bluuebunny/crossref_metadata_2025 huggingface dataset:
Тренування штучних нейронних мереж з пороговою функцією активації методом оберненого поширення похибки
Authors: Дзінько Ростислав Ігорович
Published: December 2021

В даній статті розглядається спосіб тренування нейронних мереж прямого поширення сигналу з оберненим поширенням похибки з використанням порогової функції активації (Хевісайда). В зв’язку з тим, що порогова функція не є диференційовною на області визначення, прямо використовуватись при тренуванні штучних нейронних мереж вказаним методом вона не може. Саме тому дана робота пропонує метод імітації даної функції альтернативними, в результаті чого зростає швидкість навчання нейронної мережі до отримання певного порогового значення похибки
Модель підтримки безпеки ресурсів cloud систем на рівні інфраструктури
Authors: Волокита Артем Миколайович
Published: December 2021

Надання гарантій безпеки - одна з основних проблем сучасних хмарних обчислень. Саме відсутність достатніх гарантій безпеки стає основним стримуючим фактором при переході в «хмару». Стаття присвячена підтримці безпеки cloud computing на рівні інфраструктури. Розглядаються основні загрози безпеки хмарних обчислень разом зі структурою типової хмарної системи. Наведено типові рішення даних проблем, а також переваги і недоліки кожного рішення. Побудована таблиця покриття задач підтримки безпеки розглянутими раніше методами. Визначено, що дані рішення окремо не забезпечують повноцінне покриття задач підтримки безпеки cloud computing. Описана узагальнена модель підтримки безпеки cloud систем на рівні інфраструктури. Окреслено можливі перспективи даної моделі та шляхи її подальшого розвитку.
Identification of waste: DOWNTIME in the outpatient prescription services at the pharmacy installation of Rumah Sakit Islam Siti Hajar Mataram
Authors: Atikah Nur , Parhatiwi Sari Nanchi , Pertiwi Ajeng Dian , Utami Evi Fatmi , Firman Firman
Published: December 2021

Background: The hospital pharmacy installation is a health service unit that is required to provide professional services and improve quality which is oriented towards achieving patient satisfaction. Waste identification in pharmaceutical services is important because it has an impact on stakeholder satisfaction. Objective: Identifying waste using the DOWNTIME method for the outpatient prescription services at the pharmacy installation of Rumah Sakit Islam Siti Hajar Mataram. Methods: The study used the cross-sectional design, with the population being all outpatients who were provided with pharmaceutical services during February – April 2019 as well as all staff. Data were tabulated and analyzed descriptively. Critical waste was obtained through questionnaires and the root causes of critical waste were obtained through in-depth interviews with 5-why methods. Results: Waste waiting had the highest rate compared to other wastes, reaching 44% or 53 out of 121 respondents, followed by inventory (26%), extra processing (19%), transportation (14%), defects (14%), motion (13%), over production (8%), and non-utilized skills (7%). Meanwhile, from the staff respondents, waiting was also the highest waste (18%), followed by inventory (16%), motion (13%), over production (12%), transportation (12%), non-utilized skills (10%), extra processing (10%), and defects (9%). The root cause of waste waiting was the frequent drug unavailability due to delays in payment of services from the cooperating party to the hospital as well as the narrow service areas. Conclusion:Waste waiting became the critical waste with the highest percentage of dissatisfaction in the patient respondents (44%) and staff respondents (18%). Keywords: Waste, DOWNTIME, outpatient prescription services, pharmacy installation of RSI Siti Hajar Mataram
The Solar System: Nature and Mechanics
Authors: Ljubičić Mario
Published: December 2021

Origin, mechanics and properties of the Solar System are analyzed in the framework of Complete Relativity. The analysis confirms the postulates and hypotheses of the theory with a high degree of confidence. During the analysis, some new hypotheses have emerged. These are discussed and confirmed with various degrees of confidence. To increase confidence or refute some hypotheses, experimental verification is necessary. Main conclusions are: - Solar System is a scaled Carbon isotope with a nucleus in a condensed (bosonic) state and components in various vertically excited states, - Earth is a living being of extremely introverted intelligence, life is common everywhere, albeit extroverted complex forms are present on planetary surfaces only during planetary neurogenesis, - anthropogenic climate change is only a part (trigger from one perspective) of bigger global changes on Earth and in the Solar System during planetary neurogenesis, - major extinction events are relative extinctions, a regular part of transformation and transfer of life in the process of planetary neurogenesis.
Energy Potential of Long-Period Oscillations (On the Example of Kakhovka Plain Reservoir, Ukraine)
Authors: Anakhov Pavlo
Published: December 2021

The energy potential of long-period oscillations is estimated by comparing it with watercourse power. The relaxation time of long-period waves is chosen for the estimation time interval, during which their amplitude decreases e (Euler's number) times from the initial one. According to calculations, the amount of energy produced during this time by the watercourse is 9.35–18.71 million kW×h, while the amount of energy of long-period oscillations is 3–6 times less – 1.60–5.48 million kW×h. The components of the economic factor of using long-period waves and currents for electricity production are the predictability of their magnitudes and location of maxima, long-term availability, concentration.
Timescape: A Simple Spatiotemporal Interpolation Tool
Authors: Ciolfi Marco , Chiocchini Francesca , Pace Rocco , Russo Giuseppe , Lauteri Marco
Published: December 2021

We developed a novel approach in the field of spatiotemporal modelling, based on the spatialisation of time: the Timescape algorithm. It is especially aimed at sparsely distributed datasets in ecological research, whose spatial and temporal variability is strongly entangled. The algorithm is based on the definition of a spatiotemporal distance that incorporates a causality constraint and that is capable of accommodating the seasonal behaviour of the modelled variable as well. The actual modelling is conducted exploiting any established spatial interpolation technique, substituting the ordinary spatial distance with our Timescape distance, thus sorting, from the same input set of observations, those causally related to each estimated value at a given site and time. The notion of causality is expressed topologically and it has to be tuned for each particular case. The Timescape algorithm originates from the field of stable isotopes spatial modelling (isoscapes), but in principle it can be used to model any real scalar random field distribution.
Effects of Caffeine Consumption on Attention Deficit Hyperactivity Disorder (ADHD) Treatment: A Systematic Review of Animal Studies
Authors: C. Vázquez Javier , Martin de la Torre Ona , López Palomé Júdit , Redolar-Ripoll Diego
Published: December 2021

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a persistent pattern of inattention and/or hyperactivity-impulsivity. Neurobiologically, ADHD impairments arise from abnormalities in different circuits involving the prefrontal cortex. In face of high rates of diagnosis, alternative/complementary pharmacological therapeutic approaches for ADHD are needed. Although the number of publications that study the potential effects of caf-feine consumption on ADHD treatment have been accumulating over the last years, and caffeine has recently been used in ADHD research in the context of animal models, an updated evi-dence-based systematic review on the effects of caffeine on ADHD-like symptoms in animal stud-ies is missing. To provide insight and value at the preclinical level, a systematic review based on PRISMA guidelines was performed for all publications available up to September 1, 2021. Caffeine treatment increases attention, improves learning, memory and olfactory discrimination, without altering blood pressure and body weight. These results are supported at the neuronal level. Nonetheless, the implication of caffeine in modulating ADHD-like symptoms of hyperactivity and impulsivity is contradictory, raising discrepancies that require further clarification. Our results strengthen the hypothesis that caffeine cognitive effects found in animal models could be trans-lated to human ADHD, particularly during adolescence.
Temporary Immersion System Improves Regeneration of in vitro Irradiated Recalcitrant Rice Embryogenic Calli
Authors: Hernández-Soto Alejandro , Pérez-Chávez Jason , Fait-Zuñiga Rebeca , Rojas-Vásquez Randall , Gatica-Arias Andres , Abdelnour-Esquivel Ana
Published: December 2021

The development of gamma rays mutant rice lines would be a solution for introducing variability in already farmer using varieties. In vitro gamma (60Co) mutagenesis reduces chimeras and allows a faster selection of desired traits but requires laboratory process optimization. The objective of the present work was the in vitro establishment of a recalcitrant rice embryogenic calli, the determination of its sensitivity to gamma radiation (Co-60), sequencing MATK and Rubisco for identification purposes, as well as generation optimization. The radiosensitivity of embryogenic calli resulted in an LD50 of 110Gy, while the 20% lethal dose was 64Gy. All sequenced genes matched perfectly with already reported MATK and Rubisco O. sativa genes with a clear SNP that identifies the local variety related to the southeast Asia Region. Callus induction improves with an MS with 2mg/L 2,4D, and the regeneration was achieved with an MS medium with 3mg/L BAP and 0,5mg/L NAA. The optimized radiation condition was 60Gy with an 83% regeneration in a semisolid medium, allowing a balance between mutation and regeneration. When increased to 80Gy, the regeneration rate falls to 29%. An immersion system (RITA®) of either 60 or 120 seconds every 8hours allowed a systematic and homogeneous total regeneration of the recalcitrant line, in contrast with the semisolid medium that resulted in positive but irregular regeneration. Other well-known recalcitrant cultivars, CR1821, CR1113 also had an improving regeneration in the immersion system, demonstrating its potential use for recalcitrant materials. To our knowledge, this is the first report on using an immersion system to allow regeneration of gamma-ray mutants from recalcitrant rice materials.
The Coordination of Multi-Stage Discounts in a Dual Channel Fresh Agricultural Pro-duce Supply Chain: Minimizing the Loss of Quantity and Quality
Authors: Zheng Xiaojing
Published: December 2021

This paper explores the coordination of the agricultural cooperative to supermarket or E-commerce sup-ply chain, under the condition of quantity loss with a mixed decay function of exponential and logistical distribution. The nature of this process is analyzed, and the corresponding demand and supply functions with single- and multi-stage discount strategies are constructed respectively to create a working model. The optimal discount ratios for supermarkets and agricultural cooperatives in decentralized and central-ized decision-making modes coupled with single- and multi-stage discounts are calculated respectively. Finally, a universal optimal strategy is designed, which can be applied to various quantity decay scenarios and makes the discount strategy more generalized. The results show that discounts can coordinate supply chains more effectively; not only is fresh agricultural produce sold before it starts to rot, but the benefit conflicts arising from both supermarkets vs. cooperatives and traditional vs. E-commerce channels are equilibrated. Further, multi-stage discounts are more effective than single-stage ones, but optimal discount ratios rely on the initial quantity of fresh agricultural produce in the supply chain; its market share in the traditional distribution channel; the potential market size; retail price; the price sensitivity coefficient of the channel; the cross-elasticity coefficient of prices between different channels; and the properties of the quantity loss.
Knowledge, Attitudes and Practices regarding Long-Term Complications of COVID-19 among a Sub-Urban Population in Sri Lanka
Authors: Witharana Chamindri , Siridewa Kithmini , Weerasinghe Manuj , Karunathilake Indika
Published: December 2021

Background Recently, a surge of COVID 19 was observed globally, regionally and nationally. With increasing numbers of cases, the frequency of long COVID is on the rise. Management and control of long COVID depend on changes in respect of human behaviors and requires an understanding of knowledge, attitudes, and practices (KAP) regarding health threats. MethodsA descriptive cross sectional study using online survey to gather data on the socio-economic background, knowledge, attitudes and practices on long-term complications of COVID. Results: Out of 201 respondents, 89.2% participants have heard about long-term complications of COVID 19. Only 35.9% have demonstrated adequate knowledge in the questions relating to co-morbidities and risk factors of COVID-19. A total of 92.2% believe that they should adhere to preventive measures following vaccination. Less than 60 % were following the advice on avoiding unnecessary travel and crowded places. Further, less than 50% were following COVID preventive measures. ConclusionAlthough the majority of participants have heard about long-term complications and common symptoms, the knowledge regarding co-morbidities that can lead to severe disease and long COVID was not satisfactory. The attitudes of the participants indicated increasing concern about long COVID. Practices indicate lack of adherence to key measures such as avoiding crowded places. These findings highlight the need for further increasing of awareness.
Towards a ‘City in Nature’: Evaluating the Cultural Ecosystem Services Approach to Support Urban Green Space Management
Authors: Koh Yi Fan , Loc Ho Huu , Park Edward
Published: December 2021

Cultural ecosystem services has been increasingly influential in both environmental research and policy decision-making, such as for urban green spaces However, its popular definition conflates the concepts of ‘services’ and ‘benefits’ which made it challenging for planners to employ it directly for urban green space management. One the most widely used definition of this non-tangible ecosystem services are “functions of environmental spaces and cultural activities which may then result in the enjoyment of cultural ecosystem benefits”; yet the latter itself have never found its way into official laws and regulations. In this study, via a case study in Singapore, we propose new evidence to re-evaluate and re-position the two of the most important emerging concepts in managing the green spaces in urban areas. Using the transdisciplinary mixed methods of public participation GIS and social media text mining analysis, a wealth of cultural ecosystem services and their associated benefits were reported. This was especially so with regards to recreational and aesthetic services and experiential benefits. Recommendations to improve the park were also suggested, alongside sharing of methodological considerations for future research. Overall, this paper recommends the employment of the redefined cultural ecosystem services conceptual framework to generate relational, data-driven and actionable insights to better support urban green space management, which is not only useful to Singapore governments but also world-wide relevant.
Does Agricultural Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?
Authors: Zhu Yingyu , Zhang Yan , Piao Huilan
Published: December 2021

Agricultural mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sink, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.
Essential Terminology and Considerations for Validation of Non-targeted Methods
Authors: Nichani Kapil , Uhlig Steffen , Stoyke Manfred , Kemmlein Sabine , Ulberth Franz , Haase Ilka , Döring Maik , Walch Stephan G , Gowik Petra
Published: December 2021

Through its suggestive name, non-targeted methods (NTMs) do not aim at a predefined "needle in the haystack". Instead, they exploit all the constituents of the haystack. This new form of analytical methods is increasingly finding applications in food and feed testing. However, the concepts, terms, and considerations related to this burgeoning field of analytical testing needs to be propagated for the benefit of ones associated in academic research, commercial development, and official control. This paper addresses the frequently asked questions around notations and terminologies surrounding NTMs. The widespread development and adoption of these methods also necessitates the need to develop approaches to NTM validation, i.e., evaluating the performance characteristics of a method to determine if it is fit-for-purpose. This work aims to provide a roadmap to approaching NTM validation. In doing so, the paper deliberates on the different considerations that influence the approach to validation and provides suggestions thereof.
Research on a Partial Aperture Factor Measurement Method for the Agri Onboard Calibration Assembly
Authors: Si Xiaolong , Li Xiuju , Chen Hongyao , Bao Shiwei , Xu Heyu , Zhang Liming , Huang Wenxin
Published: December 2021

A partial aperture onboard calibration method can solve the onboard calibration problems of some large aperture remote sensors, which is of great significance for the development trend of increasingly large apertures in optical remote sensors. In this paper, the solar diffuser reflectance degradation monitor (SDRDM) in the onboard calibration assembly (CA) of the FengYun-4 (FY-4) advanced geostationary radiance imager (AGRI) is used as the reference radiometer for measuring the partial aperture factor (PAF) for the AGRI onboard calibration. First, the linear response count variation relationship between the two is established under the same radiance source input. Then, according to the known bidirectional reflection distribution function (BRDF) of the solar diffuser (SD) in the CA, the relative reflectance ratio coefficient between the AGRI observation direction and the SDRDM observation direction is calculated. On this basis, the response count value of the AGRI and the SDRDM is used to realize the high-precision measurement of the PAF of the AGRI B1 ~ B3 bands by simulating the AGRI onboard calibration measurement under the illumination of a solar simulator in the laboratory. According to the determination process of the relevant parameters of the PAF, the measurement uncertainty of the PAF is analyzed; this uncertainty is better than 2.04% and provides an important reference for the evaluation of the onboard absolute radiometric calibration uncertainty after launch.
Effect of the COVID-19 Pandemic on Cost-Related Prescription Nonredemption, Health care Seeking and Hospitalization in Hungary: A Nationally Representative Cross-Sectional Study
Authors: Bekele Bayu Begashaw , Alhaffar Bahaa Aldin , Wasnik Rahul Naresh , Sándor János
Published: December 2021

Background: Although, negative repercussions of inadequate health service use on the health outcomes has been presumably exacerbated by COVID-19, the impact of the pandemic measures has been not evaluated properly yet. Objective: Our study aimed to quantify the COVID-19 pandemic measures’ effect on the general practitioner (GP) visit, specialist care, hospitalization and cost-related prescription nonredemption (CRPNR) among adults in Hungary, and to identify the social strata susceptible to the pandemic effect. Methods: This community-based cross-sectional study based on nationally representative data of 6,611 (Nprepandemic=5,603 and Npandemic=1,008) subjects aged 18 years and above. Data were obtained from the European Health Interview Survey 2019 (EHIS) and International Social Survey Program 2021 (ISSP) for prepandemic and pandemic, respectively. Multivariable logistic regression models were applied to determine the sociodemographic and clinical factors influencing the health care use by odds ratios (OR) along with the corresponding 95% confidence intervals (CI). To identify the social strata susceptible to pandemic effect, the interaction of the time of data collection with level of education, marital status, and ethnicity, was also tested. Results: While, the CRPNR did not changed, the frequency of GP visit, specialist care and hospitalization rate were remarkably reduced by 22.2%, 26.4%, and 6.7%, respectively, during the pandemic in Hungary. Roma proved to be not specifically affected by the pandemic in any studied respect. The pandemic restructuring of health care impacted the social subgroups evenly with respect to hospital care. However, the pandemic effect was weaker among primary educated adults (ORhigh-school vs primary-education =0.434; 95% CI 0.243-0.776, ORhigh-school vs primary-education =0.598; 95% CI 0.364-0.985), and among widows (ORwidowed vs married =2.284; 95% CI 1.043-4.998, ORwidowed vs married=1.915; 95% CI 1.157-3.168) on the frequency of GP visit and specialist visit; and the prepandemic CRPNR inequality by level of education was increased (ORhigh-school vs primary-education =0.236; 95% CI 0.075-0.743). Conclusion: Primary educated and widowed did not follow the general trend, and their prepandemic limited health care use was not reduced further during pandemic, resulting in an inequality reduction. The vulnerability of primary educated to CRPNR was the only gap widened in the pandemic period. This shows that although the management of pandemic health care use restrictions was implemented by increasing the social inequality in Hungary, the prevention of inequity in drug availability for primary educated individuals could require more support.
Bioaccessibility of Antioxidants in Blackcurrant Juice After Treatment Using Supercritical Carbon Dioxide
Authors: Trych Urszula , Buniowska Magdalena , Skąpska Sylwia , Kapusta Ireneusz , Marszałek Krystian
Published: December 2021

Blackcurrant juice (Ribes nigrum L.) was subjected to supercritical carbon dioxide (SCCD) at 10, 30 and 60 MPa for 10 min at 45°C as well as thermally treated at 45°C and 85°C for 10 min to determine the stability, antioxidant capacity (AC) and bioaccessibility (BAc) of vitamin C, total anthocyanins and their individual monomers. An in vitro gastrointestinal digestion model completed with dialysis was used to assess BAc. The use of SCCD at each of the pressures applied improved the stability of vitamin C, total anthocyanins, and AC before in vitro digestion. As a result of digestion, L-ascorbic acid was oxidized to L-dehydroascorbic acid, and finally, the total content of vitamin C, anthocyanins, and AC decreased. SCCD did not significantly improve the BAc of vitamin C and total anthocyanins. The highest BAc of vitamin C was noted in fresh juice (FJ) (40%) and after mild heat treatment at 45°C (T45) (46%). The highest BAc of total anthocyanins was also noted in the FJ (4.4%). The positive effect of the application of SCCD on the BAc of the delphinidin-3-O-glycosides was observed compared to T45 and thermal pasteurization at 85°C (T85). Moreover, cyanidins were generally more bioaccessible than delphinidins in all samples. AC after digestion was higher in SCCD samples compared to thermally treated measured using ABTS+• and DPPH• assays, whereas in dialysate similar trends were observed only for AC measured using the ABTS+• assay. This phenomenon was justified by the formation of individual metabolites detected by UPLC-PDA-MS / MS in the model experiment with delphinidin-3-O-rutinoside. The protocatechuic acid which is well known as a strong antioxidant was detected in the model experiment after digestion. Further research is needed to better understand the metabolic pathway of anthocyanins and the possible uses of SCCD to improve the health properties of fruit products.
The SAMME.C2 Algorithm for Severely Imbalanced Multi-class Classification
Authors: So Banghee , Valdez Emiliano A.
Published: December 2021

Classification predictive modeling involves the accurate assignment of observations in a dataset to target classes or categories. There is an increasing growth of real-world classification problems with severely imbalanced class distributions. In this case, minority classes have much fewer observations to learn from than those from majority classes. Despite this sparsity, a minority class is often considered the more interesting class yet developing a scientific learning algorithm suitable for the observations presents countless challenges. In this article, we suggest a novel multi-class classification algorithm specialized to handle severely imbalanced classes based on the method we refer to as SAMME.C2. It blends the flexible mechanics of the boosting techniques from SAMME algorithm, a multi-class classifier, and Ada.C2 algorithm, a cost-sensitive binary classifier designed to address highly class imbalances. Not only do we provide the resulting algorithm but we also establish scientific and statistical formulation of our proposed SAMME.C2 algorithm. Through numerical experiments examining various degrees of classifier difficulty, we demonstrate consistent superior performance of our proposed model.
Sums and Partial Sums of Horadam Sequences: The Sum Formulas of $\sum_{k=0}^{n}x^{k}W_{k}$ and $ \sum_{k=n}^{n+m}x^{k}W_{k}$ via Generating Functions
Authors: Soykan Yüksel
Published: December 2021

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.
On the Health Care Luxury Good Hypothesis
Authors: Ebadi Esmaeil
Published: December 2021

A wide range of research has been developed in the empirical literature regarding income and price elasticities of health care expenditure (HCE). The results are mixed, as researchers employ different methodologies and data sources. The benefits of the panel data method, such as greater data variation, less collinearity, and more degrees of freedom, made it attractive among economists. However, the pooled mean group (PMG) method provides robust estimates compared to conventional methods, such as the mean group estimator and dynamic fixed-effects estimator. As such, this paper applies the PMG method to scrutinize the effect of income and price on U.S. health care consumption using a panel of 46 states. The income and price elasticities were found to be 0.85 and -0.48, respectively, which partially describes the recessionary decline in health care consumption following the Great Recession. In addition, the model reveals that the short-run income elasticity is smaller than the long-run. This confirms that U.S. health care consumption follows the permanent income hypothesis. Consequently, the short-run efficacy of public policies targeting HCE remains limited. The results of this paper suggest reconsidering and adjusting health care policies during a recession so as to avoid probable long-run adverse effects on HCE.
Reaction Center of Rhodobacter Sphaeroides, a Photoactive Protein for pH Sensing: A Theoretical Investigation of Charge Transport Properties
Authors: Alfinito Eleonora , Reggiani Lino
Published: December 2021

Featured Application: Bio-electronic devices take advantages of some specific duties of biological matter. The specific ability of some proteins to use sunlight is considered for the realization of photo-electronic devices . Here the focus is on the role of the pH, whose variations seem to affect the protein conductance
Determining the Factors Predicting the Response to Anti-HER2 Therapy in HER2-Positive Breast Cancer Patients
Authors: You Ji Young , Park Kyong Hwa , Lee Eunsook , Kwon Youngmee , Kim Kyungtae , Nam Seungyoon , Kim Donghee , Bae Jeoung Won
Published: December 2021

Background: We aimed to identify overexpressed genes or related pathways associated with good responses to anti-HER2 therapy and to suggest a model for predicting drug response in neoadjuvant therapy with trastuzumab in HER2-positive breast cancer patients. Methods: We recruited 64 women with breast cancer and categorized them into three groups according to anti-HER2 therapy response. RNA from twenty core needle biopsy paraffin-embedded tissues and four cultured cell was extracted, reverse transcribed, and subjected to microarray. The obtained data were analyzed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and database for annotation, visualization, and integrated discovery. Results: In total, 6,656 genes differentially expressed between trastuzumab-susceptible and trastuzumab-resistant cell lines (3,224 upregulated and 3,432 downregulated). Expression changes in 34 genes in several pathways were found to be related to the response to trastuzumab-containing treatment, interfering with adhesion to other cells or tissues (focal adhesion) and regulating extracellular matrix interactions and phagosome action. Thus, decreased tumor invasiveness and enhanced drug effects might be the mechanisms explaining the better drug response in complete response group. Conclusions: This multigene assay-based study provides insights into breast cancer signal transduction and the possible prediction of treatment response to targeted therapies such as trastuzumab.
Assessing the Potential of Multi-spectral and Multi-temporal Satellite Images for Classification and Mapping of Plant Communities in a Temperate Region
Authors: Sharma Ram C. , Hirayama Hidetake , Yasuda Masatsugu , Asai Miki , Hara Keitarou
Published: December 2021

Classification and mapping of plant communities is an essential step for conservation and management of ecosystems and biodiversity. We adopt the Genus-Physiognomy-Ecosystem (GPE) system developed in previous study for satellite-based classification of plant communities. This paper assesses the potential of multi-spectral and multi-temporal images collected by Sentinel-2 satellites. This research was conducted in five representative study sites in a temperate region. It consists of 44 types of plant communities including a few land cover types as well. The plant community types were enumerated in the study sites and ground truth data were prepared with reference to extant vegetation surveys, visual interpretation of high-resolution images, and onsite field observations. We acquired all Sentinel-2 Level-1C product images available for the study sites between 2017-2019 and generated monthly median composite images consisting of ten spectral and twelve spectral-indices. Gradient Boosting Decision Trees (GBDT) classifier was employed as an efficient and distributed gradient boosting technique for the supervised classification of big datasets involved in the research. The cross-validation accuracy in terms of kappa coefficient varied from 87% in Oze site with 41 land cover and plant community types to 95% in Hakkoda site with 19 land cover and plant community types; with average performance of 91% across all sites. In addition, the resulting maps demonstrated a clear distribution of plant community types involved in all sites, highlighting the potential of Sentinel-2 multi-spectral and multi-temporal images with GPE classification system for operational and broad-scale mapping of land cover and plant communities.
Dietary Omega-3 Polyunsaturated Fatty-Acid Supplementation Upregulates Protective Cellular Pathways in Patients with Type 2 Diabetes that reduces Painful Diabetic Neuropathy
Authors: Durán Alfonso Manuel , Beeson W. Lawrence , Firek Anthony , Cordero-MacIntyre Zaida , De León Marino
Published: December 2021

Background: Omega-3 polyunsaturated fatty acids (PUFAs) are increasingly reported to improve chronic neuroinflammatory diseases in peripheral and central nervous systems. Specifically, docosahexaenoic acid (DHA) protects nerve cells from noxious stimuli in vitro and in vivo. Recent reports link PUFA supplementation to improving painful diabetic neuropathy (pDN) symptoms. However, the molecular mechanism behind omega-3 PUFAs ameliorating pDN symptoms is lacking. Therefore, we sought to determine the distinct cellular pathways that omega-3 PUFAs dietary supplementation promotes in reducing painful neuropathy in type 2 diabetes mellitus (DM2) patients. Methods: Forty volunteers diagnosed with type 2 diabetes were enrolled in the "En Balance-PLUS" diabetes education study. The volunteers participated in weekly lifestyle/nutrition education and daily supplementation with 1,000 mg DHA and 200 mg eicosapentaenoic acid. The Short-Form McGill Pain Questionnaire validated clinical determination of baseline and post-intervention pain complaints. Laboratory and untargeted metabolomics analyses were conducted using blood plasma collected at baseline and after three months of participation in the dietary regimen. The metabolomics data was analyzed using random forest, hierarchical cluster, ingenuity pathway analysis, and metabolic pathway mapping. Results: We found that metabolites involved in oxidative stress and glutathione production shifted significantly to a more anti-inflammatory state post supplementation. Example of these metabolites include cystathionine (+90%), S-methylmethionine (+9%), glycine cysteine-glutathione disulfide (+157%) cysteinylglycine (+19%), glutamate (-11%), glycine (+11%) and arginine (+13.4%). In addition, the levels of phospholipids associated with improved membrane fluidity such as linoleoyl-docosahexaenoyl-glycerol (18:2/22:6) (+253 %) were significantly increased. Ingenuity pathway analysis suggested several key bio functions associated with omega-3 PUFA supplementation such as formation of reactive oxygen species (p = 4.38 × 10-4, z-score = -1.96), peroxidation of lipids (p = 2.24 × 10-5, z-score = -1.944), Ca2+ transport (p = 1.55 × 10-4, z-score = -1.969), excitation of neurons (p = 1.07 ×10-4, z-score = -1.091), and concentration of glutathione (p = 3.06 × 10-4, z-score = 1.974). Conclusion: The reduction of pro-inflammatory and oxidative stress pathways following omega-3 PUFAS supplementation is consistent with using omega-3 PUFAs as a complementary dietary strategy as part of the overall treatment of painful diabetic neuropathy.
DYNAMICS OF AN ELECTRON BEAM FORMED BY MAGNETRON GUN WITH THE SECONDARY EMISSION CATHODE IN THE DECLINING MAGNETIC FIELD OF SOLENOID: EXPERIMENT AND SIMULATION
Authors: Mazmanishvili Oleksandr , Reshetnyak Nikolay , Sydorenko Ganna
Published: December 2021

The article presents the results of research and calculations on the formation of a radial electron beam by a magnetron gun with a secondary emission cathode in the electron energy range 35...65 keV and measuring its parameters during transportation in the total decreasing magnetic field of thesolenoid and the stray field of permanent magnets. The beam was transported in a system consisting of copper rings with an inner diameter of 66 mm,located at a distance of 85 mm from the exit of the magnetron gun. The dependence of the beam current on the amplitude and gradient of the fielddecay has been studied. The studies carried out have shown the possibility of stable formation of a radial electron beam with an energy of tens of keVin the decreasing magnetic field of the solenoid. By optimizing the distribution of the magnetic field (created by the solenoid and ring magnets) and itsdecay gradient, it is possible to achieve an increase in the incident of electrons on one ring (up to ~72% of the beam current). On the basis of themathematical model of the movement of the electron flow, a software tool has been synthesized that makes it possible to obtain and interpret thecharacteristics of the resulting flows. The obtained numerical dependences are in satisfactory agreement with the experimental results for a magneticfield with a large decay gradient. Various configurations of the magnetic field are considered. Solutions to the direct problem of modeling electrontrajectories for given initial conditions and parameters are obtained. Various configurations of the magnetic field are considered. It is shown that forthe selected initial conditions for the electron beam and the distributions of the longitudinal magnetic field along the axis of the gun and the transportchannel, the electron flux falls on a vertical section, the length of which is on the order of a millimeter. Thus, by changing the amplitude anddistribution of the magnetic field, it is possible to control the current in the radial direction along the length of the pipe, and, therefore, the place of theelectron irradiation.
COUNTERFACTUAL TEMPORAL MODEL OF CAUSAL RELATIONSHIPS FOR CONSTRUCTING EXPLANATIONS IN INTELLIGENT SYSTEMS
Authors: Chalyi Serhii , Leshchynskyi Volodymyr , Leshchynska Irina
Published: December 2021

The subject of the research is the processes of constructing explanations based on causal relationships between states or actions of an intellectualsystem. An explanation is knowledge about the sequence of causes and effects that determine the process and result of an intelligent informationsystem. The aim of the work is to develop a counterfactual temporal model of cause-and-effect relationships as part of an explanation of the process offunctioning of an intelligent system in order to ensure the identification of causal dependencies based on the analysis of the logs of the behavior ofsuch a system. To achieve the stated goals, the following tasks are solved: determination of the temporal properties of the counterfactual description ofcause-and-effect relationships between actions or states of an intelligent information system; development of a temporal model of causal connections,taking into account both the facts of occurrence of events in the intellectual system, and the possibility of occurrence of events that do not affect theformation of the current decision. Conclusions. The structuring of the temporal properties of causal links for pairs of events that occur sequentially intime or have intermediate events is performed. Such relationships are represented by alternative causal relationships using the temporal operators"Next" and "Future", which allows realizing a counterfactual approach to the representation of causality. A counterfactual temporal model of causalrelationships is proposed, which determines deterministic causal relationships for pairs of consecutive events and pairs of events between which thereare other events, which determines the transitivity property of such dependencies and, accordingly, creates conditions for describing the sequence ofcauses and effects as part of the explanation in intelligent system with a given degree of detail The model provides the ability to determine cause-andeffect relationships, between which there are intermediate events that do not affect the final result of the intelligent information system.
MATHEMATICAL MODEL OF ADAPTIVE CONTROL OF THE FUNCTIONING OF A TRAFFIC LIGHT AT THE CROSSROADS OF A URBAN TRANSPORTATION NETWORK
Authors: Gamayun Igor , Shashkov Serhii
Published: December 2021

The subject of the research is the process of modeling the functioning of a traffic light, providing adaptive control of vehicles at the intersectionsof the city transport network. In the process of functioning of urban transport networks, such phenomena as traffic jams occur, which lead tosignificant economic losses, environmental degradation, frustration of road users and other types of negative impacts. Traffic jams often occur at thenodes of the urban transport network, which are intersections - the places of intersection, abutment or branching of roads of the urban network of thesame level. One of the causes of congestion is the ineffective management of traffic flows at intersections, which is provided by such an element of theintersection as a traffic light. Within the framework of the existing transport network, traffic lights that implement adaptive control with the help ofappropriate local controllers, and more complex system controllers created on their basis, ensuring that the situation in the external environment istaken into account, which is represented by several interconnected intersections, is currently one of the most important directions for solving theproblem of traffic jams. The traffic light flow control function is implemented using a microprocessor controller, which, according to a given algorithm, switches the traffic light colors corresponding to the phases of allowing and prohibiting the movement of the vehicle in the directions of theintersection roads.The article proposes a mathematical model for building an algorithm for the functioning of a microprocessor traffic light controller, whichprovides a prompt and adequate display of situations at intersections. The main features of the model include responsiveness to changes in situations atan intersection by changing the duration of the permissive phase of movement in each cycle of traffic light operation in proportion to the length of thequeue of vehicles in the corresponding direction of travel; adequate display of the external environment by several expressions of Poisson’s law,differing in different values of the parameter, each of which corresponds to a certain daily interval of traffic light functioning; the dynamics of changesin the traffic situation due to a decrease in the number of vehicles in the queue due to the passage of the intersection by vehicles during the green phaseof the traffic light is determined on the basis of expressions that determine the movement of bodies with uniformly accelerated and uniform movement,as well as on the basis of the differential equation of the dynamics of movement of vehicles in one row taking into account the delay caused by thereaction of drivers.
TOPIC SEGMENTATION METHODS COMPARISON ON COMPUTER SCIENCE TEXTS
Authors: Sokol Volodymyr , Krykun Vitalii , Bilova Mariia , Perepelytsya Ivan , Pustovarov Volodymyr , Pustovarov Volodymyr
Published: December 2021

The demand for the creation of information systems that simplifies and accelerates work has greatly increased in the context of the rapidinformatization of society and all its branches. It provokes the emergence of more and more companies involved in the development of softwareproducts and information systems in general. In order to ensure the systematization, processing and use of this knowledge, knowledge managementsystems are used. One of the main tasks of IT companies is continuous training of personnel. This requires export of the content from the company'sknowledge management system to the learning management system. The main goal of the research is to choose an algorithm that allows solving theproblem of marking up the text of articles close to those used in knowledge management systems of IT companies. To achieve this goal, it is necessaryto compare various topic segmentation methods on a dataset with a computer science texts. Inspec is one such dataset used for keyword extraction andin this research it has been adapted to the structure of the datasets used for the topic segmentation problem. The TextTiling and TextSeg methods wereused for comparison on some well-known data science metrics and specific metrics that relate to the topic segmentation problem. A new generalizedmetric was also introduced to compare the results for the topic segmentation problem. All software implementations of the algorithms were written inPython programming language and represent a set of interrelated functions. Results were obtained showing the advantages of the Text Seg method incomparison with TextTiling when compared using classical data science metrics and special metrics developed for the topic segmentation task. Fromall the metrics, including the introduced one it can be concluded that the TextSeg algorithm performs better than the TextTiling algorithm on theadapted Inspec test data set.
USING OF MULTILAYER NEURAL NETWORKS FOR THE SOLVING SYSTEMS OF DIFFERENTIAL EQUATIONS
Authors: Marchenko Natalia , Sydorenko Ganna , Rudenko Roman
Published: December 2021

The article considers the study of methods for numerical solution of systems of differential equations using neural networks. To achieve this goal, thefollowing interdependent tasks were solved: an overview of industries that need to solve systems of differential equations, as well as implemented amethod of solving systems of differential equations using neural networks. It is shown that different types of systems of differential equations can besolved by a single method, which requires only the problem of loss function for optimization, which is directly created from differential equations anddoes not require solving equations for the highest derivative. The solution of differential equations’ system using a multilayer neural networks is thefunctions given in analytical form, which can be differentiated or integrated analytically. In the course of this work, an improved form of constructionof a test solution of systems of differential equations was found, which satisfies the initial conditions for construction, but has less impact on thesolution error at a distance from the initial conditions compared to the form of such solution. The way has also been found to modify the calculation ofthe loss function for cases when the solution process stops at the local minimum, which will be caused by the high dependence of the subsequentvalues of the functions on the accuracy of finding the previous values. Among the results, it can be noted that the solution of differential equations’system using artificial neural networks may be more accurate than classical numerical methods for solving differential equations, but usually takesmuch longer to achieve similar results on small problems. The main advantage of using neural networks to solve differential equations` system is thatthe solution is in analytical form and can be found not only for individual values of parameters of equations, but also for all values of parameters in alimited range of values.