Model Of Stage Research Articles

Versatile Weight Attack via Flipping Limited Bits.

Many attack paradigms against deep neural networks have been well studied, such as the backdoor attack in the training stage and the adversarial attack in the inference stage. In this article, we study a novel attack paradigm, the bit-flip based weight attack, which directly modifies weight bits of the attacked model in the deployment stage. To meet various attack scenarios, we propose a general formulation including terms to achieve effectiveness and stealthiness goals and a constraint on the number of bit-flips. Furthermore, benefitting from this extensible and flexible formulation, we present two cases with different malicious purposes, i.e., single sample attack (SSA) and triggered samples attack (TSA). SSA which aims at misclassifying a specific sample into a target class is a binary optimization with determining the state of the binary bits (0 or 1); TSA which is to misclassify the samples embedded with a specific trigger is a mixed integer programming (MIP) with flipped bits and a learnable trigger. Utilizing the latest technique in integer programming, we equivalently reformulate them as continuous optimization problems, whose approximate solutions can be effectively and efficiently obtained by the alternating direction method of multipliers (ADMM) method. Extensive experiments demonstrate the superiority of our methods.

Research on the modeling and control mechanism of three-phase cascade rectification stage of non-power frequency transformer

Non-power frequency transformers are essential and important devices for new energy generation and smart grid construction. This article analyzes the working principle of voltage cascade rectifier stage, constructs a mathematical model of three-phase cascade rectifier stage system, and simplifies its model. Finally, the idea of overall control of the voltage loop in the rectifier stage system was derived, and the traditional control method of rectification was directly transplanted into the overall control system of the cascade rectifier stage. At the same time, the characteristics of voltage loop and current loop of cascade rectifier stage system are analyzed, and the relevant control structure block diagram and controller design idea are given, which lays an important theoretical foundation for in-depth study of non-power frequency transformer.

Lithofacies and Depositional Models of the Fine-Grained Sedimentary Rocks of the Albian–Turonian Stage in the Rio Muni Basin, West Africa

The Rio Muni Basin is a hotspot for deep-water oil exploration in West Africa. The discovery of thirteen oil and gas fields, including Ceiba, Akom 1, and Oveng, proves the basin’s excellent exploration prospects, but only limited research has thus far been carried out there. The recent new drilling indicates that there are organic matter-rich fine-grained sedimentary rocks in the Albian and Cenomanian–Turonian stages of the Cretaceous strata. However, the depositional models of organic-rich, fine-grained sedimentary rocks are not clear. The main objectives of this study are as follows: (1) to identify the lithofacies characteristics of fine-grained sedimentary rocks in the Albian–Turonian stages of the Rio Muni Basin; and (2) to establish a depositional model for organic-rich fine-grained sediments. In this study, the mineralogical characteristics of Albian–Turonian fine-grained were determined by means of X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), and thin section analysis. In addition, the integration of mineralogical features with the total organic carbon (TOC) content allows for the recognition of three distinct lithofacies: (1) siliceous-clayey rock, (2) terrigenous clastic mixed fine-grained rock, and (3) lime-mixed fine-grained rock. Based on the evolutionary history of the passive continental margin basins in West Africa and the lithofacies characteristics, the deposition mode of organic-rich fine-grained sedimentary rocks in the Albian–Turonian stages was reconstructed by combining geochemical features with the characteristics of framboidal pyrite. The depositional models for the Albian stage are “continental margin–restricted sea–marine algae–source rocks” with the development of organic-rich fine-grained sedimentary rocks. The depositional models for the Cenomanian–Turonian stage are “continental margin–semiopen sea–mixed-source rocks”. The Albian and Cenomanian–Turonian organic-rich fine-grained sedimentary rocks represent two different deposition modes with restricted sea and semiopen sea conditions. The sedimentary characteristics in the study area during the two periods were both inherited and notably different.

Two-Stage Optimization Model of Centralized Energy Storage Participating in Peak Shaving with Maximum Reserve Capacity and Minimum Carbon Emission of the System

As the proportion of renewable energy increases in power systems, the need for peak shaving is increasing. The optimal operation of the battery energy storage system (BESS) can provide a resilient and low-carbon peak-shaving approach for the system. Therefore, a two-stage optimization model for grid-side BESS is proposed. First, the carbon emission model of thermal power units considering BESS is proposed to describe the ability of the BESS in reducing the carbon emissions. Second, in order to deal with the uncertainty of the photovoltaics and wind forecast errors, a certain capacity of BESS is reserved. The model in the first stage takes the lowest carbon emission of the system as the goal, and the model in the second stage determines the BESS reserve capacity with the objective of minimizing the risk cost of the system. The simulation results show that the carbon emission model of thermal power units with BESS can measure the contribution of energy storage to emission reduction. By setting the reserve capacity of energy storage, the peak-shaving resilience of the system is improved, and the risk of photovoltaics and wind forecast error is reduced.

Investigation of thermal behaviour and synergistic effect in co-pyrolysis of municipal solid waste and sewage sludge through thermogravimetric analysis

Municipal solid waste (MSW) and sewage sludge (SS) co-pyrolysis have the potential to revolutionize waste management and address energy challenges. Consequently, it is crucial to explore the thermal and synergistic effect of MSW, SS and their blends using thermogravimetric analysis. Different blending ratios (MSW90%SS10 %, MSW80%SS20 % and MSW65%SS35 %) were analyzed under an inert nitrogen (N2) gas atmosphere, at various heating rates (10,20 and 30 K min−1), from 30 °C to 900 °C. This paper specifically addressed the effect of heating rate and blending ratio on separate and jointed pyrolysis of the two raw materials. The analysis revealed two significant decomposition stages observed in the individual pyrolytic processes and their blends. Results showed that a higher heating rate slowed down the decomposition rate due to less effective heat transfer. The blending ratio of 35 % SS at 20 K min−1 exhibited a positive synergistic effect while an antagonistic effect was observed in another mixing ratio. Activation energy determined using the Coats-Redfern model in the second stage of active pyrolysis for MSW90%SS10 %, MSW80%SS20 % and MSW65%SS35 % was 41.879, 43.365 and 40.271 kJ mol−1 respectively. The negative ΔS (entropy) and positive ΔH (enthalpy) values indicated a decrease in disorder and an endothermic reaction respectively. This finding was consistent with the formation of complex products from the feedstock and the endothermic nature of the pyrolysis process. Therefore, strategic co-pyrolysis optimization of MSW and SS with the precise blending ratio of 35 % sewage sludge and controlled heating rate of 20 K min−1, exhibits substantial potential for advancing eco-friendly waste management practices while enabling effective energy recuperation.

Chronology and problems of the evolution of HIV infection in the Vologda Region in the structure of the North-West of the Russian Federation

Aim. To determine the general patterns and distinctive features of the formation of the HIV epidemic in chronology in various administrative territories of the Vologda Region.Materials and methods. The data of the epidemiological survey maps of HIV infection foci, reports «Causes of mortality of HIV-infected», statistical observations were analyzed: form No. 61 «Information on the contingent of HIV-infected patients», form No. 4 of the Federal State Statistical Observation, forms of the Vologda Regional Center for the Prevention and Control of AIDS and Infectious Diseases, materials of the North-Western District Center for the Prevention and Control of AIDS. Dynamic monitoring of the HIV epidemic in the Vologda Region (since 1995) and evaluation of the effectiveness of the national project to combat HIV infections were carried out.Results and discussion. On the territory of the Vologda Region, the trend of stability of the indicator of HIV infection remains. The prevalence of the population is increasing, accompanied by the identification of patients at late stages with the manifestation of secondary diseases. In the region, the HIV epidemic corresponds to the main trends of the epidemic process in the North-Western Federal District (NWFD) with some differences. The dominant transmission routes are parenteral (39.9% in 2021) and heterosexual. Over the past 5 years, there has been an upward trend in homosexual transmission of infection among men who have sex with a men (MSM), the share of which increased in 2021 by 2 times compared to 2017 and amounted to 3.1%. The detection rate in 2021, calculated for 100 thousand surveyed, in the Vologda Region was 111.3 (in the NWFD — 160.1). The highest detection rate of HIV infection was observed among MSM — 14.3% (in the NWFD — 4.1%), among injecting drug users (IDUs) — 1.0% (in the NWFD — 1.1%), among persons in prison — 1.8% (in the NWFD — 1.8%). One of the main causes of death in HIV-infected patients is the late detection of the disease and the initiation of antiretroviral therapy (ART). During the entire period of observation, the epidemic was most intense in Cherepovets and Vologda, since 2000 there has been a gradual spread of infection with involvement in the process in rural areas.Conclusion. The results obtained demonstrate the importance of implementing different models of the main stages of diagnosis, prevention and treatment of people in urban and rural areas, which is included in the developing concept of personalized HIV medicine. It is necessary to carry out additional measures for the active identification and registration of dispensary patients, the formation of adherence to dispensary monitoring and therapy, the timely appointment of ART, the introduction of new approaches to providing medical care to HIV-infected patients in the districts of the region.

A multi-institutional study to predict the benefits of DEB-TACE and molecular targeted agent sequential therapy in unresectable hepatocellular carcinoma using a radiological-clinical nomogram.

Exploring the efficacy of a Radiological-Clinical (Rad-Clinical) model in predicting prognosis of unresectable hepatocellular carcinoma (HCC) patients after drug eluting beads transcatheter arterial chemoembolization (DEB-TACE) to optimize the targeted sequential treatment. In this retrospective analysis, we included 202 patients with unresectable HCC who received DEB-TACE treatment in 17 institutions from June 2018 to December 2022. Progression-free survival (PFS)-related radiomics features were computationally extracted from HCC patients to build a radiological signature (Rad-signature) model with least absolute shrinkage and selection operator regression. A Rad-Clinical model for postoperative PFS was further constructed according to the Rad-signature and clinical variables by Cox regression analysis. It was presented as a nomogram and evaluated by receiver operating characteristic curves, calibration curves, and decision curve analysis. And further evaluate the application value of Rad-Clinical model in clinical stages and targeted sequential therapy of HCC. Tumor size, Barcelona Clinic Liver Cancer (BCLC) stage, and radiomics score (Rad-score) were found to be independent risk factors for PFS after DEB-TACE treatment for unresectable HCC, with the Rad-Clinical model being the greatest predictor of PFS in these patients (hazard ratio: 2.08; 95% confidence interval: 1.56-2.78; P < 0.001) along with high 6months, 12months, 18months, and 24months area under the curves of 0.857, 0.810, 0.843, and 0.838, respectively. In addition, compared to the radiomics and clinical nomograms, the Radiological-Clinical nomogram also significantly improved the classification accuracy for PFS outcomes, based on the net reclassification improvement (45.2%, 95% CI 0.260-0.632, p < 0.05) and integrated discrimination improvement (14.9%, 95% CI 0.064-0.281, p < 0.05). Based on this model, low-risk patients had higher PFS than high-risk patients in BCLC-B and C stages (P = 0.021). Targeted sequential therapy for patients with high and low-risk HCC in BCLC-B stage exhibited significant benefits (P = 0.018, P = 0.012), but patients with high-risk HCC in BCLC-C stage did not benefit much (P = 0.052). The Rad-Clinical model may be favorable for predicting PFS in patients with unresectable HCC treated with DEB-TACE and for identifying patients who may benefit from targeted sequential therapy.

Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging

BackgroundPrecise categorization of pressure injury (PI) stages is critical in determining the appropriate treatment for wound care. However, the expertise necessary for PI staging is frequently unavailable in residential care settings. ObjectiveThis study aimed to develop a convolutional neural network (CNN) model for classifying PIs and investigate whether its implementation can allow physicians to make better decisions for PI staging. MethodsUsing 3,098 clinical images (2,614 and 484 from internal and external datasets, respectively), a CNN was trained and validated to classify PIs and other related dermatoses. A two-part survey was conducted with 24 dermatology residents, ward nurses, and medical students to determine whether the implementation of the CNN improved initial PI classification decisions. ResultsThe top-1 accuracy of the model was 0.793 (95% confidence interval [CI], 0.778–0.808) and 0.717 (95% CI, 0.676–0.758) over the internal and external testing sets, respectively. The accuracy of PI staging among participants was 0.501 (95% CI, 0.487–0.515) in Part I, improving by 17.1% to 0.672 (95% CI, 0.660–0.684) in Part II. Furthermore, the concordance between participants increased significantly with the use of the CNN model, with Fleiss’ κ of 0.414 (95% CI, 0.410–0.417) and 0.641 (95% CI, 0.638–0.644) in Parts I and II, respectively. ConclusionsThe proposed CNN model can help classify PIs and relevant dermatoses. In addition, augmented decision-making can improve consultation accuracy while ensuring concordance between the clinical decisions made by a diverse group of health professionals.

Design, modeling, and analysis of a novel XY micro-displacement scanning stage with an elliptical compliant restraint mechanism

This paper presents a novel piezoelectric XY micro-displacement scanning stage (MDSS), which features a parallel structure based on compliant mechanisms and has a compact configuration. Since the coupling problem between two motion axes, an innovative elliptical compliant restraint mechanism (ECRM) with a compact layout is proposed and utilized in XY MDSS to obtain high motion accuracy. And the XY MDSS can realize compact structure and lower input stiffness for a large workspace owing to the ECRM simultaneously. Due to the limited displacement of the piezoelectric stack actuator, compliant amplification mechanism is applied to achieve a large stroke. In order to estimate the static and dynamic characteristics theoretically, Castigliano’s second theorem and Lagrange’s method are utilized to establish the analytical models of the newfangled ECRM, compliant amplification mechanism, and XY MDSS. The finite element analysis and experimental tests are carried out to evaluate the performances of XY XDSS, and the results are all in correspondence with analytic solutions, which further validate the correctness of the analytical modeling methodologies. Experimental results show that the XY MDSS can realize a workspace of 58.8 μm × 51.5 μm with a resonance frequency of 576.5 Hz and nanometer-level resolution. The effectiveness of the designed ECRM is also proved simultaneously, which could well limit the coupling motion. The theoretical studies, finite element analysis, and experimental testing all demonstrate that the designed XY MDSS with ECRM has good performance while having a compact structure.

CT-based deep learning model: a novel approach to the preoperative staging in patients with peritoneal metastasis.

Peritoneal metastasis (PM) is a frequent manifestation of advanced abdominal malignancies. Accurately assessing the extent of PM before surgery is essential for patients to receive optimal treatment. Therefore, we propose to construct a deep learning (DL) model based on enhanced computed tomography (CT) images to stage PM preoperatively in patients. All 168 patients with PM underwent contrast-enhanced abdominal CT before either open surgery or laparoscopic exploration, and peritoneal cancer index (PCI) was used to evaluate patients during the surgical procedure. DL features were extracted from portal venous-phase abdominal CT scans and subjected to feature selection using the Spearman correlation coefficient and LASSO. The performance of models for preoperative staging was assessed in the validation cohort and compared against models based on clinical and radiomics (Rad) signature. The DenseNet121-SVM model demonstrated strong patient discrimination in both the training and validation cohorts, achieving AUC was 0.996 in training and 0.951 validation cohort, which were both higher than those of the Clinic model and Rad model. Decision curve analysis (DCA) showed that patients could potentially benefit more from treatment using the DL-SVM model, and calibration curves demonstrated good agreement with actual outcomes. The DL model based on portal venous-phase abdominal CT accurately predicts the extent of PM in patients before surgery, which can help maximize the benefits of treatment and optimize the patient's treatment plan.

Open Data-Based Village Potential Mapping Model Design in the Tomini Bay Region in the KKN Course

The objectives of this study were: 1) To develop an open data-based village potential mapping model design in the Tomini Bay Region in the KKN course and 2) Test the validity of the open data-based village potential mapping model in the Tomini Bay Region in the KKN course, 3) Testing the effectiveness of the open data-based village potential mapping model in the Tomini Bay Region in KKN courses. The research method used in this study is the Research and Development research method of the Borg &amp; Gall model of model development stages, which include (1) drafting the model, (2) expert and practitioner validation, (3) limited model trial, (4) more comprehensive model trial; and (5) model revision. The subjects of this study were 42 students participating in KKN in the Tomini Bay Region in 5 villages. The quality of the developed product was analyzed with descriptive statistics. The results showed that (1) The design of the open data-based village potential mapping model developed has a very high level of validity with an average value of 0.87 and is feasible to use; (2) The open data-based village potential mapping model developed is practical to use, based on the value of model implementation which reaches an average value of 83.59% with perfect implementation criteria, and gets an excellent response from KKN student participants with an average value of 85.15%, (3) There was an increase in the average score between the pre-test and post-test in the control group, where the average score of the pre-test in the control group was 53.13 while the average score of the post-test in the control group was 73.84. There was a significant increase between the pre-test and post-test in the experimental group, where the average score of the pre-test in the experimental group was 56.65 and the average score of the post-test in the experimental group was 86.06.

FSI Application in the Parametric Analysis of Blade–Disk Connection of Turbojet Engine Compressor

The following paper evaluates the strength properties of the critical area of the turbine rotor stage of a jet engine. This is where the blade is attached to the rotor disk. Important aspects of this issue are characteristic geometrical dimensions and operating factors, e.g., changes in rotor speed. In the article, the strength properties of the rotor stage with a trapezoidal blade–disk connection were analyzed using parametric analysis considering fluid–structure interaction (FSI). Virtual models of the compressor rotor stages were developed, including parametric blade–disk connections and discrete models for FEM (finite element method) and CFD (computational fluid dynamics) analyses. The parametric analysis was aimed at assessing selected geometric parameters in terms of their impact on the maximum stresses in the blade root. The analysis performed shows that by changing the blade’s width and thickness angles at the root, we can influence the value of the maximum stresses in the rotor stage. It was noticed that some combinations of these two parameters may negatively affect the value of the stresses in the rim.

Impacts of exposure to humidex on cardiovascular mortality: a multi-city study in Southwest China

BackgroundMany studies have reported the association between ambient temperature and mortality from cardiovascular disease (CVD). However, the health effects of humidity are still unclear, much less the combined effects of temperature and humidity. In this study, we used humidex to quantify the effect of temperature and humidity combined on CVD mortality.MethodsDaily meteorological, air pollution, and CVD mortality data were collected in four cities in southwest China. We used a distributed lag non-linear model (DLNM) in the first stage to assess the exposure–response association between humidex and city-specific CVD mortality. A multivariate meta-analysis was conducted in the second stage to pool these effects at the overall level. To evaluate the mortality burden of high and low humidex, we determined the attributable fraction (AF). According to the abovementioned processes, stratified analyses were conducted based on various demographic factors.ResultsHumidex and the CVD exposure–response curve showed an inverted “J” shape, the minimum mortality humidex (MMH) was 31.7 (77th percentile), and the cumulative relative risk (CRR) was 2.27 (95% confidence interval [CI], 1.76–2.91). At extremely high and low humidex, CRRs were 1.19 (95% CI, 0.98–1.44) and 2.52 (95% CI, 1.88–3.38), respectively. The burden of CVD mortality attributed to non-optimal humidex was 21.59% (95% empirical CI [eCI], 18.12–24.59%), most of which was due to low humidex, with an AF of 20.16% (95% eCI, 16.72–23.23%).ConclusionsLow humidex could significantly increase the risk of CVD mortality, and vulnerability to humidex differed across populations with different demographic characteristics. The elderly (> 64 years old), unmarried people, and those with a limited level of education (1–9 years) were especially susceptible to low humidex. Therefore, humidex is appropriate as a predictor in a CVD early-warning system.

A Computationally Efficient Method for the Thermo-Structural Analysis of a Turbocharger Turbine Wheel Under Engine Transient Operation

Abstract The accurate evaluation of thermally-induced stresses is of particular importance for life-cycle analysis of modern turbochargers. Conjugated heat transfer (CHT), steady-state calculations represent the state-of-the-art, whose temperature distribution is usually imported into a structural solver as a thermal load for carrying out thermo-structural analyses. In the case of transient analyses, however, issues arise. Indeed, due to the different timescales of convective and conductive heat-transfer mechanisms, unsteady CHT simulations are burdened by high computational costs. Moreover, in the specific case of turbocharged engines, the timescales of engine load transients and turbocharger response may differ by a factor of up to 105. The present study proposes an approach for carrying out transient thermo-structural analyses of the solid domain only, characterized by a physical time in the order of 101 s, without the need for unsteady fluid flow calculations, which would imply the use of a solver time-step in the order of 10−5 s. In the proposed methodology, the effects of the fluid flow in the heat-transfer process are modeled by imposing adequate boundary conditions to wet surfaces of the solid domain with minimum computational effort. Indeed, by performing two steady-state CHT calculations and one steady-state computational fluid dynamics (CFD) calculation, time-dependent boundary conditions can be derived in terms of convective heat transfer coefficient and near-wall fluid temperature. The case study used for model development is a high-performance turbocharger turbine for automotive applications, responding to engine load transients of tenths of seconds. Initially, steady-state CFD and CHT models of the turbine stage are validated against experimental data. Then, transient analyses on the turbine wheel are carried out, and their results are imported as thermal loads into an unsteady structural solver, allowing for accurate transient thermo-structural analyses at sustainable computational cost.

Human Neural Progenitors Expressing GDNF Enhance Retinal Protection in a Rodent Model of Retinal Degeneration.

Stem cell therapy for retinal degenerative diseases has been extensively tested in preclinical and clinical studies. However, preclinical studies performed in animal models at the early stage of disease do not optimally translate to patients that present to the clinic at a later stage of disease. As the retina degenerates, inflammation and oxidative stress increase and trophic factor support declines. Testing stem cell therapies in animal models at a clinically relevant stage is critical for translation to the clinic. Human neural progenitor cells (hNPC) and hNPC engineered to stably express GDNF (hNPCGDNF) were subretinally injected into the Royal College of Surgeon (RCS) rats, a well-established model for retinal degeneration, at early and later stages of the disease. hNPCGDNF treatment at the early stage of retinal degeneration provided enhanced visual function compared to hNPC alone. Treatment with both cell types resulted in preserved retinal morphology compared to controls. hNPCGDNF treatment led to significantly broader photoreceptor protection than hNPC treatment at both early and later times of intervention. The phagocytic role of hNPC appears to support RPE cell functions and the secreted GDNF offers neuroprotection and enables the extended survival of photoreceptor cells in transplanted animal eyes. Donor cells in the RCS rat retina survived with only limited proliferation, and hNPCGDNF produced GDNF in vivo. Cell treatment led to significant changes in various pathways related to cell survival, antioxidative stress, phagocytosis, and autophagy. A combined stem cell and trophic factor therapy holds great promise for treating retinal degenerative diseases including retinitis pigmentosa and age-related macular degeneration.

A habitat connectivity reality check for fish physical habitat model results and decision‐making for river restoration

Abstract Fish physical habitat models are a tool for guiding restoration efforts in lotic ecosystems, but often they overestimate restoration outcomes because currently they do not incorporate habitat connectivity. This persistent issue can, in extreme cases, result in little or no improvement to fish populations after the restoration, wasting valuable conservation resources. We present a case study where practitioners applied a fish habitat model for multiple life stages of gravel spawning fishes to a 52‐km stretch of the Iller River but did so at a microscale implementation by setting up a model based on cross sections with a maximum of 200 m distance from each other. This approach provided an opportunity to assess the connectivity of habitats for gravel spawning fishes, that is, European Grayling (Thymallus thymallus) and Common Nase (Chondrostoma nasus), integrating probabilities to find suitable habitats for all life‐history stages and seasonal movements. We used the assessed habitat estimates (availability of distinct habitat types within reaches defined by the 200 m cross sections) to calculate the minimum distance a fish would need to overcome to change from one habitat type into the other as it hypothetically ‘grew up’ from egg to full spawning adult. This approach can be interpreted as a life cycle habitat check as it considers all habitat types that are necessary to fulfil the life cycle of gravel spawning fishes including their size, distance and flow direction‐related orientation (e.g. larvae habitats only used when downstream of spawning areas). Our results show that the assumption of complete connectivity would require long movement distances for vulnerable life stages to find suitable habitat. This puts the high priority on the creation of migration corridors and passability of migration barriers in question. Without consideration of habitat types for all life stages of a species and their spatial context, restoration will not be successful. Shortly said: A perfect migration corridor does not necessarily provide habitat connectivity. We recommend the application of the habitat connectivity approach when predicting the effect of restoration measures and particularly setting the priority of measures for mitigation of fish migration.

Adaptive Façades Strategy: An architect-friendly computational approach based on co-simulation and white-box models for the early design stage

Adaptive Façades Strategy: An architect-friendly computational approach based on co-simulation and white-box models for the early design stage

Automation of the technological process of forming details with straight rifts

The subject matter of the article is technological line for the production of thick sheet parts with rifts, made of structural and special steels. The goal of the work is analysis and creation of methods of managing basic technological operations at all stages of the technological process of the automated production of such parts. The following tasks were solved in the article: formation of models of the main stages of forming parts with rectilinear rifts and control of dynamic properties of selected systems of their implementation. The following methods used are – methods of numerical integration and numerical methods of solving differential equations; analytical solution of differential equations based on the Dahlembert principle or by using the Lagrange equation; frequency analysis of transfer functions of individual links, presented in the form of fractional-rational functions. The following results were obtained – constructed in the first approximation the composition and sequence of the main operations of the generalized technological process of the automated production of thick-walled sheet parts with rifts; according to the results of the analysis of the process of elastic-plastic change of the shape of the region with many connections, the input and output parameters necessary for building a control model of the specified process were determined; it is determined that for its implementation it is necessary to ensure free deformation of at least 0.25 % of the rift surface area outside of contact with the forming tool, and the necessary technological methods for this are proposed; proposed variants of the technical implementation of the selected technological methods; the results of modeling schemes and modes of operation of the necessary technical equipment are presented. Conclusions: The application of the proposed structure, composition and sequence of main operations of the generalized technological process of the automated production of thick-walled sheet parts with cracks, based on its implementation by the selected methods on the proposed equipment, will allow to ensure the effective management of the quality of the production of the specified parts at each stage of the technological process.

The evolutionary stage of Betelgeuse inferred from its pulsation periods

Abstract Betelgeuse is a well known bright red supergiant that shows semi-regular variations with four approximate periods of 2200, 420, 230, and 185 days. While the longest period was customarily regarded as LSP (long secondary period) of unknown origin, we identify the ∼2200-d period as the radial fundamental mode, and the three shorter periods as the radial first, second, and third overtones. From a linear nonadiabatic pulsation analysis including the pulsation/convection coupling, we have found that these radial pulsation modes are all excited in the envelope of a model in a late stage of the core-carbon burning. Models with similar pulsation property have masses of 11 ∼ 12 M⊙ (19 M⊙ at ZAMS) with luminosities (log L/L⊙ = 5.27 ∼ 5.28) and effective temperatures (log Teff ≈ 3.53) that are consistent with the range of the observational determinations. We also find that a synthetic light curve obtained by adding the fundamental and the first-overtone mode is comparable with the light curve of Betelgeuse up to the Great Dimming. We conclude that Betelgeuse is likely in the late stage of core carbon burning, and a good candidate for the next Galactic Type II supernova.

The dynamics of entrepreneurial agglomeration formation: Social selection and simulation.

From the facts that numerous regions with initially similar economic conditions end up with different levels of entrepreneurial agglomeration, this paper constructs a model assuming that the sequential entrants make their career choices based on existing entrepreneurial ratio and describing the dynamics of entrepreneurial agglomeration formation. After mathematical analysis and numerical simulation using NetLogo, it is found that under social selection, a nonlinear Polya process with self-reinforcing and path-dependency characters will emerge, and the repeated entrants' career choices will lead to the agglomeration of entrepreneurship; the agent's risk compensation value, the initial population of agents, the number of role models in the early stage and the initial entrepreneurial ratio are determinants to the formation of entrepreneurial agglomeration. The findings confirm that entrepreneurship has "memory" and the entrepreneurial history could have influence on the future. In order to forge the entrepreneurial agglomeration, our suggestions include exerting influence on the determinants from an early age, and improving the individual's risk-taking abilities.