bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional Model of Railway Automated Design System in Informational-Digital Environment
Authors: Anisimov Vladimir , Bulakaeva Ol'ga , Shkurnikov Sergey
Published: January 2023

Purpose: Development of new technology for automated solution for railway design tasks in informational-digital environment. Methods: Structural system analysis methodology, system theory, the principle of decomposition are applied. Results: Based on analysis results for structure and functional possibilities of widely used modern systems of railway and highway automated design, the procedures sequence for existing technology of railway automated design was defined. Functional model of railway automated design system in informational-digital environment, based on the application of informational modeling technologies, data mining and mathematical optimization methods, is proposed. Practical significance: The proposed functional model represents the basis for the development of automated design system that will allow implementing new technology for railway automated design, reducing labor costs and time for the development of design solutions, improving their quality and efficiency.
Reduction of Electric Power Consumption by Freight Mainline Locomotives 2(3)ES5S According to Operational Trial Results
Authors: Zarif'yan Aleksandr , Shrayber Marina
Published: January 2023

Purpose: To evaluate the reduction in power specific consumption by freight mainline loco-motives 2(3)ES5S when operating in power-efficient mode (automatic speed control in com-bination with discrete-adaptive switch on/off of Traction Electric Drive depending on an in-stantaneous load), obtained from the results of operational tests. Methods: Array records analysis of on-board recorder made it possible to establish the nature of the dependence of locomotive efficiency degree from its power consumption. Way for controlling multi-engine traction electric drive efficiency in traction mode has been developed and patented. Computer modeling has allowed to obtain preliminary estimate to increase power efficiency. Speed au-tomatic controller block is built using finite automation theory method. The proposed changes, aimed at locomotive power efficiency improvement, have been introduced into top-level con-trol system. Final ratings of power consumption have been obtained during operational trials. Results: The analysis of results obtained during two trips on about 7-thousand-ton mass trains along section with hilly profile of 108 km length is presented. Ceteris paribus, during second trip, when electric locomotive was operating in power-efficient mode (discrete-adaptive con-trol of operating traction drive number in combination with speed automatic control), specific consumption reduction of electric power for traction was achieved on 25% in comparison with the first trip when all 12 traction motors were constantly working. Practical importance: Long-term development program of JSC Russian Railways provides for cost consistent reduc-tion for electric power that’s a purchased (consumed) product. In particular, optimization is planned in such direction as reducing specific consumption of power and fuel for train trac-tion.
Synthesis Method of Self-Checking Devices with Calculation Control by Two Diagnostic Parameters with Preliminary Compression of Signals from the Object of Diagnosis
Authors: Efanov Dmitriy , Pivovarov Dmitry , Leonenko Oleg
Published: January 2023

The structure of self-checking digital devices with calculation control by two diagnostic parameters has been proposed. The belonging of being formed in in-built control circuit codeword to constant-weight code “2-out-of-4” is used as a first parameter. A second parameter is the belonging of each being calculated function to the class of self-dual Boolean functions. The specificity of being described in the article the organization structure of self-checking digital devices is the presence of the circuit of preliminary compression of signals from diagnosis object. Its usage allows to cut structural redundancy of end device down essentially. Besides, nevertheless, errors can be masked at the inputs of compression elements. The article underlines the features of the choice of being compressed outputs of diagnosis object and the algorithm is proposed allowing to minimize the risk of undetectable error occurrence at compression scheme output. The algorithm of built-in control scheme synthesis by two diagnosis parameters has been presented which takes into account conditions for the formation of full set of test combinations for testers and elements of transformation in signal correction block. The example of realization of synthesis algorithm for fully self-checking device Logisim is considered. Key features of built-in control scheme are denoted; the scheme is embodied according to the proposed structure. The way of organizing calculation control by two diagnostic parameters is of interest at the synthesis of fully self-checking digital calculation devices and systems.
A method to position a simple strip trial to improve trial efficiency and maximise the value of vineyard variability for decision-making
Authors: Song Xinxin , Bramley Robert G.V. , Evans Katherine J.
Published: January 2023

The main difficulties grapegrowers and consultants face in obtaining robust trial results include time and labour to collect data and land variability that confounds trial results. Spatial approaches that use whole-field designs, sensing technologies and geostatistical analysis enable more efficient data collection and account for the impact of spatial variation on crop responses while generating statistically robust results. However, the practical application of these approaches for vineyard trials requires affordable automation of measurements of viticultural variables and access to skills for geostatistics. A strip approach has been developed to simplify experimentation by allowing the farmer to use a single crop row to trial and analyse data in a spreadsheet. However, guidance is needed as to how to position trial strips in a vineyard block to reveal likely treatment effects across the entire block. Here, we investigated using a covariate to a response variable of interest to position a strip trial to infer treatment effects beyond the trial strip. Strip trials were simulated for two experiments: one comparing three treatments for vineyard floor management on grape yield and another comparing two spray programs for powdery mildew control. Useful covariates for yield or mildew severity were determined using correlation analyses. Trial results were analysed using a moving pairwise comparison of treatments and a moving average of the covariates. Simulated trial strips that incorporated a range of variation in a useful covariate close to that encountered in the whole block showed how yield or mildew severity varied with the covariates along the strips. Importantly, such results provided information about likely crop responses in other parts of the block according to variation in the covariates, thus contributing to better-informed decision-making. Compared to whole-field approaches, this strip approach is more efficient and simpler for growers to implement.
Genetic Diversity and Population Structure of the Peruvian Andean Legume, tarwi (Lupinus mutabilis), With High Quality SNPs
Authors: Huaringa-Joaquin Amelia , Saldaña Carla L. , Saravia David , García-Bendezú Sady , Rodriguez-Grados Pedro , Salazar Wilian , Camarena Felix , Injante Pedro , Arbizu Carlos I.
Published: January 2023

Lupinus mutabilis Sweet (Fabaceae), “tarwi” or “chocho”, is an important grain legume in the Andean region. In Peru, studies on tarwi have been mainly focused on morphological features, however, the have not been molecularly characterized. Currently, it is possible to explore genetic parameters of plants with reliable and modern methods like genotyping-by-sequencing (GBS). We here for the first time used single nucleotide polymorphisms (SNPs) markers to infer the genetic diversity and population structure of 89 accessions of tarwi from nine Andean regions of Peru. A total of 5922 SNPs distributed along all chromosomes of tarwi were identified. STRUCTURE analysis revealed that this crop is grouped into two clusters. A dendrogram was generated using the UPGMA clustering algorithm and, similar to the principal coordinate analysis (PCoA), it showed two groups that correspond to the geographic origin of the tarwi samples. AMOVA showed a reduced variation between clusters (7.59 %) and indicated that variability within populations is 92.41 %. Population divergence (Fst) between clusters 1 and 2 revealed low genetic difference (0.019). We also detected a negative Fis for both populations, demonstrating that, similar to other Lupinus species, tarwi also depends on cross-pollination. SNPs markers were powerful and effective for the genotyping process in this germplasm. We hope that this information is the beginning of the path towards a modern genetic improvement and conservation strategies of this important Andean legume.
Pengaruh Trichoderma harzianum dan Nano Silika Terhadap Penyakit Moler dan Produksi Bawang Merah
Authors: Ishlah Muhammad Akhlishil , Kristanto Budi Adi , Kusmiyati Florentina
Published: January 2023

Twisted disease is one of the important diseases that can decrease shallot yield.The purpose of this experiment was to examine the effect of the interaction Trichoderma harzianum and nano silica on twisted disease and shallot yield. The research was conducted in Platar, Mangunjiwan, Demak and the Laboratory of Ecology and Plant Production, Faculty of Animal and Agriculture Science, Undip, on April – Agustus 2022. The experimental design used factorial completely randomized design with three replications. The first factor was T. harzianum consisted of three levels (P0 = 0 (control), P1 = 10, and P2 = 20 g plant-1). The second factor was nano silica concentration with four levels (S0 = 0, S1 = 1000, S2 = 2000, and S3 = 3000 ppm). The results showed that application of T. harzianum 20 g plant-1 or nano silica 3000 ppm had the lowest disease intensity 2,74 % and 2,48 % observed at 20 days after planting and 11,81 % and 10,81 % observed at 40 DAP. Combination T. harzianum 20 g plant-1 and nano silica 3000 ppm resulted in  the highest yield parameters which were tuber diameter (2,370 cm), number of tubers (6 tubers), tuber fresh weight (36,2 g), and tuber dry weight (28,7 g). Treatments of T. harzianum and nano silica did not significantly affect the infection rate and number of leaves, but application of T. harzianum 20 g plant-1 and nano silica 3000 ppm showed a decrease in twisted disease intensity and the highest shallot yield.
Identification of Morphology and Molecular PCR-RAPD Bactrocera spp. in the Location of Red Guava Crops, Deli Serdang District
Authors: Sari Putri Mustika , Lisa Oviana , Lisdayani Lisdayani
Published: January 2023

Various fruit flies are in Indonesia, but only a few species of fruit flies have been found at the red guava plant in Deli Serdang District. Knowing the species of fruit flies are needed to do the proper control. In addition to morphological identification, it is necessary to carry out molecular characterization to obtain accurate results in characterizing species differences. This study aims to identify the fruit fly based on morphology and molecularly PCR-RAPD for mapping the genetic closeness of the relationship between individual fruit flies. Bactrocera morphologically identified at LIPI, namely B. carambolae, B. papayae, B. caudata, B. albistrigata, B. umbrosa, B. curcubitae, B. tau, and B. kinabalu. For molecular identification PCR-RAPD, shows the dendrogram results from the Neighbor-Joining analysis based on RAPD markers of DNA band characters showing the genetic proximity of eight species divided into three groups of Bactrocera based on their location. The closeness of genetic relationships between individuals was analyzed using Pairwise Distance Calculation which describes the genetic distance between species. The results of Pairwise Distance Calculation ranged from 0.13-0.42. By knowing what species there fruit flies are in red guava plantations in the Deli Serdang district, it can make it easier for farmers to monitor and control fruit flies in red guava plantations.
Dynamic Pattern Recognition Model Based on Neural Network Response to Signal Fluctuation
Authors: Doho Hirotaka , Nishimura Haruhiko , Nobukawa Sou
Published: January 2023

We have proposed a model of dynamic retrieval in associative memory based on temporal input/output correlations under a stimulus-response open scheme of neural networks. This mechanism is different from that of the conventional stationary Hopfield model in which the input signal is used only as information for the initial state of the network. Building upon the fundamental properties of the proposed model, in this paper, we newly evaluate the dependence of identification performance on the signal fluctuation level and on the number of stored patterns by introducing an accuracy rate for known (stored) and unknown (non-stored) patterns, based on the network correlation to the input signal with fluctuation. The results indicate that the dynamic scheme of network response to a fluctuating signal leads to increased efficacy and usefulness.
Optimization Trading Strategy Model for Gold and Bitcoin Based on Market Fluctuation
Authors: Xie Hong-Xia , Feng Yan , Yu Xue-Yong , Hu Yu-Ning
Published: January 2023

As a new type of digital currency, Bitcoin is considered as “future gold” by various scholars. Therefore, this study considers Bitcoin and gold as a group of hedging assets to conduct investment research and it also discusses the investment rules between Bitcoin and gold: prediction of the rise and fall of Bitcoin, comparison of the characteristics of Bitcoin and gold, and the impact of the transaction procedures of Bitcoin and gold on the final trading results, and formulates trading strategies through optimization algorithms. Then, four machine learning algorithms, i.e., LSTM, BP neural network, Adaboost, and Bagging, are introduced to predict the rise and fall of gold and Bitcoin the next day, and then, the entropy weight method is used to synthesize four predicted results to ensure the robustness of the predicted results. To establish the optimal trading strategy, this study considers the maximum expected return as the goal to develop a single-objective optimization model and historical five-day price volatility as a risk factor. In this study, ant colony, simulated annealing, and genetic algorithms are used to solve the single-objective optimization model. Finally, we conclude that Bitcoin, similar to other financial assets, e.g., gold, is sensitive to shocks and volatile and possesses a relatively quiet cycle. When Bitcoin has an asymmetric impact, Bitcoin and gold can equally treat transactions.
Infectivity of Omicron BA.5 Comparison with Original Strain and Other Mutated Strain of SARS-CoV-2 in Japan
Authors: Kurita Junko , Sugawara Tamie , Ohkusa Yasushi
Published: January 2023

Background: Earlier studies have indicated the BA.5 sublineage of Omicron variant strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as more infective than BA.2. Object: This study estimated BA.5 infectivity while controlling other factors possibly affecting BA.5 infectivity including vaccine effectiveness, waning effectiveness, other mutated strains, Olympic Games, and countermeasures. Method: The effective reproduction number R(t) was regressed on shares of BA.5 and vaccine coverage, vaccine coverage with some delay, temperature, humidity, mobility, shares of other mutated strains, countermeasures including the Go to Travel Campaign, and the Olympic Games and associated countermeasures. The study period was February 2020–July 22, 2022, using data available on August 12, 2022. Results: A 120 day lag was assumed to assess waning. Mobility, some states of emergency, vaccine coverage and those with lag, and the Delta and Omicron BA.2 proportions were found to be significant. The omicron BA.1 proportion was significant, but with an unexpected sign. The estimated coefficient of BA.5 was negative but not significant. The Go to Travel Campaign was significantly negative, indicating reduced infectivity. The Olympic Games were negative but not significant, indicating that they did not raise infectivity. Discussion: The obtained estimated results show that BA.5 did not have higher infectivity than the original strain. It was lower than either Delta or Omicron BA.2 variant strains. That finding might be inconsistent with results obtained from earlier studies. This study controlled several factors potentially affecting R(t), though the earlier studies did not. Therefore, results from this study might be more reliable than those of earlier studies.
Risk Communication During the COVID-19 Pandemic in the Era of Social Media
Authors: Feng Changchun , Umaier Kabilijiang
Published: January 2023

The widespread application of social media in the field of crisis management has been adopted globally. In recent years, the role of social media in emergencies has grown, especially during the coronavirus disease 2019 (COVID-19) pandemic. This study explores the different roles played by social media in the government, the media, and the public during the pandemic through the key nodes of information dissemination at each developmental stage of crisis risk communication. The results indicate that in a government-led environment, in which social media is the link and the public is the core, attention must be directed towards the key role of social media as a “whistleblower” during the incubation period of a crisis event. Moreover, a new gatekeeping mechanism that integrates the public, the media, and the government should be formed to improve emergency management during crises.
Effect of Proportion of Aloe Vera Porridge with CMC (Carboxy Methyl Cellulose) Concentration on Characteristics of Ice Cream
Authors: Ulum Misbachul , Hudi Lukman , Azara Rima
Published: January 2023

This study aims to determine the effect of the proportion of aloe vera with CMC concentration on the characteristics of ice cream. This study used a factorial Randomized Block Design (RAK) with 2 factors and was repeated 3 times. The first factor is the concentration of aloe vera pulp with 3 levels, namely: L1 = 40% aloe vera pulp, L2 = 30% aloe vera pulp, L3 = 20% aloe vera pulp. The second factor is the concentration of the stabilizer CMC (Carboxy Methyl Cellulose) with 3 levels, namely: C1 = 0.0% CMC, C2 = 0.1% CMC, and C3 = 0.2% CMC. The variables observed in this study were the analysis of vitamin C levels, viscosity, melting rate, physical color. analysis of total dissolved solids (TPT) and organoleptic tests (taste, aroma, and texture). The data obtained were analyzed using analysis of variance, if the results of the analysis showed significant differences, it would be continued with the 5% level of Real Difference Test (BNJ), for organoleptic tests were analyzed using the Friedman test. Based on the data obtained, the best treatment was aloe vera ice cream with 20% aloe vera pulp treatment and 0.2% CMC concentration (L3C3) which showed 0.14% vitamin C, total soluble solids 29.47°Brix, viscosity 107, 33 mPas, the value of lightness color is 81.91, the value of redness is -2.93, the value of yellowness is 24.51, the melting rate is 87.09 minutes, the organoleptic color is 3.73 (usually - like), the organoleptic aroma is 3.50 (usually - like) ), organoleptic texture 3.93 (like - very like), organoleptic taste 4.00 (like very much).
Band of Brothers y cómo aprovechar la visión de la Segunda Guerra Mundial según HBO
Authors: Dávila Vargas-Machuca Miguel
Published: January 2023

Hermanos de sangre (Band of Brothers, HBO, 2001) es considerada desde su estreno como una de las mejores series de la historia, con una incontestable calidad que diluye las fronteras entre televisión y cine. Su posición privilegiada en la historia de la televisión y su ejemplo de producción espectacular la han convertido en un paradigma para otras muchas series históricas o épicas posteriores. Como adaptación de la novela homónima de Stephen Ambrose, está construida sobre una sólida base histórica, ofreciendo a la audiencia un resultado muy atractivo fundado en unos hechos por fuerza parciales respecto a un conflicto tan amplio como en el que sitúa su acción, la Segunda Guerra Mundial. Pero tanto su argumento como las singulares herramientas narrativas que utiliza la convierten en un complemento audiovisual muy valioso que puede aprovecharse para apoyar al conocimiento y a la enseñanza sobre ese conflicto tan determinante en el mundo del siglo XX e incluso en el de nuestro presente del siglo XXI.
Persepsi Siswa mengenai Guru Close Minded dalam Pembelajaran
Authors: Putra Ilham Andika , Mahmudah Fitri Nur
Published: January 2023

Guru merupakan pelaku utama dalam mencerdaskan kehidupan bangsa, akan tetapi dalam pelaksanaan tugasnya dalam pembelajaran tentu memiliki kendala dan masalah. Salah satu masalah pembelajaran yang timbul dari faktor guru adalah sikap yang berpemikiran tertutup atau close minded. Hal ini membuat proses pembelajaran menjadi tidak maksimal. Penelitian akan digali fenomena tersebut dari sudut pandang siswa sebagai orang yang merasakan langsung dan berinteraksi langsung dengan guru yang memiliki sikap close minded. Metode yang digunakan dalam penelitian ini adalah metode kualitatif fenomenologi dengan teknik pengumpulan data menggunakan metode wawancara. Partisipan dipilih dengan teknik purposive sampling, sehingga proses pemilihan responden harus memenuhi kriteria yang sudah ditentukan sebelumnya. Hasil penelitian ditemukan bahwa pertama guru close minded memiliki interaksi yang searah,pasif karena hanya fokus untuk menyelesaikan tugas, kurang menguasai kelas, dan hanya peduli pada siswa pintar. Kedua, belajar dengan guru close minded memiliki suasana belajar yang membosankan, kaku, monoton, dan tegang akibat proses pembelajaran yang tidak interaktif. Ketiga adalah feedback atau timbal balik dalam pembelajaran yang cenderung satu arah dan jika dua arah hanya antara guru dan siswa yang pintar saja. Hal ini mengakibatkan siswa lain merasa tersisihkan, memilih diam, malas dan takut salah sehingga takut akan berimbas kepada nilai yang jelek. Guru ideal yang didambakan oleh siswa adalah guru yang mampu membangun interaksi yang baik dengan siswa, cerdas secara psikologis dan emosional.
Adjusting tertiary mental health education during Covid-19: an Australian experience
Authors: Rosenberg Sebastian , Salvador-Carulla Luis , Strazdins Lyndall , Katruss Natasha
Published: January 2023

Globally, tertiary education has been greatly affected by the Covid-19 crisis. In this essay we explore the impact of the pandemic on this educational sector in an Australian setting; specifically, we discuss how the Research School of Population Health at the Australian National University adjusted and adapted to the changing circumstances arising from the pandemic. In this respect, two adjustments (both described in detail in the text) in the way mental health education was delivered at the School were proposed to mitigate the impact of Covid-19 and enhance the university’s capacity to provide quality public health education to students. Thus, this essay shows that it is possible to design educational interventions that surmount the challenges posed by the pandemic. In addition, educators may use the examples cited in this paper to guide them to respond appropriately to the challenges that have arisen in terms of health education due to Covid-19.
Public health education in Colombia: influence on public policies
Authors: De la Hoz-Restrepo Fernando
Published: January 2023

Colombia has a tradition on Public Health education since the mid years of 1950’s. The first cohorts of Public Health academics and workers were trained at the National School of Public Health, which was established, with the support of the Rockefeller Foundation, at the Universidad Nacional de Colombia in Bogota, but later moved to the Universidad de Antioquia in Medellin. In the current context, Colombian Public Health academics have rallied against the neoliberal Health Reform implanted in 1993 that has failed to address the country’s health priorities. Most of the interactions between Public Health academic leaders with government and other decision makers, revolve around the discussion on whether a new way to conceptualize and operate the national health system should be visualized and implemented. So far, the academic sector have been unable to overthrow the main aspects of the Reform −private insurance companies operating, and profiting, on public money− but they have demonstrated how inequalities in health access have widening under the Health Reform and how it have been unable to improve the health situation of the population.
Governmental public health in Taiwan
Authors: Chan Chang-Chuan , Sally Chen Chi-Hsin
Published: January 2023

A healthy and safe public health environment is a fundamental responsibility of government; achieving it requires collaboration across multiple sectors. Public health services include, forexample, vaccination and quarantine for infectious diseases; health promotion, such as anti-smoking campaigns for noncommunicable diseases; and health insurance for universal health coverage. All these services require intersectoral actions in which the government must play a fundamental role, either partially or totally. The Taiwanese outlook on governmental public health infrastructure and professionalization of public health is given in this paper. It also describes the national governmental public health measures that were employed during the Covid-19 pandemic and discusses the challenges ahead for the country’s governmental public health. Governmental public health is essential and should not be affected by changes in political forms or socioeconomic development. Instead, effective governmental public health will promote these developments while protecting citizens’ right to health.
Tradition, leadership and innovation in public health education. Commemorating the 100th anniversary of ESPM
Authors: Middleton John
Published: January 2023

Health is a global concern. No one country or health system can tackle public health problems on their own. Climate change, enironmental degradation, conflict, human trafficking and migration, substance addictions, the uncontrolled corporate health damage caused by multinational corporations, economic catastrophe, global market collapse- all these require concerted public health action from local to global level. Schools of public health need to be equipped to educate, train and research problems of the health of the public and planet in the 21st century. The need for actions by schools of public health has never been more vital.
Towards a unified curriculum system based on a public health holistic approach. Renovation of the academic programs at the School of Public Health of Mexico
Authors: Ferreira-Guerrero Edith Elizabeth , Galván-Portillo Marcia Verónica , Ángeles-Llerenas Angélica , Bahena-Botello Arlette , Llano-Tapia Gemma Clara , López-Carrillo Lizbeth , Lazcano-Ponce Eduardo , Rodríguez Mario Henry
Published: January 2023

Public health training cannot be practiced in isolation, but rather within the framework of substantive conceptual visions, the organizational structure and teaching culture in a broad sense. The School of Public Health of Mexico (ESPM), in the mist of its 100th anniversary, is implementing an educational restructure with the guidance of conceptual and ethical principles. The restructure of the academic pro­grams will follow a constructivist pedagogical model, based on renewed institutional practices that integrates research, teaching and community outreach, making for truly transfor­mative learning. The new design of the whole structure of its academic programs has the objetive of making them flexible, less technical-based but more practical, and a within an uni­fied curricular system that articulates and allows continuity between master’s degrees and doctorates programs. In the new structure, the curriculum will have a common core for all the academic programs, emerging from the study of the essential bases of public health, human rights, including gender and social perspectives, principles of global health, ethics of public health practice, environmental and animal health inferences and community outreach in the form of social retribution. The Institute’s research groups will be the functional units for investigation and teaching, thus students will be integrated into these at an early stage, under the guidance of a tutor. In this context, the requirements for a comprehensive, unifying and at the same time flexible cur­riculum will support training of Public Health with a holistic approach. The current programs were analyzed including the review of their courses, regarding the pertinence of their contents and proposed competencies. We present herein a description of these observations, and propose a new com­mon core (conceptual-operative) with compulsory courses as the base for all programs. The participation of all academic bodies in reviewing the proposed new common core, as well as the syllabus and courses, identified those that are essential in each program’s study concentration area, is indicated.
Rabies, the cause of fatal encephalitis
Authors: Torres-Pérez Manuel Elizafán , Reyes-Cortés Idarmis Brisseida , Romero-Ramos Erik Mauricio , Reyna-Osorio Daniel Alejandro , Serrano-Murillo Mónica , Martínez-Manjarrez Jorge Arturo , Kuri-Álvarez Alfredo , Arriaga-Ponce Jesús Vladimir , Sierra-Díaz Erick
Published: January 2023

To describe the clinical progression and medical protocols applied in a 41 year old man who was bited by a bat three months before. The patient did not ask for medical care until acute tremor and pain in the right thoracic limb and hydro­phobia started. For a history of a wild animal bite associated with a unique clinical condition, we suspected of rabies encephalitis, confirming the diagnostic by pathology after his death. This case ocurred in Guadalajara, Jalisco, México, in April, 2022. The last case of human rabies reported in Jalisco secondary to bat bite was almost 30 years ago. As an uncomon disease, medical personnel and facilities should be prepared to attend this sort of cases after clinical suspicion. For the present case, the medical history was the key for diagnosis. Rabies is a disease caused by the neurotropic virus belonging to the Rhabdoviridae family whose prognosis is bleak, with mortality close to 100% and therapeutic options limited. This case emphasizes the high mortality of rabies virus infection and the importance of increasing awareness and education to the public in general, with regard to applying the vaccine as post-exposure prophylaxis.
Diseño de una estrategia de comunicación para la promoción del uso del etiquetado de advertencia en niños, niñas y adolescentes mexicanos
Authors: Jáuregui Alejandra , Pacheco-Miranda Selene , Ayvar-Gama Yatziri , Alejandro-Torres Nelson Zacarías , Cuno Amalia , Espinosa-de Candido Anabel Fiorella , Martínez-Cruz Marina Isabel , Bonvecchio-Arenas Anabelle , Barquera Simón
Published: January 2023

Objetivo. Describir el proceso para diseñar una estrategia de comunicación con el fin de promover el uso del etiqueta­do frontal de advertencia (EFA) y la selección de alimentos saludables en niños, niñas y adolescentes (NNA) mexicanos. Material y métodos. Estudio de cuatro fases con esco­lares, adolescentes y cuidadores: 1) investigación formativa (18 grupos focales, n= 179); 2) talleres de cocreación con NNA (n= 33); 3) diseño de la estrategia, con base en el modelo de comportamiento COM-B; y 4) prueba piloto (seis grupos focales, n= 52). Resultados. La estrategia de comunicación debería mejorar la comprensión del EFA y los conocimientos sobre la relación de los ingredientes críticos (calorías, grasas saturadas, grasas trans, sodio, edulcorantes y cafeína) y la enfermedad; asimismo, debería resaltar las consecuencias positivas de una alimentación saludable y las negativas del consumo excesivo de alimentos con sellos, así como destacar que los alimentos naturales tienen un menor costo y mejor calidad que los alimentos con sellos; se deben ofrecer sugerencias de preparaciones atractivas y saludables con alimentos naturales. Conclusión. La investigación formativa y la participación de NNA en la creación de la campaña fueron esenciales para diseñar una estrategia cultu­ralmente pertinente con potencial de impacto. El proceso y los resultados del estudio podrían informar sobre esfuerzos en contextos parecidos al de México.
The influence and leadership of the Escuela de Salud Pública de México in Mexican health
Authors: Carrillo Ana María
Published: January 2023

Not available
Physics-Informed Neural Networks and Capacitance-Resistance Model: Fast and Accurate Oil and Water Production Forecast Using End-to-End Architecture
Authors: Gladchenko Elizaveta S. , Illarionov Egor A. , Orlov Denis M. , Koroteev Dmitry A.
Published: January 2023

Capacitance-Resistance model (CRM) has been a useful tool for fast production forecasts for decades. The unique combination of simplicity and physics-based nature in this data-driven approach allowed it to stay as an object of scientific interest and get its own place among other types of models capable of giving predictions on flow rates, such as full-scale 3D reservoir models. However, the model simplicity, assumptions, and limitations does not allow wide application of a conventional CRM in complex field cases. A vast majority of studies on CRM are about overcoming its limitations by introducing new coefficients, modifying the analytical form of the equation, etc. Integrating CRM with rapidly developing artificial intelligence (AI) methods seems to be a logical continuation of model evolution.

Recently introduced Physics-Informed Neural Networks (PINN) can preserve CRM's governing equations and coefficients that gives some insights about wells and formations standing out from other popular machine learning and deep learning methods. Moreover, PINN type models give certain flexibility in the choice of architectures – it means that the model architecture can be changed in a way that may assist in solving different problems. Thus, we introduce end-to-end learning of neural networks (NN) while implying some physical constraints. It is intended to overcome one of the major limitations of CRM, which is obtaining predictions for oil and water production rates from total liquid. This way, the additional training of rough approximation fractional flow models that are either not suitable for the case or may require the knowledge of reservoir properties is not needed.

In this work, the well-known concept of Capacitance-Resistance models appears in a new form, which allows performing history matching rather rapidly, achieving robustness and forecasting liquid, oil and water production rates simultaneously. To test this new approach, several datasets (both synthetic and real) were used. The results obtained by PINN are compared to those obtained by a conventional CRM. By conventional we mean the analytical solution, which was modified by our research group to take into consideration common real field cases such as shut-in wells, workover operations, etc. by introducing dynamic characteristic coefficients [1].
Advisory System for Drilling Optimization Using Artificial Intelligence and In-Cutter Sensing Data
Authors: Koulidis Alexis , Ahmed Shehab
Published: January 2023

The drilling optimization concept corresponds to enhancing the drilling efficiency by identifying the optimum drilling parameters with respect to bit wear. On many occasions, human interference can reduce the scale of a problem and enhance efficiency, but it has limitations, especially when working with big data and complex machines. This work utilizes in-cutter force sensing data and a scaled-drilling rig to apply an AI-based solution and facilitate drilling optimization.

There are several experimental challenges to building an advisory system: tuning the PID controller, continuous communication and feedback between hardware and software, data synchronization, and system efficiency. The core capability that enables drilling optimization is in-cutter sensing, which allows evaluating the forces acting on a PDC cutter. Initially, an extensive experimental study is conducted to record and process the drilling data with sharp cutters. Weight on bit, torque, rotational speed and rate of penetration are measured and sampled at the same frequency as the in-cutter force sensing. Rock samples with different mechanical properties are utilized and tested in atmospheric conditions.

The AI-based solution utilizes the data from the PDC cutter and the scaled-drilling rig structure to identify the optimum range of the drilling parameters depending on the mechanical properties of the rock samples. Artificial Neural Network (ANN) is utilized to predict the rate of penetration for samples with different uniaxial compressive strength. The supervised machine-learning models are trained on input variables such as weight on bit, torque, rotational speed, uniaxial compressive strength, vibrations, and more importantly the measured force at the PDC cutter.

A physics constraint is applied for torque, weight on bit and vibrations to guarantee that the output of the ML model is within the operating ranges. For each sample, approximately 100 data points are extracted per variable, with 70% for training, 15% for validation and 15% for testing. Cross-validation is used to enhance the robustness of the ML model. The results show that prediction performance is enhanced when the in-cutter sensing measurement is implemented as an input variable. The reliability of the ML models is tested on samples with different mechanical properties, with the results indicating an accurate prediction of the rate of penetration.

The paper demonstrates an innovative workflow that combines AI and in-cutter sensing data to enhance the drilling efficiency with respect to system's mechanical limitations. The model provides a reliable and rapid decision to identify the optimum drilling parameters with respect to physics constraints.
Optimization of Architecture and Operation of Intelligent Wells Under Geological and Economic Uncertainties
Authors: Khan Zurwa , Tafreshi Reza , Wahid MD , Retnanto Albertus
Published: January 2023

Intelligent Wells (IWs) actively manage oil production and water breakthrough. IWs comprise Inflow Control Valves (ICVs), which are automated valves with multiple openings. In reservoirs with geological uncertainties, ICVs can be used to optimize production in different segments of IWs. However, economic uncertainties related to the varying oil prices and the high capital cost of IWs also need to be examined. The objective is to maximize the Net Present Value (NPV) of a horizontal Intelligent Well (IW), undergoing geological and economic uncertainties, by changing IW architecture and number, flow control position, and placement of Inflow Control Valves (ICVs), while satisfying safety standards, equipment capacity constraints and minimizing water breakthrough. To simulate the pressure drops for different scenarios within the IW for the optimization problem, a mechanistic model of a Conventional Wellbore (CW) and ICVs has been considered for oil-water flow. Nested loops were employed to maximize the objective function. The inner loop optimized the placement and flow control position with a genetic algorithm. The outer loop optimized the number of ICVs and IW's physical dimensions with a gradient-based method. Validating with experimental data resulted in 30.1% root mean squared error. The Pressure, Volume and Temperature (PVT) properties for oil and water were determined with empirical correlations. Sensitivity analysis indicated that the number of ICVs is the most essential variable among all variables for maximizing NPVs. The presented optimization strategy is successful at increasing NPVs relative to conventional wells. Unlike conventional literature, current optimization strategy not only focuses on design or production of IW, but it also considers both, the design and the IW's production optimization simultaneously.
Digitally Augmented Subsurface History Match (DASH-Sim): A New Frontier in Reservoir Simulation History Matching
Authors: Baig Raheel , Nooruddin Hasan
Published: January 2023

History matching is a long-standing industry challenge and resource-intensive process. In this paper, we introduce a new method in the area of automated history matching algorithms, called Digitally Augmented Subsurface History Match (DASH-Sim), that focuses on calibrating the permeability property at the field level. The new approach captures the global displacement mechanism as observed in the field by capitalizing on time-lapse surveillance data.

Time-lapse surveillance data is used to derive an accurate representation of subsurface saturation as a function of time. We refer to this dynamic saturation distribution as the 4D saturation model. The DASH-Sim method minimizes the difference in saturation between the 4D model and the simulation model at all timesteps by adjusting the 3D grid-cell permeability values. A novel mathematical relationship is introduced that calculates the required permeability calibration in the simulation model as a function of the underlying rock quality and the difference in water saturation between the 4D saturation model and the simulation model. The algorithm considers the dynamic nature of saturation by successively updating the static permeability property at each timestep of the corresponding observed 4D saturation.

A synthetic case study is presented in which the new algorithm is applied. First, a truth case simulation model was run using a permeability distribution from which water saturations were recorded as a function of time. The simulated water saturation over time using the truth case permeability was treated as the observed 4D saturation model. Next, a significantly modified permeability property was replaced in the simulation model resulting in a new water saturation distribution over time. The DASH-sim algorithm was then used as an inverse history match calibration process to generate permeability modifications guided by the objective function to minimize mismatch in saturations between the observed 4D saturation model and the numerical simulation model. Results indicate a very good history match is achieved in an automated manner, reducing the turnaround time for such tasks by orders of magnitude.

The inverse problem of history matching subsurface reservoir models is a very challenging and time-consuming task. The DASH-Sim offers a new approach to automate this tedious task consistently by considering both surface-level production and subsurface time-lapse measured surveillance data.
A Novel High-Speed AI-Physics Hybrid Model to Predict the Reservoir Behavior; A Case Study
Authors: Qubian Ali , Zekraoui Mohammed Ahmad , Mohajeri Sina , Mortezazadeh Emad , Eslahi Reza , Bakhtiari Maryam , Al Dabbous Abrar , Al Sagheer Asma , Alizadeh Ali , Zeinali Mostafa
Published: January 2023

Reservoir simulation is widely applied to model and manage subsurface flow operations. However, due to the nonlinear nature of the governing equations and the multiscale character of the geological description, executing numerical simulations can be expensive and increasingly slow. In this study, we propose an innovative high-speed simulation method to build a model that is capable to predict the field's behavior. In this study, a novel AI-Physics hybrid model was proposed for reservoir simulation. Classical numerical simulation and deep learning neural networks are coupled together to create an AI-Physics hybrid reservoir simulation. As a result, a model was obtained with predictive capabilities to forecast the field's behavior. Then, we combined AI-Physics history training with blind test prediction calculation of remaining oil maps. Finally, forecast scenario definitions based on the remaining oil map were created by the AI-Physic model. The proposed high-speed simulation model can reduce the history matching and scenario assessment time by 90 to 95%. According to its capabilities, three improved forecast scenarios were created based on a predefined scenario. These improved scenarios can produce a significant million standard barrels more oil than the original development scenario within three years. This technology eliminates limitations for multiple scenario assessments. In our AI hybrid model, the power of dynamic reservoir simulation is combined with a modern machine learning approach to "Evergreen" forecasts in reservoir assets. Consequently, the simulation resulted in a sub-optimal shortcut between model updates and inconsistencies in production forecasting. Moreover, applying deep learning methods to focus on the critical reservoir properties intelligently leads to tremendous time-saving in the static model update life cycle. In fact, with this novel simulation that we implemented, the new production data could be incorporated within minutes to regenerate more reliable and up-to-date forecasts. This simulation generates ‘up-to-date remaining hydrocarbon maps interactively, so the operator can continuously optimize the infill drilling locations between Field Development Plan cycles.
Standardizing and Automating Well Log Data Sources in Subsurface Applications
Authors: Kumar Pranav , Krishnapillai Anish
Published: January 2023

Objectives/Scope

Well operations team deals with series of Well log data through real time system and any other data exchange system. This data is streaming through different channels and with a naming convention implemented by the respective originator of the data or the system. The goal of the data is to be used for Studies and Operations. This paper mentions the implemented data workflow to deal with Well log data sources, channels, mnemonics and sharing through a standardized workflow.

Methods, Procedures, Process

The Real time data streaming through WITSML servers is connected directly into Subsurface application by proper authorization and access. The data naming conventions was collected from all the specific service provider, and it was than mapped with standard naming that is used in the organization. The data consists of several different type of mnemonics. Example could be XXX_P10H, XXX_ROBB, XXX_MCIA, XXX_GRM2, where XXX stands for vendor specific name. The frequency of Real time data depends on the streaming and some time it takes time to update data. In parallel, memory data for the same wells are made available to the Operations team through a defined exchange system. A mapping was developed between Log mnemonics from the vendors and the standard naming convention proposed by the Operations team. Python scripts were used to automatically rename and map any log mnemonics and aliases coming to the subsurface application. For the memory data, other scripts work, which goes to the individual LAS files and check the mnemonics and changes them back to standard naming convention.

Results, Observations, Conclusions

Implementation of the mapping and python scripting has helped engineers achieve their objectives in efficient way. They do not have to worry about individually renaming the specific log and channel names. Data quality has improved by comparing the real time and memory data sources. User experience has enriched and enhanced with the implemented data mapping and standardization workflow. For example, in case of Neutron log sometimes, users must change units from % to Fraction for using it for other Petrophysical calculations. This process is now automated, and data gets converted with the defined standard.

Novel/Additive Information

By mapping and standardizing the way of comparing data sources, logs and channels has improvised the data quality, data sharing and data governance related issues. This is a continuous process which requires further improvements and result oriented approach.