long-range dependence or antipersistence and feature the volatility uncertainty simultaneously, it can be a better alternative stochastic process in the financial applications. Thus, in this paper, some empirical studies for the financial applications of the fGBm were carried out, where the recent high-frequency data for some selected assets in the financial market are from the Oxford-Man Institute of Quantitative Finance Realized Library. There are two main empirical findings. One was that the H-$ G $-normal distributions associated with the fGBm are more suitable in describing the dynamics of daily returns and increments of log-volatility for these assets than the usual distributions, since they not only characterize the properties of skewness, excess kurtosis, and long-range dependence $ \left(\frac{1}{2} < H < 1\right) $ or antipersistence $ \left(0 < H < \frac{1}{2}\right) $, but also feature the volatility uncertainty. The other one was that the daily return and log-volatility both behave essentially as fGBm with different $ \underline{\sigma}^2 $ and $ \overline{\sigma}^2 $, but Hurst parameters $ H < \frac{1}{2} $, at any reasonable time scale. Then a generalized stochastic model for the dynamics of the assets called rough fractional stochastic volatility model driven by fGBm (RFSV-fGBm) was developed. Finally, some parameter estimates and numerical experiments for the RFSV-fGBm model were investigated and carried out.</p>

Binding mechanism of oligopeptides on solid surface: assessing the significance of single-molecule approach.

This paper addresses the complementarity and potential disparities between single-molecule and ensemble-average approaches to probe the binding mechanism of oligopeptides on inorganic solids. Specifically, we explore the peptide/gold interface owing to its significance in various topics and its suitability to perform experiments both in model and real conditions. Experimental results show that the studied peptide adopts a lying configuration upon adsorption on the gold surface and interacts through its peptidic links and deprotonated thiolate extremities, in agreement with theoretical predictions. Single-molecule force spectroscopy (SMFS) measurements revealed the existence of a wide panel of adhesion forces, resulting from the interaction between individual peptide moieties and the abundant surface sites. We therefore propose methodological developments for sorting the events of interest to understand the peptide adsorption mechanism. Thermodynamic and kinetic aspects of the peptide adsorption are probed using both static and dynamic force spectroscopy measurements. Specifically, we show the possibility of providing a reasonable estimate of the peptide free energy of adsorption ΔadsG° by exploring the fluctuations of the adhesion work, based on the Jarzynski equality, and by using a parametric Gamma estimator. The proposed approach offers a relevant method for studying the different factors influencing the peptide adsorption and evaluating their impact on ΔadsG° as an alternative to exploring adhesion forces that may lead to misinterpretations. This is illustrated by the comparison of the adsorption of two peptides with specific amino acids substitution. Our method provides insights into the overall mechanism by which peptides interact with the surface and allows an integration of the single-molecule versus ensemble-average points of view.

Impact of LITAF on Mitophagy and Neuronal Damage in Epilepsy via MCL-1 Ubiquitination.

This study aims to investigate how the E3 ubiquitin ligase LITAF influences mitochondrial autophagy by modulating MCL-1 ubiquitination, and its role in the development of epilepsy. Employing single-cell RNA sequencing (scRNA-seq) to analyze brain tissue from epilepsy patients, along with high-throughput transcriptomics, we identified changes in gene expression. This was complemented by invivo and invitro experiments, including protein-protein interaction (PPI) network analysis, western blotting, and behavioral assessments in mouse models. Neuronal cells in epilepsy patients exhibited significant gene expression alterations, with increased activity in apoptosis-related pathways and decreased activity in neurotransmitter-related pathways. LITAF was identified as a key upregulated factor, inhibiting mitochondrial autophagy by promoting MCL-1 ubiquitination, leading to increased neuronal damage. Knockdown experiments in mouse models further confirmed that LITAF facilitates MCL-1 ubiquitination, aggravating neuronal injury. Our findings demonstrate that LITAF regulates MCL-1 ubiquitination, significantly impacting mitochondrial autophagy and contributing to neuronal damage in epilepsy. Targeting LITAF and its downstream mechanisms may offer a promising therapeutic strategy for managing epilepsy.

A small cavity for detecting sound-induced flow.

A study is presented of a method for creating an acoustic flow sensor that is generally compatible with current silicon microfabrication processes. An aim of this effort is to obtain a design consisting of a minimal departure from the existing designs employed in mass-produced silicon microphones. Because the primary component in all of these microphones is the cavity behind the pressure-sensing diaphragm, we begin with a study of the acoustic particle velocity within a cavity in a planar surface. The sound within the cavity is caused by the external plane sound wave traveling parallel to the cavity's open surface. It is shown that with suitable dimensions of the cavity, the acoustic particle velocity simultaneously flows inward at one end and outward at the other end of the single open cavity surface. A simple analytical model is presented to estimate the required length and depth of the cavity such that the acoustic particle velocity into and out of the opening is a reasonable approximation to that of a plane traveling sound wave in the free field. Measurements of the acoustic particle velocity into and out of the cavity are in close agreement with both the simple model and a more detailed finite element model. Agreement between two dissimilar modeling approaches and experiments suggests that the dominant features of the system have been accounted for. By redirecting the acoustic particle velocity into and out of the cavity opening rather than the flow being parallel to the plane surface, this configuration greatly facilitates the design and fabrication of structures intended to sense the acoustic flow.

Seismic Resilience of Geogrid Reinforced Concrete Earth-Retaining Wall of Various Incremental Panels Based on Physical and Numerical Modelling

The dynamic response for different earth-retaining walls having geogrid as a reinforcement, combined with cohesionless granular material for backfill to mitigate earth pressure, has been examined through scale-down shaking table experiments and full-scale 3D FE analysis, utilizing ABAQUS as the finite element software. The scale factor is 1/4th for scaled-down. This study included various physical modelling experiments using different geogrid-reinforced earth retaining (GRER) walls (1m height, 7.5cm, thickness, and length 1m). Additionally, comprehensive 3D finite element analysis were conducted with the configurations measuring (4m, height 0.3m, thickness, and length 4m). This study examines hollow prefabricated concrete panels with shear key (PC-W), stone masonry walls of gravity type (GM-W), and traditional reinforced concrete (RC-W) walls. It also presents comparative investigations, such as lateral horizontal displacement of the wall, lateral pressure to the backfill, backfill soil settlement, and settlement of the wall foundation of various (GRER) walls. The accuracy of the Finite Element simulation framework has also been assessed in the shaking table experiment, as well as the FE analyses. According to the results, a PC-W wall with a shear key is the most effective type because it shows more resistance toward displacement. As per the comparison of the test models, GRER walls’ seismic response was more affected by the earthquake waves from the far field having long-term high acceleration values. In contrast, seismic waves from the close field had a smaller impact on the walls’ seismic response. However, the geogrid could improve the GRER seismic resilience deformation. Geogrid layers may reduce backfill pressures and backfill settlements. The geogrids located in the central portion within the reinforced soil and the geogrid roots connected to the walls were essential to the seismic design of the geogrid-reinforced earth retaining wall. To evaluate the reliability of the findings, the models have a predicted R2 variance below 0.1, indicating a consistent relationship between these two variables.

Outer membrane vesicles from genetically engineered Salmonella enterica serovar Typhimurium presenting Helicobacter pylori antigens UreB and CagA induce protection against Helicobacter pylori infection in mice

ABSTRACT Helicobacter pylori causes globally prevalent infections that are highly related to chronic gastritis and even development of gastric carcinomas. With the increase of antibiotic resistance, scientists have begun to search for better vaccine design strategies to eradicate H. pylori colonization. However, while current strategies prefer to formulate vaccines with a single H. pylori antigen, their potential has not yet been fully realized. Outer membrane vesicles (OMVs) are a potential platform since they could deliver multiple antigens. In this study, we engineered three crucial H. pylori antigen proteins (UreB, CagA, and VacA) onto the surface of OMVs derived from Salmonella enterica serovar Typhimurium (S. Typhimurium) mutant strains using the hemoglobin protease (Hbp) autotransporter system. In various knockout strategies, we found that OMVs isolated from the ΔrfbP ΔfliC ΔfljB ΔompA mutants could cause distinct increases in immunoglobulin G (IgG) and A (IgA) levels and effectively trigger T helper 1- and 17-biased cellular immune responses, which perform a vital role in protecting against H. pylori. Next, OMVs derived from ΔrfbP ΔfliC ΔfljB ΔompA mutants were used as a vector to deliver different combinations of H. pylori antigens. The antibody and cytokine levels and challenge experiments in mice model indicated that co-delivering UreB and CagA could protect against H. pylori and antigen-specific T cell responses. In summary, OMVs derived from the S. Typhimurium ΔrfbP ΔfliC ΔfljB ΔompA mutant strain as the vector while importing H. pylori UreB and CagA as antigenic proteins using the Hbp autotransporter system would greatly benefit controlling H. pylori infection.

Targeting Enterobacter cloacae attenuates osteolysis by reducing ammonium in multiple myeloma.

Multiple myeloma (MM)-induced bone disease affects not only patients' quality of life but also their overall survival. Our previous work demonstrated that the gut microbiome plays a crucial role in MM progression and drug resistance. However, the role of altered gut microbiota in MM bone disease remains unclear. In this study, we show that intestinal E. cloacae is significantly enriched in MM patients with osteolysis. Through fecal microbial transplantation and single bacterial colonization experiments in a 5TGM1 MM mouse model, we found that intestinal colonization of E. cloacae promotes osteolysis by increasing circulating ammonium levels. Elevated ammonium promotes osteoclastogenesis by increasing Trap protein levels in osteoclast precursors and by acetylating and stabilizing CCL3 protein in MM cells. Inhibition of ammonium synthesis, using E. cloacae with a deleted dcd gene, along with probiotic supplementation, alleviated osteolysis in MM. Overall, our work suggests that E. cloacae promotes osteolysis in MM by synthesizing ammonium. This establishes a novel mechanism and potential intervention strategy for managing MM with osteolysis.

Earthquake Nucleation and Slip Behavior Altered by Stochastic Normal Stress Heterogeneity

AbstractIn recent laboratory experiments, varying nucleation locations of accelerating slip with changing nucleation lengths were observed. Spatial variations in effective normal stress, due to the controlling influence on fault strength and fracture energy, play an important role. We quantitatively explain how spatially heterogeneous effective normal stresses affect earthquake nucleation and slip behavior. We simulate a meter‐scale laboratory experiment in a numerical earthquake sequence model with stochastically variable normal stresses. We identify five regimes of earthquake nucleation and slip behaviors, controlled by the ratio of the heterogeneity wavelength to the nucleation length . When , full ruptures are observed. Slip rates and recurrence intervals are similar to those on homogeneous faults with comparable averaged normal stress. When , slow slip events and partial ruptures occur frequently and the nucleation length of each earthquake depends on the local stress level. We find locations of nucleation and arrest in both low and high normal stress regions (LSR and HSR, respectively) when and are of the same magnitude. When , earthquakes nucleate in LSRs, and arrest in HSRs. However, HSRs and LSRs switch these roles when . Interestingly, we observe that nucleation migrates from an LSR to its neighboring HSR in one earthquake, when is between the minimum and maximum local nucleation lengths. We observe a large amount of aseismic slip and associated stress drop in the initial LSR, which might be linked to the migration of foreshocks as documented in natural and laboratory observations. This improved understanding of earthquake nucleation is important in estimating the seismic potential of different fault patches for natural and induced seismicity.

Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance. Clinical data in the form of structured diagnostic codes, medications, procedural codes, and demographics were extracted from two large independent health systems and polygenic risk scores (PRS) were generated across all patients of European ancestry with genetic data in the corresponding biobanks. Crohn's disease was studied based on its substantial genetic component, established EHR-based definition, and sufficient prevalence for training and testing. We investigated the impact of choices regarding PRS integration method, training sample, model complexity, and performance metrics. Overall, our results show that including PRS resulted in higher performance but this gain was only robust in situations with limited clinical information. We find consistent performance increases from more compute-intensive models such as random forest, but the impact of other decisions vary by site. This work highlights the importance of considering methodological decision points in interpreting the impact of PRS on prediction performance in clinical models.

MULTILEVEL INVERTER TO GENERATE VOLTAGE WITH COMPLEX HARMONIC COMPOSITION

The paper deals with the problem of forming the desired and controllable harmonic composition of the output curve of a multilevel voltage inverter. The problem is relevant when creating installations for multi-frequency induction heating and metal melting. The purpose of the study is to develop an effective method to form the output voltage of power sources for multi-frequency induction heating installations, the curve of which has a given harmonic spectrum. Materials and methods. The theoretical part of the work was carried out on the basis of the circuit base of multi-level voltage inverters and switching DC converters using numerical analytical methods of studying nonlinear electrical circuits, methods of solving nonlinear differential equations and approximate harmonic analysis, as well as simulation modeling methods using the MATLAB/Simulink mathematical package. Experimental verification of the theoretical results was carried out in laboratory conditions on the example of a multi-level inverter generating a voltage curve with three operating harmonics. ACS758 series sensors and a four-channel RIGOL DS1104Z digital oscilloscope were used to record the results. Research results. Achieving of the purpose is based on the use of a universal multilevel voltage inverter, the circuit scheme of which does not depend on the levels number of the generated curve, which ensures a minimum number of power elements for any complexity of the curve spectrum. The method of forming of the output curve of this inverter consists in alternately connecting of the output capacitors of two direct voltage impulse converters to the input of a single-phase bridge voltage inverter using a transistor switch. In this case, voltages of different parity levels are formed by capacitors in the order of their succession, as a result of which a constant-sign multilevel voltage is formed on the input of the bridge inverter, corresponding to the required alternating-sign multilevel voltage. The law of the transistor switching of the bridge inverter ensures the conversion of its input voltage into a load voltage with a given harmonic composition. The peculiarity of the developed converter control method is that the transistor switching of the bridge inverter is carried out in accordance with the change in the sign of the generated curve. The method contains an algorithm to determine levels values formed by capacitors of impulse converters that realizes the required spectrum of the inverter output curve. The efficiency of the proposed method is illustrated by computer modeling of the converter when voltage with four working harmonics of the spectrum (i.e. the required spectrum harmonics) is generated. The quality indicators of the realized spectrum of the voltage curve are proposed and the analysis results of the influence of the levels number on values of these indicators are presented. The efficiency of the proposed methods is demonstrated experimentally with a laboratory model of the converter. Conclusions. The paper proposes a method to form the output voltage of a power source, the curve of which has a given harmonic, the efficiency of which is confirmed by the results of computer modeling and laboratory experiments. The proposed technical solutions made it possible to generate an output voltage, the spectrum of the curve of which contains four or more harmonics with specified amplitudes with a minimum number of power elements of the circuit. The paper also proposes models of quality indicators of the realized spectrum of the voltage curve and presents the results of the analysis of the influence of the number of levels on the values of these indicators. The developed methodology allows the development in the direction of controlling the spectrum of the generated voltage in real time, as well as non-periodic alternating voltage that changes according to a given program in accordance with the requirements of the technological process.

Exosomes derived from hypoxic mesenchymal stem cells restore ovarian function by enhancing angiogenesis

BackgroundhucMSC-exosomes can be engineered to strengthen their therapeutic potential, and the present study aimed to explore whether hypoxic preconditioning can enhance the angiogenic potential of hucMSC-exosomes in an experimental model of POF.MethodsPrimary hucMSCs and ROMECs were isolated from fresh tissue samples and assessed through a series of experiments. Exosomes were isolated from hucMSCs under normoxic or hypoxic conditions (norm-Exos and hypo-Exos, respectively) and then characterized using classic experimental methods. Based on a series of angiogenesis-related assays, we found that hypo-Exos significantly promoted ROMEC proliferation, migration, and tube formation and increased angiogenesis-promoting molecules in vitro. Histology, immunohistochemistry, and immunofluorescence experiments in a rat model of POF demonstrated that hypoxia pretreatment strengthens the therapeutic angiogenic effect of hucMSC-exosomes in vivo. Subsequently, high-throughput miRNA sequencing, qRT‑PCR analysis, and western blotting were employed to identify the potential molecular mechanism.ResultsWe found that hypo-Exos enhance endothelial function and angiogenesis via the transfer of miR-205-5p in vitro and in vivo. Finally, based on the results of bioinformatics analysis, dual luciferase reporter assays, and gain- and loss-of-function studies, we found evidence indicating that exosomal miR-205-5p enhances angiogenesis by targeting the PTEN/PI3K/AKT/mTOR signalling pathway. These results indicated for the first time that exosomes derived from hypoxia-conditioned hucMSCs strongly enhance angiogenesis via the transfer of miR-205-5p by targeting the PTEN/PI3K/AKT/mTOR signalling pathway.ConclusionsOur findings provide a theoretical basis and demonstrate the potential application of a novel cell-free approach with stem cell-derived products in the treatment of POF.

Модель для контроля качества магнитопроводов линейных электродвигателей на стадии изготовления

The article presents the results of implementing an integrated approach to quality control of linear electric motor inductors at the production stage. The approach is based on the use of mathematical modeling methods and computational experiment. To assess the quality of inductors, it is proposed to use two types of indicators: differential and integral. Differential indicators are determined by conducting a series of experiments with each tooth division of the inductor. Integral indicators allow us to assess the quality of the inductor magnetic circuit as a whole, for which criterion relationships are used. To test the effectiveness of the proposed approach and the reliability of the obtained indicators, a simulation mathematical model of an electric motor inductor with detailing down to one tooth division was developed. Based on this model, an algorithm and a computer program were created that implement the proposed method of quality control during technical testing. The program is written in the Maple software product’s own interpreted programming language and requires the user to enter the parameters of the inductor and power source. As a result of the program, the user receives a conclusion on the quality of the inductor magnetic circuit, as well as numerical values of the differential and integral quality indicators. The materials of the prototype inductor with a high-quality and low-quality magnetic core were used to test the quality criteria using mathematical modeling and computational experiment methods. The results of the experiment confirmed the feasibility of implementing the proposed approach and showed that it adequately reflects the technical quality of inductor magnetic cores. The software product created as a result of the study is intended for technical control of inductor magnetic cores during their production and information support for measures to improve their quality.

Fundamental principles of the effect of habitat fragmentation on species with different movement rates.

Habitat loss and fragmentation have independent impacts on biodiversity; thus, field studies are needed to distinguish their impacts. Moreover, species with different locomotion rates respond differently to fragmentation, complicating direct comparisons of the effects of habitat loss and fragmentation across differing taxa and landscapes. To overcome these challenges, we combined mechanistic mathematical modeling and laboratory experiments to compare how species with different locomotion rates were affected by low (∼80% intact) and high (∼30% intact) levels of habitat loss. In our laboratory experiment, we used Caenorhabditis elegans strains with different locomotion rates and subjected them to the different levels of habitat loss and fragmentation by placing Escherichia coli (C.elegans food) over different proportions of the Petri dish. We developed a partial differential equation model that incorporated spatial and biological phenomena to predict the impacts of habitat arrangement on populations. Only species with low rates of locomotion declined significantly in abundance as fragmentation increased in areas with low (p=0.0270) and high (p=0.0243) levels of habitat loss. Despite that species with high locomotion rates changed little in abundance regardless of the spatial arrangement of resources, they had the lowest abundance and growth rates in all environments because the negative effect of fragmentation created a mismatch between the population distribution and the resource distribution. Our findings shed new light on incorporating the role of locomotion in determining the effects of habitat fragmentation.

Identification of the angles of attack of a hydrodynamic anchor in comparison of numerical and physical experiments

The article is devoted to the urgent task of increasing the effectiveness of rescue operations for the protection of human life at sea by maximizing the drift of rescue vehicles using a hydrodynamic anchor. The paper defines the hydrodynamic characteristics of a hydrodynamic anchor by two different methods: numerical hydrodynamic modeling and physical experiment in a direct experimental pool by pulling a full-scale hydrodynamic anchor with fixed speeds. The identification of the angles of attack of the hydrodynamic armature was carried out in comparison of numerical and physical experiments and the results of calculations of the angles of the working stroke were shown. The angles of installation of the hydrodynamic armature for the angles of attack of the wing, as well as the angles of attack for idling were determined.

Large-scale production of Mansonella perstans infective larvae from engorged Culicoides milnei.

Mansonella perstans is transmitted by Culicoides species and affects hundred millions of inhabitants in about 33 countries in sub-Saharan Africa. It is known that Mansonellosis due to Mansonella perstans do not result in a clear clinical picture, but down-regulates the immunity of patients predisposing them to other diseases like tuberculosis, HIV and malaria or damping vaccine efficacy. However, research about novel drugs against this filarial nematode is missing because of the lack of parasite material. Previous studies have developed in vitro culture systems using infective stage 3 larvae (L3), but these life stages are difficult to obtain and thus the performance of in vitro cultures is restricted and does not allow large-scale testing of drugs or even infection experiments in animal models. Therefore, we aim to establish a platform for the large-scale production of M. perstans infective larvae from engorged Culicoides milnei. Culicoides species were caught in Yangom (Yabassi Health District) in the Littoral Region of Cameroon following a blood meal on six microfilariae-positive donors with different microfilaraemic loads over one year. Engorged midges were reared in the insectarium for up to 14 days and L3 were isolated from the different body parts. In summary, 13,658 engorged Culicoides were collected and reared in the laboratory. We observed an overall predicted survival of 78.5%. Out of the 8,123 survived midges, 7,086 midges belong to C. milnei, from which 2,335 were infected leading to a recovery of 6,310 L3. Moreover, we found the highest survival rates of midges during the early dry season in December with moderate temperatures (23-25°C) and low (2-4mm) or no rainfall. In addition, we observed that midges that fed on donors with high microfilarial loads showed increased mortality. We revealed suitable conditions for the collection and maintenance of engorged Culicoides midges allowing the large-scale production of M. perstans L3. This procedure will provide a platform to produce sufficient parasite material that will facilitate in vitro cultures and the establishment of a murine model of M. perstans, which is important for in-depth investigation of the filarial biology and screening of novel drugs that are effective against this ivermectin-resistant nematode.