bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of “Hidden in Plain Sight” de-identification methodology in electronic healthcare data provides minimal risk of misidentification: Results from the iCAIRD Safe Haven Artificial Intelligence Platform.
Authors: Farrow Luke , Wilde Katie , Dymiter Jaroslaw , Boyle Moragh , Weir Alexander , Blackwood James , Mayor Charlie , Harrison David , Anderson Lesley
Published: August 2022

ObjectivesTo determine the risk of misidentification when using a “Hidden In Plain Sight (HIPS)” Named Entity Recognition (NER) de-identification methodology applied to Scottish healthcare data within The Industrial Centre for Artificial Intelligence Research in Digital Diagnostics (iCAIRD) Safe Haven Artificial Intelligence Platform (SHAIP).

ApproachRather than the traditional redaction of potential identifiable information in routinely collected healthcare data, our HIPS methodology utilises an NER “find and replace” approach to de-identification that keeps the structure of text intact. This ensures that context is maintained, key to the interpretation of free text information and potential Artificial Intelligence applications.

To our knowledge these methods have been previously untested on Scottish healthcare data. We therefore performed assessment of this approach in terms of potential risk of misidentification using HIPS on structured Scottish data deployed in SHAIP as part of the iCAIRD programme.

ResultsFive individual cohorts, with a total of 169,964 patients were included. For each cohort the HIPS approach was applied, and then compared to actual patient information from within the same region, in order to determine the risk of misidentification. The following fields were included: Forename, Surname, Previous Name, Gender, Date of Birth (DOB), and Postcode.

Across the five cohorts and varying combinations of identifiable data fields there were a total of 94 instances of potential misidentification (0.06%). 85/94 (90.4%) of these were for the combination of Gender, Date of Birth and Postcode. Across the five cohorts there were only 3 instances (0.002%) of Forename/Surname/DOB, and 5 instances (0.003%) of Forename/Surname/Postcode potential misidentification amongst the 169,964 patients.

ConclusionsThe iCAIRD NER HIPS Methodology provides an acceptably low misidentification rate. Further work is now required to determine the recall and precision rates. Benefits of this approach include retaining the structure of free text, as well as reducing the ability to detect any potential leaked identifiable data.
Mapping where patients access primary care providers.
Authors: Frymire Eliot , Gozdyra Peter , Green Michael , Bayoumi Imaan , Glazier Richard , Jaakkimainen Liisa , Khan Shahriar , Kiran Tara , Premji Kamila
Published: August 2022

ObjectivesTo gain an understanding of the attribution of patients to newly introduced Ontario Health Teams (OHT). OHTs are responsible for organizing and delivering health local care based on established connections between patients, their primary care providers, and hospitals. Furthermore, we aim to identify areas with poor geographic access to care.

ApproachWe used GIS analyses and maps to depict the attribution of patients to OHTs based on their uptake of primary care and hospital referral patterns.   Residents of a specific local area can be attributed to different OHTs based on their prevailing health seeking choices.  This leads to a creation of non-unique OHT ‘capture zones’, which may pose challenges in primary health care planning and delivery.

The range of spatial analyses and maps used in this study helps to overcome some of these limitations and provides healthcare administrators with important geographic layer of information not available through other data summary methods.

ResultsThe distribution of patients and patterns of the primary care seeking vary greatly between urban, rural and remote areas.  Many of the rural and remote OHTs have their patients clustered in areas surrounding the main hospital.  These areas can be quite large geographically but their extents are still unique from other OHTs.  OHTs in urban areas show substantial overlaps of their patient base. The urban patients are in most cases highly clustered around the main hospital location for hospitals providing primary and secondary care.  The distribution of patients attributed to OHTs with hospitals providing tertiary care is quite spread out throughout the region or even the province.

All these unique patterns reflect complex ways of primary care seeking behavior and referral patterns for hospital care.

ConclusionThese attribution maps and data tables are an essential resource for planners and decisions makers in identifying priorities within the regional provision of primary care.  This knowledge is essential to a better understanding of health care needs of local populations, and to implementing improvements in health care access.
Statistical methods for assessing the impact of the Covid-19 pandemic on health services use: Paediatric primary care and mental health access.
Authors: Stukel Therese , Guttmann Astrid , Saunders Natasha , Fu Longdi
Published: August 2022

ObjectivesThere were large disruptions to health care services after the onset of the COVID pandemic. We compared outpatient primary care and mental health care physician visits before and during the COVID-19 pandemic in Ontario, Canada.

ApproachPopulation-based study of pediatric primary care and mental health visit rates after vs. before Covid restrictions. We used Poisson GEE regression to model 3-year pre-Covid trends and forecast expected trends after restrictions. The model included age, sex, a secular trend, and pre-Covid month indicators. Expected visit rates and 95% CIs post-restrictions were estimated by applying the linear combination of pre-Covid regression coefficients to the post-pandemic data and exponentiating. Relative changes in post Covid visit rates were expressed as an adjusted rate ratio of observed to expected rates by exponentiating the difference of observed and expected post-pandemic log rates and CIs.

ResultsIn a population of 2.5 million children, primary care visit rates declined by 20% of expected (adjusted rate ratio [aRR], 0.80; 95% CI, 0.77–0.82). The largest monthly decrease occurred in April 2020. Virtual visits accounted for 53% of overall visits. Although visit rates increased slowly after April 2020, they did not return to pre-restriction levels by November 2020. Mental health visit rates declined rapidly to below expected in April 2020 (aRR, 0.81; 95% CI, 0.79-0.82) followed by an increase to 7% above expected (aRR, 1.07; 95% CI, 1.04-1.09) by July 2020 and sustained at 10-15% above expected to February 2021. Adolescent females had the greatest overall increase in mental health visit rates relative to expected (aRR, 1.26; 95% CI, 1.25-1.28).

ConclusionThe pandemic contributed to rapid decreases in primary and mental health care, with some recovery and a shift to virtual care. There was a disproportionate increase in mental health care services among adolescent females. System-level planning to address increasing needs and monitor quality with such large shifts is warranted.
Analysing Siamese Neural Network Architectures for Computing Name Similarity.
Authors: Vinden Nicholas , Foxcroft Jeremy , Antonie Luiza
Published: August 2022

IntroductionA wide assortment of string similarity measures can be used to determine how similar two names are. A diverse set of discriminating and independent features for name similarity are important for classification during record linkage. A Siamese neural network could surpass traditional string similarity measures for the name similarity problem.

Objectives and ApproachThis research aims to compare a classifier based on the Siamese network architecture with a Random Forest classifier. In addition to comparing overall performance, we seek to answer whether there are any special properties of certain matching name pairs where the complexity of the Siamese network offers particular benefit.

Our data consists of 25,000 last name pairings, with each pair being two variants of a family name. Name similarity predictions from the Siamese network are compared to a Random Forest model that serves as an ensemble of existing string similarity measures.

ResultsWe compare the similarity scores yielded by the two methods and discuss the results. We describe the representation of names to each method; name representation is computed formulaically for the traditional measures but is learned by the Siamese network during training. The comparison of different methods is made both in terms of their similarity prediction quality, and the computational cost to generate the predictions.

As expected, the Siamese network necessitates a significant computational cost to train. Unexpectedly, the ensemble of traditional measures yields almost identical overall classification performance. However, we expect that further analysis of false positives and false negatives will yield some insight into when practitioners should consider one method over the other.

Conclusions/ImplicationsResults suggest that there may be instances where a Siamese network outperforms other similarity measures, although training a Siamese network comes at a considerable computational cost. It is worth considering this approach to name similarity as an additional similarity feature when performing record linkage tasks.
Evidence from an Applied Health Research Question (AHRQ): Health care utilization of publicly funded rehab services for patients post COVID-19 diagnosis.
Authors: Golding Haley , Churchill Katie , Levy Charissa , An Diana , Hall Ruth , Plumptre Lesley
Published: August 2022

ObjectivesThe Rehabilitative Care Alliance issued an Applied Health Research Question request to collect information regarding healthcare and rehabilitation use among COVID-19 positive individuals. The objective of this project is to determine the association between length of stay (LOS) in acute care and the number of rehabilitation services used post COVID-19 diagnosis.

ApproachHospital and rehabilitation service use was identified among individuals diagnosed with COVID-19, using administrative health data. Admission into acute care within 30 days post COVID-19 diagnosis was recorded. Use of inpatient, physiatry and home-care rehabilitative services were collected until March 31st 2021. Outpatient rehabilitation reporting is not mandatory and was not included. Marginalization was evaluated using the Ontario Marginalization Index factor scores. The association between LOS in acute care and number of rehabilitation categories used was assessed using a negative binomial model, stratified by with or without a stay in the ICU and controlling for age, sex, comorbidities and long-term care residence.

ResultsOf 181,139 individuals diagnosed with COVID-19 prior to December 31st 2020, 5% were hospitalized. Of those hospitalized 2.3% then entered rehabilitation compared to 0.06% who were not hospitalized post COVID-19 infection. Rehabilitation users had higher residential instability (mean=0.45 vs -0.01 in the overall cohort), dependency (mean=-0.02 vs -0.27) and material deprivation (mean=0.37 vs 0.19) but similar ethnic diversity (mean=0.87 vs 0.90) compared to the full cohort. LOS in acute care was associated with a 3.3% increased risk of using additional rehabilitation services for individuals without a stay in the ICU (RR 1.033, 95% CI: 1.011 to 1.055; p=0.0036), and a 3.7% increased risk for individuals with a stay in the ICU (RR 1.037, 95% CI: 1.025 to 1.048; p<.0001).

ConclusionsPost COVID-19 diagnosis, a larger proportion of rehabilitation service users were hospitalized compared to all COVID-19+ individuals. Additionally, LOS in acute care was associated with the use of more rehabilitation care categories following a COVID-19 diagnosis, and the association was stronger for more severe cases requiring an ICU stay.
Ancillary Data Record Linkage to characterize the completeness of data for the All of Us Research Program.
Authors: Yang Yuyang , Rodriguez Kelsey , Basford Melissa , Nambiar Sidd , Berman Lew , Kho Abel
Published: August 2022

ObjectiveThe All of Us Research Program (AoURP) is an ambitious effort to gather health data from one million Americans to accelerate research. We linked Electronic Health Records (EHR) and insurance claims data to characterize the degree to which ancillary datasets can improve data completeness for care received by AoURP participants.
ApproachWe sought to link EHR data for 400,000 consented AoURP participants with insurance claims data provided by IPM.AI (Swoop Analytics), a commercial analytics company who have insurance claims data for 300M (over 90% of) Americans.  We utilized a HIPAA-compliant privacy-preserving record linkage method (tokenization, provided by Datavant) to match patients between datasets. We evaluated match fidelity and the degree of overlap between AoURP EHRs and IPM.AI claims data. We characterized the association of patient and organizational level factors (demographics, healthcare provider organization, reporting site) with match performance.
ResultsAs of submission of this abstract, 41% of AoURP EHRs matched with IPM.AI claims. We compared patient healthcare encounters, diagnosis codes (DX), procedure codes (PX), and national drug codes (NDC) for matched patients by month. The union of AoU and IPM.AI data greatly increased data completeness in matched patients. Only 20% of healthcare encounters were seen by AoURP and IPM.AI concurrently while 25% were unique to AoU EHRs and 55% to IPM.AI claims on a monthly level. The number of diagnosis events compared between AoURP and IPM.AI is roughly equal (AoU +6%) while procedure events are elevated in claims data (23%) and drug counts are greatly elevated in AoURP EHR data (71%). We found that matched patients had more healthcare encounters compared to unmatched patients.
ConclusionTo our knowledge this is the first effort to address challenges in AoURP data completeness through complementary data linkage. Our results suggest that supplementary data linkage can improve data completeness in a large national research initiative. We identified several patient factors that require further investigation in improving match fidelity.
Brazilian governmental database linkage to correct the municipalities underreported cases in a time-dependent cluster analysis on COVID-19.
Authors: Ara Anderson , Santo Jonatas Espirito , Conceição Jackson , Barreto Marcos Ennes , Costa Lilia Carolina Carneiro , Souza Rafael Felipe da Silva , Fiaccone Rosemeire Leovigildo , Barreto Mauricio Lima , Ichihara Maria Yury Travassos
Published: August 2022

ObjectivesCovid-19 databases have detailed information about each affected person in Brazil, but it has flaws in counting the number of cases, which are underreported. We aimed to construct and correct the cases dataset by linking different sources of data observations to study the pandemic evolution in Brazilian municipalities.

ApproachUsing the electronic Unified Health System (e-SUS), a public and governmental database, we calculated the pandemic curves of COVID-19 cases. We applied the following approaches to investigate data anomalies a) to perform a descriptive analysis and compare these results with  a non-governmental database using Dynamic Time Warping distance; b) to verify and correct municipalities data anomalies linking to other public governmental database namely National Council of Health Secretaries (CONASS) with e-SUS. c) To apply a K-means DTW Barycenter Averaging in clustering analysis to describe the general behaviors of pandemic in Brazilian Municipalities.

ResultsAround 10% records of cases in the e-SUS public governmental database were underreported. After the linkage and the data updating procedure, the time-dependent clustering analysis presents no anomalies and more interpretable results. The clustering analysis provided eight different behaviors of COVID-19 curves of cases. The degree of intensity for prevalence and incidence rates were identified according to eight clusters from the lowest to highest.

ConclusionsUsing the matching procedure based on Dynamic Time Warping distance to correct the municipalities unreported cases, we provided a richer dataset to support a clustering time dependent analysis to characterize the Pandemic evolution in Brazil. These results may be explored in future deprivation social studies.
Addressing multi-region data linkage needs through data sharing agreements – Three Canadian initiatives.
Authors: Maillet Donna Curtis , McDonald Ted
Published: August 2022

ObjectivesData sharing and administrative data access for multi-jurisdictional research must accommodate all local requirements for the protection of personal information and personal health data. Navigating the different safeguards for data sharing found in all relevant Canadian provincial and territorial legislation requires exploring innovative, privacy compliant solutions.

ApproachHealth Data Research Network Canada (HDRN Canada) and one of its provincial data centre partners, New Brunswick Institute for Research, Data and Training (NB-IRDT), are undertaking unconventional approaches to data sharing that balance legislative compliance and data access needs.  Three approaches are being pursued: harmonizing data sharing agreements between a national longitudinal study and 10 provincial data centres; facilitating 4 individual data sharing agreements with one regional cohort of a nationwide study; and coordinating data sharing between 4 provincial government departments and one national data centre. Each approach has unique features that presented problems needing innovative resolutions.

ResultsThe experiences and challenges of these three approaches to data sharing for multi-regional research have been perplexing but ultimately are leading to productive outcomes.  Learnings acquired enable partners to move beyond anecdotal perceptions of data sharing limitations to practical solutions that can be applied in future data sharing partnerships.

The ongoing project management approach of these initiatives identified a core set of somewhat predictable devices to ensure the advancement of simultaneous multiple regional data sharing agreements. These include the assignment of a project coordinator role, clear and ongoing communication, and the ability to negotiate and manage expectations.  More innovative, however, is the roadmap that evolved, laying out the necessary (previously unanticipated) measures and sequence in which they should occur for the most expedient outcome.

ConclusionTo harness the potential of multi-regional research in Canada, provinces and territories must identify feasible and efficient data sharing solutions.  The identification of adoptable and replicable legislatively compliant data sharing practices will increase potential data accessibility.  This will increase available data and data platforms for research informed policy decisions.
COVID-19 transmission and infection: linkage of COVID-19 Infection Survey, Test and Trace, and Patient Demographics Survey.
Authors: Maizey Leah , Plachta Josie , Clarke Holly , Collyer Sarah , Cummins Sarah , De La Serna Gabriela , Gammon Shelley , Harries Ben , Pereira Elizabeth , Youell Caroline
Published: August 2022

ObjectivesData linkage was conducted between the Office for National Statistics’ Covid Infection Survey (CIS), the Department of Health and Social Care’s Test and Trace (T&T) and NHS’ Personal Demographics Service (PDS) datasets. Linked data was required to provide reliable estimates of rates of COVID-19 transmission and infection used to inform policy regarding the ongoing pandemic.

ApproachThe CIS was created to track infection rates in the UK population. Linking CIS participants to positive tests in T&T helped improve these estimates. Linkage to PDS was required to attach NHS number to these datasets to facilitate further linkages that could also be used to inform Government about the spread of the virus. Multiple approaches were used to link the data. Initially, T&T was linked to itself via a series of strict matchkeys to cluster records belonging to the same individual, to create a person level identifier. Subsequent linkage of CIS-PDS, T&T-PDS and CIS-T&T involved deterministic linkages with matchkeys designed and applied independently. A probabilistic (Fellegi-Sunter scoring) method was used to link CIS-PDS and CIS-T&T. Additional, associative links were created between CIS and T&T records that had matched to the same PDS record but had not matched to each other.

ResultsThe accuracy of CIS-PDS and CIS-T&T linkages was high (recall and precision >98%; all 95% lower confidence intervals >93%). A quality assessment of T&T-PDS is underway, as are relevant bias analyses.

ConclusionAs a result of this linkage, COVID-19 analysts have access to enriched datasets linked to compare previously separated variables, with confidence that the linkage method used was to required quality standards. The linked data has been used to provide crucial evidence to Government on infection and re-infection rates. Subsequent linkages have enabled analysts to explore risk factors associated with different variants of the virus, vaccination status and hospital episodes. Improvements continue to be made.
Development of a Prediction Model for Survival Time in Esophageal Cancer Patients Treated with Resection.
Authors: Harrison Lyndsay , Mahar Alyson , Coburn Natalie , Boyes Randy , Pugliese Michael , Compton Carolyn , Darling Gail , Davis Laura , Decker Kathleen , Gupta Vaibhav , Kidane Biniam , Manuel Douglas , Ringash Jolie , Turner Donna , Hsu Amy
Published: August 2022

ObjectiveAccurate estimates of survival guide decision-making for patients and oncologists. Advances in the capacity to measure complex tumour biology and patient factors allow for concurrent consideration of clinical, pathological, molecular, and biological markers for prognostication. Clinical prediction tools are a mechanism to combine and personalize these increasingly large amounts of complex information for prognostication.

ApproachWe describe the process of linking routinely collected health data, cancer registry, and pathology report data in two provinces to develop (Ontario, Canada) and validate (Manitoba, Canada) a clinical prediction tool in esophageal cancer. We compared the performance of a base model restricted to patient and disease characteristics available prior to surgical resection (e.g., age, sex, histology, comorbidities), and a more complex model including pathology specimen details (e.g., tumour stage). Cox proportional hazards models were fit to predict death at three years following resection. Internal and external validity was assessed using overall calibration and optimism corrected c-statistics. Equity was assessed through calibration in predefined patient subgroups.

Results2124 patients who underwent surgical resection for esophageal cancer between May 1, 2004 and June 30, 2016 for whom a pathology record was available were included in the study cohort. Median age was 66, with 80% males and 85% adenocarcinomas. Survival data were available until March 31, 2020.  The model with pathology data had superior discrimination and calibration (calibration slope of 1.02 and intercept -0.01, and optimism-corrected c-statistic 0.77), compared to the base model (calibration slope of 0.95, intercept 0.02, and c-statistic 0.60).  External validation is ongoing.

ConclusionOur study demonstrates that prediction models for cancer prognosis built solely on data from health administrative databases may be unreliable. The addition of high-quality pathology report data from electronic medical records or population-based cancer registries is necessary for accurate estimation. Our work provides a framework for combining administrative and clinical data which could be applied to the development of other clinical prediction models.
Associations between dietary patterns and cardiovascular disease risk in Canadian adults: a comparison of partial least squares, reduced rank regression and the simplified dietary pattern technique.
Authors: Lazarova Svilena , Jessri Mahsa
Published: August 2022

ObjectivesWe aimed to compare two data reduction techniques, partial least squares (PLS) and reduced rank regression (RRR), in identifying dietary patterns associated with a high cardiovascular disease (CVD) risk in Canadian adults, and to construct PLS- and RRR-based simplified dietary patterns as well as evaluating associations between derived patterns and CVD risk.

ApproachData were collected from 24-hour dietary recalls of adult respondents in two cycles of the nationally representative Canadian Community Health Survey (CCHS)-Nutrition: CCHS 2004 linked to health administrative databases (n = 12,313) and CCHS 2015 (n = 14,020). Using 39 food groups, PLS and RRR were applied for the identification of an energy-dense (ED), high-saturated-fat (HSF) and low-fiber-density (LFD) dietary pattern. Associations of derived dietary patterns with lifestyle characteristics and CVD incidence and mortality were examined using weighted multivariate regression and weighted multivariable-adjusted Cox-proportional hazard models, respectively. Random and systematic measurement errors were adjusted for in all statistical analyses.

ResultsPLS and RRR identified highly similar ED, HSF, LFD dietary patterns with common high positive loadings for fast food, carbonated drinks, salty snacks and solid fats, and high negative loadings for fruit, dark green vegetables, red and orange vegetables, other vegetables, whole grains, legumes and soy (≥|0.17|). Food groups with the highest loadings were summed to form simplified pattern scores. Although the dietary patterns were not significantly associated with CVD risk, they were positively associated with 402 kcal/d higher energy intake (P-trends <0.05) and higher obesity risk [PLS (OR: 2.09; 95% CI: 1.62, 2.7) and RRR (OR: 1.76; 95% CI: 1.44, 2.17)] (P-trends <0.0001) in the fourth quartiles as compared to the first.

ConclusionPLS and RRR were shown to be equally effective for derivation of a high-CVD-risk dietary pattern among Canadian adults. This research highlights the importance of leveraging linked data to inform public health nutrition policies. Further research is warranted on the role of major dietary components in cardiovascular health.
PENGARUH DIVERSITAS DEWAN DIREKSI TERHADAP NILAI PERUSAHAAN
Authors: Pramesti Aryanti Ariesta , Nita Riski Aprillia
Published: August 2022

The diversity of gender, age, tenure, educational background and nationality are factors that companies must consider when selecting someone to serve on the company's board of directors. The purpose of this study is to analyze the effect of board of directors diversity on firm value. This research was conducted on Property, Real Estate, and Building Construction sector companies listed on the Indonesia Stock Exchange in 2016-2020. The sample of this study was selected using purposive sampling. This study obtained data from 56 companies with a total sample used in this study as many as 236 companies. Testing this hypothesis using multiple linear regression test with SPSS software version 24. The results showed that gender diversity, educational diversity and tenure diversity had an effect on firm value, while age diversity and nationality diversity had no effect on firm value.
Androgen levels in blood and follicular fluid of IVF patients with diminished ovarian reserve
Authors: Gavisova AA , Shevtsova MA , Kindysheva SV , Starodubtseva NL , Frankevich VE , Nazarenko TA , Dolgushina NV
Published: August 2022

Androgen concentrations in follicular fluid samples collected from patients undergoing in vitro fertilization (IVF) may provide useful clinical indicators. This study aimed to analyze possible associations of the androgen levels in follicular fluid and blood plasma in patients with diminished ovarian reserve (POR) in IVF programs. Cross-sectional study with a parallel group design, conducted in 2019–2021, enrolled 300 patients with infertility, aged 18–42 years, applying for assisted reproduction involving IVF/intracytoplasmic sperm injection and embryo transfer. The androgen profiles of blood plasma and follicular fluid were determined by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Androgen concentrations in blood plasma and follicular fluid, particularly those of dehydroepiandrosterone (DHEA-S), androstenedione and total testosterone, significantly correlated. The results implicate androgen levels in blood plasma and follicular fluid as early markers of POR in patients with infertility.
Genetic testing in health care practices (adapted from an empirical study)
Authors: Bogomiagkova ES
Published: August 2022

The article contains the results obtained during an empirical study of health care practices among people of a large Russian city implemented in a combined strategy in 2020–2021. Our focus remains on the reference of citizens to the procedure of DNA diagnostics as a novel instrument of health-saving behavior and attitude to genetic knowledge in general. The obtained data allow concluding that genetic testing is not widely popular among population today, as only 9,5% of those interviewed have ever done it. DNA diagnostics is more frequently used by young women and men with high income and don’t trusting modern medicine, which probably reflects the actual condition of the market of genetic services in our country. Apart from financial possibilities, involvement into consumer genomics is influenced by insufficient trust in DNA information, and suspecting that players on the market of genetic services obtain economic profit. However, the most important argument against it consists in the discovered discrepancy between perception of genetic data as something inevitable and currently popular ideology of healthy lifestyle, meaning that a person can influence the outcome of the efforts made. As a result, research participants are not willing to become the everlasting ‘patients-in-waiting’ even in case of existing symptoms, but implement their ‘right not to know’. Under these conditions, an important task includes organization of active promoting awareness that unlocks potential, capabilities and limitations of genetic diagnostics.
Uroven' androgenov v krovi i follikulyarnoj zhidkosti u zhenshchin s besplodiem i snizhennym ovarial'nym rezervom v programmah VRT
Authors: Гависова А. А. , Шевцова М. А. , Киндышева С. В. , Стародубцева Н. Л. , Франкевич В. Е. , Назаренко Т. А. , Долгушина Н. В.
Published: August 2022

Koncentraciya androgenov v obrazcah follikulyarnoj zhidkosti u pacientok v programmah vspomogatel'nyh reproduktivnyh tekhnologij (VRT) mozhet byt' svyazana s processami oogeneza i embriogeneza. Cel'yu issledovaniya bylo proanalizirovat' svyaz' urovnya androgenov v plazme krovi i follikulyarnoj zhidkosti u pacientok s besplodiem i snizhennym ovarial'nym rezervom yaichnikov v programmah VRT. Provedeno odnomomentnoe issledovanie v parallel'nyh gruppah 300 pacientok 18–42 let s besplodiem s 2019 po 2021 gg., obrativshihsya dlya provedeniya programmy EKO/IKSI i PE. Opredelyali androgennyj profil' v plazme krovi i follikulyarnoj zhidkosti metodom mass-spektrometrii zhidkostnoj hromatografii i tandemnoj massspektrometrii (VEZHKH-MS/MS). Poluchennye rezul'taty pokazali, chto androgeny v plazme krovi i follikulyarnoj zhidkosti, a imenno urovni DGEA-S, androstendiona i obshchego testosterona, mogut byt' rannimi markerami snizheniya ovarial'nogo rezerva (SOR) u zhenshchin s besplodiem. Statisticheski znachimaya korrelyacionnaya svyaz' mezhdu urovnyami androgenov v krovi i follikulyarnoj zhidkosti svidetel'stvuet ob ih vklade v formirovanie snizheniya ovarial'nogo rezerva. Takim obrazom, pri snizhennom ovarial'nom rezerve vyyavleno snizhenie koncentracii androgenov v plazme krovi i v follikulyarnoj zhidkosti, chto svidetel'stvuet o roli androgenov v processah follikulogeneza, takih kak testosteron i androstendion.
Reactive Power Compensation for Preventing Voltage Instabilities in Distribution Lines Enriched with PV Power Plants
Authors: M. Averbukh  , S. Rajput  , I. Amiel  , Z. Danin
Published: August 2022

The efficient voltage regulation method by capacitive reactive power usage is represented in the article. The stochastic electricity generation of multiple PV stations placed in local distribution lines induces voltage instabilities. These voltage fluctuations may overcome the allowable limits and cause technical problems and economic losses. The method of applying reactive power generated by a capacitor bank at the load is proposed. Primarily, a strict analytical solution of non-linear equations describing voltage deviations in the distribution line connected with photovoltaic systems was obtained. The control system can fast select optimal capacitors based on the analytical solution and then connect them smoothly to a load. The developed experimental setup verified and approved the correctness and accuracy of theoretical analysis. Experimental measurements confirmed the proposed method’s ability to improve voltage stability in distribution grids. The proposed method is supposed to be used together with the transformer tap-changers in electrical substations. The capacitive power is applied in a time of inappropriate voltage deviations only and is disconnected as the tap-changer corrected the transformation ratio.
Artificial Neural Networks-Based Method for Enhancing State Estimation of Grids with High Penetration of Renewables
Authors: S. Cosic  , I. Vokony
Published: August 2022

This paper addresses state estimation as one of the most essential mechanisms in real-time operation and control of modern power systems,and proposes a novel solution to the issue of poor network observability, commonly faced in distribution system state estimation(DSSE) characterized by an ever-increasing penetration of renewable generation. The ongoing transformation from conventional passive, one-directional power systems to active smart grids necessitates more accurate and reliable system state estimation to achieve optimal system performance. Real-time grid monitoring and control has been a routine task in transmission networks, but distribution grids cannot successfully utilize these capabilities due to different topologies, specific electrical characteristics, the low amountof available real-time measurements, as well as substantial communication effort needed to handle the data. Furthermore, with the advent of distributed generation, new types of loads and the vast surge of prosumers, a substantial amount ofdata is required to maintain system stabilityand controllability. For these reasons, reliable state estimation requires a high-quality creation process of pseudo-measurement, in addition to an efficient algorithm and an extremely accurate estimator.Thus, this paper proposes a novel framework of dynamic estimation methodology that includes the use of Artificial Neural Networks (ANN) in the pseudo-measurements generation process, utilizes Iteratively Reweighted Least Squares (IRWLS) algorithm and Schweppe-Huber Generalized Maximum Likelihood (SHGM) estimator. The efficiency and accuracy of the proposed methodology were assessed and verified on a benchmark network model.
Analysis of the economic feasibility of different floating offshore renewable energies in Canary Islands
Authors: A. Filgueira-Vizoso  , X. Costoya  , D. Cordal-Iglesias  , L. Piegari  , P. Tricoli  , L. Castro-Santos
Published: August 2022

The aim of this paper is to study the suitability of different floating offshore energy technologies in a particular location in economic terms. In this context, their main initial investments and expenses have been taken into account in order to calculate the economic indicators of the economic feasibility study. These indicators are Internal Rate of Return, Net Present Value and Levelized Cost Of Energy. The case study has evaluated the Canary Islands (Spain) and three types of floating offshore renewable energies: offshore wind, wave energy and hybrid systems. The method created generates economic maps, which facilitates the election of the best area where install offshore renewable energy farms in the location selected. In addition, it also allows to select what is the best marine technology to be exploited in this area.
Transformer‐Based Z‐Source Inverter with MVDC Link
Authors: Enrique González-Rivera  , Carlos Andrés García-Vázquez  , Pablo García-Triviño  , Raúl Sarrias Mena  , Francisco Jurado  , Luis Sainz  , Santiago Bogarra  , Felipe Córcoles  , Luis M. Fernández Ramírez
Published: August 2022

Z‐source inverters have attracted considerable attention in renewable energy systems like photovoltaic (PV) systems due to advantages such as buck–boost power conversion in single stage, shoot-through capability, and wide range of input voltage regulation. Transformer-Based Z-source inverters (Trans ZSI) based on magnetically coupled inductors and reduced number of passive components can be used to improve the boost capacity of these inverters, and to increase the voltage levels. Medium voltage DC (MVDC) is being used more and more in distribution grids and renewable energy systems. This paper presents a trans Z-source inverter with MVDC link where renewable energy systems and energy storage systems can be integrated. The active and reactive powers and DC voltage are controlled by acting on the modulation index and shoot-through duty cycle of the converter. The trans-Z-source inverter is evaluated under different operating conditions to illustrate its suitable operation.
Agile digitalization evolution in the energy sector, taking into account innovative and disruptive technologies
Authors: I. Vokony  , I. Taczi  , M. Szalmane Csete
Published: August 2022

The development of technology and science is decisive in the development of social welfare. We are experiencing the fourth revolution in technological development –after the invention of the steam engine; electricity and process automation; and then computer / IT technology – characterized by an interconnected information network. This revolution will affect all related industries, including the energy sector. New solutions, sensors, devices are available, but the main issue is the use of these devices. So-called smart grid technologies have many advantages, but they also present challenges, whether technologically, economically or sociologically and socially [1]. The answers to these challenges are often not traditional, but creative solutions can mean a breakthrough, changing and accelerating the current progress trends. Such solutions and methods can change and advance all segments and areas, from energy to medicine to the beauty industry. The digital transformation and its implications will significantly change the support for the basic functions of energy distribution. Nowadays, it is almost impossible to solve any task or complete a simple work phase without a computer or IT tool, location data, work schedule description, parameters, and so on. Long-term operation and design, proper architecture and design framework are crucial for efficient operation. Enterprise architecture management within large companies usually involves a very complex range of activities [2]: business, IT and organizational information infrastructure. The role of enterprise architecture is becoming increasingly important for developing and growing companies [3]. In our article, we show how recent decades have helped improve the efficiency of network management and how digitalization is becoming an indispensable player in a sustainable, renewable based vision.
Supervision of the energy performance of multi-arrays PV plants by means of bi-monthly violin plots
Authors: S. Vergura
Published: August 2022

Small PV plants are frequently not equipped with a meteorological station, that is decisiveto monitor the energy performance of a PV plant and to detect low-intensity anomalies, as premature ageing, before they become faults. The paper proposes a methodology for PV plant not equipped with a weather station and it is based on a violin plot, thatis a statistical tool that integrate information from box plot and histogram.In absence of environment parameters, the monitoring is done, by comparing each other the energy performance of the arrays constituting the PV plant, that should produce the same environment condition affects all the arrays. The methodology is applied to a real 20kWp PV plant, studying the energy performance for different energy datasets.
ESTIMATING ELECTRICAL ENERGY GENERATION FROM HUMAN MUSCLE EFFORTS
Authors: R. Halfeld  , R. Castro  , M. Cohen  , E. Castro
Published: August 2022

This paper aimed to develop a model to estimate the generation of electrical energy through human muscular effort, using a generator bicycle, connected to the electrical grid. The motivation resulted from the author's experience in distributed electrical energy generation, which identified a difficulty in installing photovoltaic solar generation systems on the top of buildings. As a research methodology, this study used multiple linear regression using time, weight, height, and body mass index (BMI) as independent variables. The model showed promising results, presenting a high adjusted R-squared, respecting the assumptions associated with a linear regression model. The simulations based on the model showed a considerable energy generation potential for Brazil. In conclusion, although the estimated regression model presented a high predictive capability, further studies are recommended before any financial investment.
Hydrogen Technologies to Provide Flexibility to the Electric System: A Review
Authors: Á. Menéndez-Agudin  , R. Rocca  , G. Fernandez  , L. Luengo-Baranguan  , D. Zaldivar
Published: August 2022

Nowadays, the electric system is evolving towards a paradigm shift,with aconstantlyhigher penetration of renewable generation,as well as the electrification of the transport and different industry sectors. This new scenario requires flexibility servicesto be provided totransmission anddistribution grids, toallow theirsafe and reliable operation.From amongst the various optionscurrently investigated, hydrogen technologies are demonstrating great potential in terms of lower energy costs for consumers/prosumers, lower emissions,and better levels of quality and security of supply.This paper providesa review ofthe latest state-of-the-art flexibility services that hydrogen-basedtechnologies can provide to both DSOs and end-users.Thisreview considerscontributions from both academia and industry.
Design of a Hybrid Dryer for Hemp Flowers for the Inter-Andean region of Ecuador
Authors:   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Peralta-Jaramillo J. , Delgado-Plaza E. ,   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Rivera A. ,   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Rivera D. ,   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Polanco C. ,   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Reinoso J. ,   ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, Centro     de Desarrollo Tecnológico Sustentable,Facultad de Ingeniería en Mecánica y      Ciencias de la Producción, Guayaquil. Ecuador, Sosa-Tinoco Ian ,   Electrical Engineering Department, Instituto Tecnológico de Sonora, Mexico, Alvarez Montero X. ,   Vicerrectorado de Investigación y Vinculación, Universidad Estatal de Bolívar. Ecuador
Published: August 2022

The hemp flower has gained relevance in the agroindustrial and medical field worldwide due to the analgesic, antiinflammatory, and antiepileptic benefits that cannabidiol offers. A critical process in post-harvest is drying, as this allows to maintain the intrinsic properties of the flower. This operation requires a constant heat supply that involves high energy consumption. Therefore, a dryer was designed that uses a hybrid heat supply system based on solar thermal and electric energy. For this, a design of the chamber with a dome cover capable of taking advantage of solar radiation was made together with a system of collectors, supported by an electrical resist for periods of low irradiance. A theoretical analysis of the process was carried out considering the speed and temperature as study parameters and was validated by simulation and dynamic fluid modeling (CFD), obtaining that the thermal power to dry 120kg of the flower is 8.52kW, supplied by 4 solar collectors in series, the dome-type cover, and a tubular resistance of 2kW. The proposed design meets the requirements for maintaining a temperature of 50 ° C within the chamber during the drying time and a speed of 0.5m/s, which guarantees that the product is dehydrated without affecting its organoleptic properties and quality. Furthermore, the project will contribute as a benchmark for technological innovation in the use of renewable energy sources in Ecuador.
Device Modeling for GHE Experimental Test
Authors:   Higher Polytechnic School,     University of Jaen. Spain, Extremera-Jiménez Alejandro J. , Gutiérrez-Montes Cándido , Casanova-Peláez Pedro J. , Cruz-Peragón Fernando
Published: August 2022

Ground Thermal Response (TRT) tests are employed to calculate ground thermal characteristics for Ground Heat Exchanger (GHE) design and optimization purposes. There are plenty of 3D models to increase the accuracy of the calculated characteristics, with which the fluid outlet temperature is obtained based on the experimental inlet temperature. To simulate other behaviours not tested in the GHE, it is necessary to correctly simulate the conduct of the fluid inside the test equipment. For this reason, a simple model has been obtained which considers the absorption of heat by the elements of the equipment during an initial time through a variable equivalent heat capacity term and a load factor.
Optimal economic dispatch of hybrid microgrids integrating Energy Storage Systems with Grid-Forming Converters
Authors:   Departamento de Ingeniería Eléctrica, E.P.S., Universidad Carlos III de Madrid. Spain, González de Armas Marcial , Arnaltes Gómez Santiago , Arredondo Francisco , Rodríguez Amenedo José Luis
Published: August 2022

New control strategies based on Grid-Forming converters make possible the operation of isolated microgrids without the support of synchronous generation. This paper proposes an Energy Management System algorithm that optimizes the operation of a microgrid, maximizing the integration of renewable energy and considering the possibility of disconnecting all synchronous generators. The algorithm is applied to a microgrid modelled with real data and two economic dispatch strategies are analysed: the first requires keeping at least one synchronous generator connected to provide frequency regulation following standard practice; and the second considers the disconnection of all conventional generation relying on the capabilities of Grid-Forming converters when sufficient reserve is available. The results show that the proposed strategy reduces the operational cost of the system, as well as solar PV curtailment and diesel consumption.