Current Surge Research Articles

Design of a linearization model for three‐phase PWM rectifiers for electrochemical machining

AbstractElectrochemical machining (ECM) is a processing method for metals that uses a DC power supply and flowing electrolyte. In some cases, discharge occurs during ECM when the gap between the electrode and workpiece, whose distance is rather small, is filled with hydrogen generated via electrolysis. We attempt to utilize a DC inductor placed between the DC supply and the ECM load in order to limit di/dt of the short or discharge current, which damages both the electrode and workpiece. When the output current surges, that is, when discharge occurs, the output voltage is suppressed by the DC inductance. In this paper, we propose a method for designing a PWM rectifier to reduce the discharge current, establish a linear approximation model for use in the PWM rectifier, describe a control method of the PWM rectifier, and demonstrate the efficacy of the model via simulations and experiments.

TRANSIENT PROCESSES IN ELECTRICAL COMPLEX OF PRODUCTION WELL WITH DOWNHOLE COMPENSATOR OF REACTIVE POWER

Link for citation: Glazyrin A.S., Isaev Yu.N., Kopyrin V.A., Timoshkin V.V., Kladiev S.N., Khamitov R.N., Kovalev V.Z., Losev A.F., Leonov A.P., Popov E.I. Transient processes in electrical complex of production well with downhole compensator of reactive power. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 5, рр.168-180. In Rus. The relevance. At the present time at routine complication of technological processes to increase efficiency of production processes due to introduction of new equipment conflicts between functional capabilities of various technical means and their ability to function with specified quality, in specified electromagnetic environment and do not create inadmissible electromagnetic interference to other technical means. The electrical engineering complex for oil production includes a combination of ground and submersible electrical equipment assembled for receiving, transforming electrical energy, controlling its flow, converting electrical energy into mechanical energy and transmitting it to a submersible pump, including various electrical and electronic devices: a control station with a frequency converter, a step-up transformer, a cable line, a submersible electric motor, a downhole reactive power compensator and other devices. Any change in the layout of electrical systems for extracting oil or technical characteristics of the equipment used requires careful analysis of transient processes between the operating modes of electrical equipment in order to prevent the risks of false triggering of electrical equipment protection devices. The purpose: analysis of transient processes in the electrical system of the production well with the downhole reactive power compensator when the power supply is disconnected in order to prevent the risks of false operation of the compensator protection devices. The object: section of a power supply system for a cluster of oil producing wells equipped with electric centrifugal pump installations with downhole reactive power compensators. Methods: positions of theoretical bases of electrical engineering, theory of electric drive, theory of differential equations, numerical methods. Results. The authors developed the mathematical model of the electrical system of the submersible unit for oil production with a downhole reactive power compensator, which enables to investigate transient processes in start-up and shutdown mode of the submersible induction motor. Characteristics of transient processes are obtained in elements of electrical complex of submersible plant for oil production when power supply is switched on and disconnected. It is established that the maximum current surge in the downhole reactive power compensator is 2,56 times with the parameters of the electrical system of the production well accepted in the study. The inventive measures for reducing the number of false actuations of the protection devices are also disclosed.

Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021

Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across different fields of research. In this study we examine worldwide adoption of AI technology within 333 fields of research during 1960–2021. We do this by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. We define AI using a list of 214 phrases developed by expert working groups at the Organisation for Economic Cooperation and Development (OECD). We found that 3.1 million of the 137 million peer-reviewed research publications during the entire period were AI-related, with a surge in AI adoption across practically all research fields (physical science, natural science, life science, social science and the arts and humanities) in recent years. The diffusion of AI beyond computer science was early, rapid and widespread. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to cover over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We note AI has experienced boom-bust cycles historically; the AI “springs” and “winters”. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.

Sociodemographically Stratified Exploration of Pancreatic Cancer Incidence in Younger US Patients: Implication of Cannabis Exposure as a Risk Factor

Introduction. The aetiology for the recent increase in pancreatic cancer incidence (PCI) in the US is unknown. This paper provides an epidemiological investigation of the exponential increase in PCI in young people aged 15–34 years, particularly amongst females, with a focus on the exponential rise amongst African American females, and its relationship to substance use. Methods. National pancreatic cancer data from recent reports. Tobacco, alcohol and daily cannabis use data taken from the annual nationally representative National Survey of Drug Use and Health, response rate = 74%. Results. Amongst the 15–34-year-aged cohort, PCI was found to be significantly more common in females (females: β-est. = 0.1749 p = 0.0005). African American females are noted to have the highest rates of daily cannabis use amongst females in the 26–34 and 35–49-year groups. The relationship between PCI and daily cannabis use was strongly positive across all ethnicities and in both sexes. In African American females, the Pearson correlation between daily cannabis use and PCI was R = 0.8539, p = 0.0051. In an additive multivariable model for each sex and race, cannabis was the only significant term remaining in the final model in the 15–34-year-aged cohort and thus out-performed alcohol as a risk factor. The most significant term in multivariate models was the alcohol:cannabis interaction which was highly significant in all ethnicities from p = 2.50 × 10−7 for Caucasian American females and the highest E-value pair was for Hispanic American females (E-value estimate = 1.26 × 10102 and E-value lower bound 2.20 × 1074). Conclusion. These data show that cannabis fulfills quantitative criteria of causality in all age, sex and ethnicity cohorts, and thus explains both the recent surge in PCI and its ethnocentric predominance. Cannabis interacts powerfully genotoxically and cancerogenically with alcohol, with increases in cannabis use driving the current PCI surge. These results raise the important question as to how much cannabis might be responsible for the modern renaissance in cancer rates amongst younger people.

Assessment of Emergency Department Key Performance Indicators about Surge Response Actions Across Three Periods of the COVID-19 pandemic in an Italian Hospital

Introduction:At the beginning of the COVID-19 pandemic, Italian emergency departments (EDs) had to hastily implement current surge response plans or create new ones. The objectives of this study are to quantitatively assess ED performance improvements between selected non-pandemic and pandemic periods at Sant’Anna hospital in Como, Italy, and to relate these to adopted and adapted surge response actions.Method:The average length of stay (LOS), time-to-physician initial assessment (TPIA) and left-without-being seen (LWBS) rates were calculated during two ED periods prior to the pandemic and then three periods during the pandemic in the COVID ED (C-ED) dedicated to treat COVID patients, and the COVID-free ED (NC-ED) dedicated to treat all other patients. Then quantitative data analysis based on hypothesis testing was performed.A qualitative theme and subtheme data analysis based on the Hospital Surge Preparedness and Response Index (HSPRI) was performed on baseline strategies before each pandemic period and on the actions implemented in the subsequent period.Results:The LOS increased across all periods, while the TPIA decreased in the first two pandemic periods in comparison to pre-pandemic periods. The NC-ED LOS was lower than the C-ED LOS, and the C-ED TPIA was lower than the NC-ED TPIA in all three pandemic periods. The LWBS decreased between pre-pandemic and pandemic periods, with an increasing trend towards pre-pandemic levels in the last pandemic period. Of the 20 action items listed in the HSPRI, six were implemented in the first pandemic period, eight in the second and one in the third.Conclusion:The LOS, TPIA and LWBS rates are useful indicators to rapidly obtain an overview of ED performance but failed to provide an exhaustive assessment because ED performance depends on countless external and internal variables. Close collaboration of ED leaders with other healthcare agencies is critical to respond to a pandemic surge.

A spatial correlation prediction model of urban [formula omitted] concentration based on deconvolution and LSTM

Precise prediction of air pollutants can effectively reducre the occurrence of heavy pollution incidents. With the current surge of massive data, deep learning appears to be a promising technique to achieve dynamic prediction of air pollutant concentration from both the spatial and temporal dimensions. This paper presents Dev-LSTM, a prediction model building on deconvolution and LSTM. The novelty of Dev-LSTM lies in its capability to fully extract the spatial feature correlation of air pollutant concentration data, preventing the excessive loss of information caused by traditional convolution. At the same time, the feature associations in the time dimension are mined to produce accurate prediction results. Experimental results show that Dev-LSTM outperforms traditional prediction models on a variety of indicators.

The Rise in Anti-Asian Racism and Xenophobia in the Time of COVID-19

As the COVID-19 pandemic continues to have a detrimental impact on the health of the American people and those abroad, the social consequences stemming from the spread of the virus have become an international crisis whose effects reach far beyond the medical issues associated with the disease. Racial and xenophobic propaganda about the illness promoted on social media platforms such as Facebook and Twitter and at campaign rallies by former President Trump has spurred a dramatic increase in anti-immigrant sentiments toward Asian Americans. The polarizing effects of the Administration’s anti-Asian rhetoric have become a battle cry that has given renewed justification to the growing number of White Supremacist hate groups stepping up their bias-related attacks against members of a community, which they believe is the primary source of viral transmission. The present article analyzes the socioeconomic and psychological factors contributing to the increase of COVID-19-related racism and xenophobia in the United States. It reviews the history of sociocultural responses to past epidemics to aid our understanding of society’s reaction to the current global epidemic. It also examines specific legislative and grassroots measures that advocacy organizations and the federal government can implement to stem the tide of misinformation about the viral transmission at the heart of the current surge of violence and racial discrimination against the Asian American and Pacific Islander communities.

Magnetic state balance technology of transformer based on magnetic field modulation strategy

The transformer core is easy to saturate in the half cycle under the influence of the remanent magnetism (RM) and the bias magnetism (BM), then the excitation surge current (ESC) and the DC bias will be generated, causing the transformer excitation current (TEC) distort, leading the winding temperature rise and decreasing the transformer insulation. In this paper, one kind of magnetic balance modulation method for the transformer core is proposed. TEC distortion could be improved by adjusting the transformer magnetic field distribution. Firstly, the AC/DC/DC converter was designed and connected to the auxiliary winding according to the hybrid transformer topology. Second, the specific modulated signal for the magnetic field modulation (MFM) was generated and output through the AC/DC/DC. The modulated forward and reverse DC current or the stepped AC current would be injected into the transformer winding to achieve the balance of the transformer magnetic state. Finally, in order to verify the correctness of the design scheme, a 1 kVA/380 V/220 V/38 V transformer experiment platform was built. The results showed that this proposed MFM strategy could effectively solve the impact of the transformer ESC, DC bias and prolong the transformer service life, which provides a novel idea to solve the transformer fault.

A Systematic Review and Meta-Analysis of Dual Enrollment Research

Given the current surge in student participation in dual enrollment programs, an updated synthesis of literature relating to how these programs impact students is warranted. Furthermore, while there are qualitative literature reviews relating to dual enrollment and student outcomes, there has not been a quantitative synthesis of literature relating to the findings of this research. Accordingly, we conduct a quantitative literature review involving the academic outcomes of higher education enrollment, persistence, performance, and degree attainment. Using meta-analytic techniques, we find that across the 162 study effect sizes included in our analysis, participation in dual enrollment programs was positively associated with grade point average (GPA), total earned college credits, college enrollment, early persistence, degree attainment, and full-time attendance. Also, we find negative associations between dual enrollment and time to graduation and total semesters enrolled in college, indicating these programs can help students graduate college more quickly.

Prevalence of Giardia lamblia Infection among Pupils and Students from Selected Schools in Nsukka Metropolis, Enugu State

Globally, Giardia lamblia is the most common intestinal protozoa parasite with about 200 million yearly infections in Africa, Asia, and Latin America. The parasite is common in third-world countries with poor living conditions. The current surge in terrorism across Nigeria has forced people to migrate into relatively peaceful regions and Nsukka has been one of the cities in Nigeria that have witnessed the influx of migrants. This migration aids the spread of G. lamblia and thus puts the public health of the inhabitants of Nsukka metropolis at risk. The current state of G. lamblia infection in Nsukka metropolis is not known and this knowledge gap hampers effective planning by public health officers and policymakers to safeguard the public health of the inhabitants. The objectives of this study were to provide information on the prevalence of G. lamblia infection among pupils and students from selected schools within Nsukka metropolis and to provide data on the age group that is more vulnerable to the parasitic infection among the studied population for public health campaign against the parasite. Faecal samples were collected from 170 individuals from five different schools. The faecal samples were examined for G. lamblia under the microscope using formol-ether concentration and direct smear methods. The prevalence of G. lamblia is 38.2%. The prevalence is higher in males (40.3%) than in females (36.7%). El-Shaddai Nursery and Primary School (ENPS) and University of Nigeria Nsukka (UNN) recorded the highest prevalence of 53.3% each. Children in the age groups 3 - 7 years had the highest prevalence of 66.7%. Giardia lamblia is widespread among children and university students in Nsukka metropolis.

Recently emerged omicron subvariant BF.7 and its R346T mutation in the RBD region reveal increased transmissibility and higher resistance to neutralization antibodies: need to understand more under the current scenario of rising cases in China and fears of driving a new wave of the COVID-19 pandemic.

Recently emerged omicron subvariant BF.7 and its R346T mutation in the RBD region reveal increased transmissibility and higher resistance to neutralization antibodies: need to understand more under the current scenario of rising cases in China and fears of driving a new wave of the COVID-19 pandemic.

A soft start-up method for DC micro-grid based on improved two-level VSC with DC fault ride-through capability

For the black start-up of DC micro-grids, three-phase charging resistors are required to limit the uncontrollable surge current. The main drawback of this start-up method is the difficulty in determining the appropriate resistance value to achieve a rapid start-up and limit the surge current with the change of grid parameters. To address this problem, this article proposes a soft start-up method for the DC micro-grid based on an improved two-level voltage source converter (VSC). Specifically, an silicon controlled rectifier and anti-parallel diode are added in each up-bridge-arm in the improved VSC. By conducting a dynamic control strategy of the firing angle on the SCRs, the start-up current can always be maintained near a given value to achieve rapid start-up. Moreover, the improved VSC has DC fault ride-through capability. The simulation results based on PSCAD/EMTDC are provided to validate the feasibility of the proposed start-up method.

Effect of Immunonutrition on the Liver Function Status of End-Stage Liver Disease Patients Waiting/Referred for Liver Transplant: A Randomized Controlled Trial.

Background Malnutrition and liver dysfunction are commonly observed in patients with chronic liver disease. With the current surge in liver diseases, prompt nutritional planning will ensure the well-being of patients during the waiting period and will improve the clinical outcomes following liver transplantation (LT). We conducted this study to monitor the effect of immunonutrition on liver function parameters among end-stage liver disease (ESLD) patients referred for LT. Methodology In this randomized controlled trial, 144 ESLD patients who met the inclusion criteria were randomly enrolled into control (CON) and intervention (INT) groups after obtaining informed consent. Three patients were lost to follow-up due to the COVID-19 lockdown. The INT group(n = 69) was provided with 100 g of immunonutrient and the CON group (n = 72)was provided with supervised diet advice. Liver function test (LFT) parameters such as total protein, albumin, total bilirubin, direct bilirubin, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, and prothrombin time/international normalized ratio before and after therapy at one month were checked in both groups. Results The majority of patients with the disease were males (83.3% in the CON group vs 76.8% in the INT group), having alcoholism as the etiology in both groups with 45.8% in the CON group and 56.5% in the INT group. Thecomparison of LFT parameters among ESLD patients during pre and post-therapy between the control and immunonutrition groups did not show any statistically significant difference in the LFT parameters between the INT and CON groups both at baseline and at one month. Conclusions The impact of immunonutrition on ESLD patients awaiting LT compared to supervised diet advice did not significantly improve liver function. The liver disease itself profoundly affects the level of nutrition; hence, nutritional assessment and early nutritional interventions can be instituted to improve clinical outcomes.

COMPARISON ON STUDY OF LITHIUM ION AND LEAD ACID CHARGING AND DISCHARGING CHARACTERISTICS

A lithium-ion or Li-ion battery is a type of rechargeable battery which uses the reversible reduction of lithium ions to store energy. It is the predominant battery type used in portable consumer electronics and electric vehicles. Energy density: 250–693 Wh/L (0.90–2.49 MJ/L) Specific energy: 100–265 Wh/kg (0.360–0.954 MJ/kg) Charge/discharge efficiency: 80–90% Cycle durability: 400–1,200 cycles Self-discharge rate: 0.35% to 2.5% per month depending on state of charge Specific power: c. 250–340 W/kg Lithium batteries, as opposed to alkaline, are capable of giving off a strong energy surge after a long period of low discharge. This makes them ideal for fire alarms. Alkaline batteries provide good, long-term power, but they lose strength over time. On the other side , the Lead acid battery are inexpensive compared to newer technologies, lead–acid batteries are widely used even when surge current is not important and other designs could provide higher energy densities. Energy density: 80–90 Wh/L Nominal cell voltage: 2.1 V Self-discharge rate: 3%–20%/month Specific energy: 35–40 Wh/kg Charge temperature interval: Min. −35°C, max. 45°C Charge/discharge efficiency: 50%–95% Cycle durability: <350 cycle In order to observe the characteristic nature of Lead acid & Lithium ion battery , a review is made on the subject using Matlab Simulink and Simscape.

STUDY OF LEAD ACID CHARGING & DISCHARGING CHARACTERISTICS

ABSTRACT:-The lead-acid batteries provide the best value for power and energy per kilowatt-hour; have the longest life cycle and a large environmental advantage in that they are recycled at an extraordinarily high rate. No other chemistry can touch the infrastructure that exists for collecting, transporting and recycling lead-acid batteries.The rechargeable and secondary batteries category includes lead acid batteries. Despite the battery's low energy-to-volume and energy-to- weight ratios, it can deliver higher surge currents. This refers to the fact that lead acid cells have a high power-to-weight ratio. These are the batteries that transform chemical energy into electrical energy by using lead peroxide and sponge lead. Because of the elevated cell voltage levels and low cost, these are commonly used in substations and power systems. Lead Acid batteries are widely used in automobiles, inverters, backup power systems etc. Unlike tubular and maintenance free batteries, Lead Acid batteries require proper care and maintenance to prolong its life. The Lead Acid battery consists of a series of plates kept immersed in sulphuric acid solution. The plates have grids on which the active material is attached. The plates are divided into positive and negative plates. The positive plates hold pure lead as the active material while lead oxide is attached on the negative plates. A completely charged battery can discharge its current when connected to a load. During the process of discharge, the sulphuric acid combines with the active materials on the positive and negative plates resulting in the formation of Lead sulphate. Water is the single most important step in maintaining a Lead Acid battery. The frequency of water depends on usage, charge method and operating temperature. During process, the hydrogen atoms from the sulphuric acid react with oxygen to form water.This results in the release of electrons from the positive plates which will be accepted by the negative plates. This leads to the formation of an electric potential across the battery. The electrolyte in the Lead Acid battery is a mixture of Sulphuric acid and water which has a specific gravity. Specific gravity is the weight of the acid-water mixture compared to equal volume of water. The specific gravity of pure ions free water is 1.

From the Archive to the Computer: Michel Foucault and the Digital Humanities

Michel Foucault famously introduced the method of “discourse analysis” in the humanities, especially in historiography. In his Archaeology of Knowledge, originally published in 1969, in particular, Foucault argues for making the history of knowledge the object of discourse analyses. In the context of the current surge of interest in discourse analysis in the field of computer science, however, there are hardly any references to Foucault, partly because he never defined a methodological process that could be operationalized. Nonetheless we argue for re-reading the Archaeology of Knowledge in the context of computer science and the digital humanities. As a matter of fact, there are considerable affinities between Foucault’s search for the regularities of discourse and current projects dealing with the digitization of texts, their indexing, distributional features, stylometry, etc. We show that these projects were already quite prominent in Foucault’s day, to the point that historian Emmanuel Le Roy Ladurie could assert, in 1968, that “the future historian will be a programmer.” A year later, Foucault’s Archaeology of Knowledge actively responded and constructively took up the challenge – which, given the recent advances in machine learning and computational linguistics, strikes us as a crucial move today.

Hybrid low switching frequency modulation strategy with high dynamic response for high‐power voltage source converter

AbstractFor high‐power converters, the low switching frequency (SF) modulation represented by selective harmonic elimination pulse width modulation (SHE‐PWM) is crucial to reduce the switching loss and enhance the efficiency with a good steady‐state performance. However, since the advantages of SHE‐PWM mainly come from the fixed switching angle distribution limited by non‐linear equations, switching angles should be adjusted slowly. This requires that the bandwidth of proportional integral (PI) controllers be limited hugely, resulting in a poor dynamic response. As the most popular control to improve the dynamic response, finite‐control‐set model predictive control (FCS‐MPC) has a worse steady‐state performance under low SF because of large errors caused by a long prediction period and harmonics caused by space vector PWM (SVPWM). Therefore, a hybrid modulation strategy with an acceptable complexity is proposed in this article, which combines SHE‐PWM and FCS‐MPC. PI + SHE‐PWM is adopted in a steady state with low SF, while MPC + SVPWM is used in a transient state with high SF. By studying smooth switching from the modulation level and control level, the proposed method can eliminate the current surge when switching between PI + SHE‐PWM and MPC + SVPWM. Experiments verify that the proposed method have a good steady‐state performance and high dynamic response simultaneously under overall low SF.

Labor Unbound? Assessing the Current Surge in Labor Activism

Where will the current surge of labor activism lead? To address this question we examine two distinctive currents of labor struggle—one rooted in “new economy” firms and a second in the nation's logistics sector—where post-pandemic conditions have confronted workers with important opportunities and challenges. If the workers’ movement is to make enduring gains, it will need to foster organizational alliances that stretch across distinct sectors of the economy, build support among consumers and the broader public, and challenge culture war rhetoric through appeal to workers’ shared needs.

Categorizing 15 kV High-Voltage HDPE Insulator’s Leakage Current Surges Based on Convolution Neural Network Gated Recurrent Unit

The leakage currents are appropriate for determining the contamination level of insulators in the power distribution system, which are efficiently cleaned or replaced during the maintenance schedule. In this research, the hybrid convolution neural network and gated recurrent unit model (CNN-GRU) are developed to categorize the leakage current pulse of the 15 kV HDPE insulator in the transmission towers in Taiwan. Many weather parameters are accumulated in the online monitoring system, which is installed in different transmission towers in coastal areas that suffer from heavy pollution. The Pearson correlation matrix is computed for selecting the high correlative features with the leakage current. Hyperparameter optimization is employed to decide the enhancing framework of the CNN-GRU methodology. The performance of the CNN-GRU is completely analyzed with other deep learning algorithms, which comprise the GRU, bidirectional GRU, LSTM, and bidirectional LSTM. The developed CNN-GRU acquired the most remarkable improvements of 79.48% CRE, 83.54% validating CRE, 14.14% CP, 20.89% validating CP, 66.24% MAE, 63.59% validating MAE, 73.24% MSE, and 71.59% validating MSE benchmarks compared with other methodologies. Therefore, the hybrid CNN-GRU methodology provides comprehensive information about the contamination degrees of insulator surfaces derived from the property of leakage currents.

Tackling chikungunya and dengue crisis in Paraguay amidst COVID-19: an epidemiological alert - a correspondence.

Tackling chikungunya and dengue crisis in Paraguay amidst COVID-19: an epidemiological alert - a correspondence.