bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis and Implementation of Energy Efficiency Measures in Multi-Apartment Buildings in Latvia
Authors: Cimbale A. , Amolina I. , Geipele I. , Zeltins N.
Published: September 2023

A simplified life cycle of any product or service consists of three main stages – manufacturing, including obtaining, transformation, combination of raw materials; transportation, as well as packaging; consumption from purchase up to actual use. Energy is not an exception, it is also an item offered by the market in different forms, and everyone in need of it has the right to buy it in case the price is acceptable. Heat power is one of the energy types required by households and important for proper maintenance. Without heating, as well as electricity, modern houses cannot function appropriately, are not attractive to their inhabitants, do not provide comfort and safety. Nevertheless, heat power often is considered as a by-product of electricity production, nowadays a swift price increase for both types of energy is inevitable.

Energy efficiency is the level of appropriate usage of energy resources, which can be determined as the relation between final product type, quality, quantity and consumption of energy necessary to create this product [1].

Indirectly energy efficiency impacts health of the society in general and each individual in particular. Renovated energy efficient apartment buildings have a better ventilation system and microclimate. The problem of moisture and mold is at least partly solved, comfort is reached by consuming less energy, especially, heat power [2].

The aim of the paper is to research the impact of different energy efficiency increasing measures on heat consumption in multi-apartment buildings.
Development of a Conceptual Snow Sub-Model: Application in Meteorological Stations, Slovakia
Authors: Kandera Miroslav , Výleta Roman
Published: September 2023

A semi-distributed rainfall-runoff Approximate Redistributive Balance (ARB) model is currently in development as a tool for the assessment and analysis of the water management balance at the level of micro-basins on the territory of Slovakia. For the winter season, it is necessary to supplement the model with a sub-model for calculating the snow water equivalent (SWE) with a comparatively low amount of the input data necessary. Since SWE models generally operate in a daily time step, a new sub-model was developed and tested in monthly and weekly time steps in 30 meteorological stations in the north of Slovakia. When compared in a weekly time step with the snow sub-model of the HBV rainfall-runoff model and when the impact of switching from a monthly to weekly time step on the quality of the runoff simulation was evaluated, the results showed that the snow sub-model does react to sudden snowmelt better when compared to the modified version of the HBV snow sub-model used. Using a weekly time step for the snow sub-model in a monthly ARB model runoff simulation showed an increase of accuracy (NSE change from 0.89 to 0.92) in one case, while maintaining the same level of accuracy in the second one.
In Vitro Coinoculation Between Actinobacteria and Diazotrophic Nodulating Bacteria from the Semiarid
Authors: De Sousa Juliani Barbosa , Bandeira Leonardo Lima , Dos Santos Franciandro Dantas , Silva Valéria Maria Araújo , Cavalcante Fernando Gouveia , Martins Suzana Cláudia Silveira , Martins Claudia Miranda
Published: September 2023

Purpose: To evaluate the potential of actinobacterial strains from the Brazilian semiarid to establish facilitation relationships with native rhizobia from the same region.
 
Theoretical framework: The study is based on the ecological and biotechnological importance of soil actinobacteria, producers of biosurfactants and enzymes, and of nitrogen-fixing rhizobia in legumes.
 
Method: 50 strains of actinobacteria were isolated from soils from Ceará with different levels of anthropization and 19 strains of rhizobia using cowpea. The morphological, cultural and micromorphological characterization of the strains was performed, as well as the evaluation of their enzymatic profiles. In vitro facilitation tests were conducted between cellulolytic actinobacteria and non-cellulolytic rhizobia.
 
Results: The soil areas presented a similar composition of actinobacteria, but strains from the anthropized area showed higher enzymatic activity. Two Streptomyces strains promoted the growth of non-cellulolytic rhizobia in vitro, indicating potential application as bioinoculants in microbial consortia.
 
Conclusions: The study contributes to the knowledge of the interaction between beneficial microbial groups from the semiarid region and their possible biotechnological use in agriculture.
 
Originality/value: Works on coinoculation between actinobacteria and rhizobia from semiarid soils are scarce.
Unequal Territories and Water Access Policies in the Brazilian Northeast
Authors: Santana Mario Rubem Costa , Rocha Altemar Amaral , Santos Mateus Costa , De Alcantara Fernanda Viana , Lisboa Acssuel de Sousa , Oliveira Crislane da Silva
Published: September 2023

Objective: The present work aims to analyze the territorial inequalities of public policies for access to water through the territorial approach.
 
Theoretical framework: This study is conducted based on theoretical reflections about geographic knowledge about space and territory, the latter as primordial in the analysis of power relations in the management, access and use of water. The theoretical framework uses the contributions of some of the authors who discuss the territory, among them: Haesbaert (2004), Folcault (1989) Saquet (2010) and Araújo (2000).
 
Method: It is based on the use of data collection with mapping and theoretical discussion. It seeks to analyze the inequalities and diversities of territorialities in the territory(ies), inquiries are made about territorial development through public policies mediated with the contributions of geographic science, data collection on the construction of cisterns is used in the northeast of Brazil, as well as the mapping of areas most affected by droughts in the northeast.
 
Results and conclusion: As a result, the theoretical analysis of approaches to territorial development and public policies allied to geographic knowledge permeates the production of space and the phenomena caused in rural areas.
 
Research implications: We understand that the territory is historically built by power relations, the territorial approach to development arises from the proposition of working on intra-regional inequalities with a view to generating social participation and, in parallel, governance of social subjects with power public.
 
Originality/value: This research has social, economic and scientific value due to the originality of the discussions presented.
COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS FOR SENTIMENT ANALYSIS OF TEXTS IN AZERBAIJANI AND ENGLISH
Authors:   Landau School,Baku, Azerbaijan, Rasul Mehdi
Published: September 2023

The prediction of sentiment of the text within different business spheres has been one of the challenging problems for a variety of linguistics. In this paper, the sentiment analysis of the texts is carried out using different machine learning (ML) techniques. Various feature extraction techniques and supervised learning algorithms are employed on the movie review dataset sourced from the Internet Movie Database and translated into Azerbaijani. Specifically, the techniques utilized encompass Support Vector Machine, Logistic Regression, Decision Trees, Random Forest, AdaBoost, XGBoost, and Naïve Bayes. The proposed models depict the importance of language corpus that Azerbaijani language lacks by comparing the results obtained from both Azerbaijani and English versions of the dataset.
SOFTWARE DEFECT PREDICTION USING THE MACHINE LEARNING METHODS
Authors:   Institute of Information Technology, Baku, Azerbaijan, Bayramova Tamilla
Published: September 2023

Reliability of software systems is one of the main indicators of quality. Defects occurring when developing software systems have a direct effect on reliability. Precise prediction of defects in software systems helps software engineers to ensure the reliability of software systems and to properly allocate resources for the trial process. The development of an ensemble method by combining several classification methods occupies one of the main places in research conducted in the field of error prediction in software modules. This paper proposes a method based on the application of ensemble training for defect detection. Here, a database obtained from PROMISE and GITHUB software engineering registry is used to detect defects. Experiments are conducted using Weka software. The prediction efficiency is evaluated based on F-measure and ROC-area. As a result of experiments, the defect detection accuracy of the proposed method is proven to be higher than that of individual machine learning methods.
COMPARATIVE ANALYSIS OF MODELS FOR SOLAR STATION OUTPUT PREDICTION
Authors:   Azerbaijan Technical University,Baku, Azerbaijan, Najafli Javad
Published: September 2023

This research paper explores the prediction of solar energy radiation using various machine learning methods and neural networks. The results are presented based on the analysis of four different datasets obtained from solar stations. The study begins with an overview of solar energy in the context of contemporary challenges in the fields of energy and environmental sustainability, and reviews previous research related to the application of artificial intelligence in solar energy. The main contribution of the work lies in the analysis and comparison of diverse machine learning models and neural networks for predicting solar energy radiation. The results are compared considering accuracy metrics (RMSE - Root Mean Squared Error, MAE - Mean Absolute Error, MRE - Mean Relative Error) and execution times for each model. Each model is evaluated on four datasets with different characteristics.
USING MACHINE LEARNING METHODS FOR INDUSTRIAL CONTROL SYSTEMS INTRUSION DETECTION
Authors:   Institute of Information Technology, Baku, Azerbaijan, Shikhaliyev Ramiz
Published: September 2023

In recent decades, information technology has been integrated into industrial control systems (ICS). At the same time, there was a connection of the ICS to the Internet and a transition to cloud computing. Consequently, new vulnerabilities and threats to sophisticated cyberattacks have emerged that create significant risks for the cybersecurity of ICS, and the old security model based on the isolation of ICS is no longer able to ensure their cybersecurity. This situation makes it very important to intellectualize the cybersecurity of ICS, for which machine learning (ML) methods are used. The use of ML methods will make it possible to detect cybersecurity problems of ICS at an early stage, as well as eliminate their consequences without real damage. This paper discusses the issues of ICS intrusion detection based on ML methods. The work can help in the choice of ML methods for solving anomaly detection problems of ICS.
6G TECHNOLOGY: PERSPECTIVES, PROBLEMS AND SOLUTIONS
Authors:   Institute of Information Technology, Baku, Azerbaijan, Aghashov Javid , Aghashov Tabriz ,   Institute of Information Technology, Baku, Azerbaijan
Published: September 2023

The standardization procedure of the fifth generation communication has already been completed and global spread has launched. To maintain the competitive advantage of wireless communication, researchers conceptualize next-generation (6th generation, 6G) wireless communication systems aimed at founding the stratification of communication needs of the 2030s. This article highlights the most promising research areas in the recent literature on the overall trends of the 6G project to support this view. It discusses the development and analysis of 6G wireless communication technology, which is projected to be implemented in the near future. Networks based on 6G wireless technology seem to be the most promising and developing field in the field of wireless technology. The article indicates the emergence and development of 6G to lead to a new wave of developments in the field of the Internet of Things (IoT). It touches upon the services applied during the implementation of the previous generation (5th generation, 5G) technologies and the emerging problems. It also reviews the benefits and challenges associated with the development of 6G wireless communication, which is designed to provide a better communication system in the future and to get many new perspectives.
La contención de los individuos
Authors: Martuccelli Danilo
Published: September 2023

El artículo analiza una de las grandes fuentes de producción del malestar subjetivo contemporáneo: los cambios advenidos en los procesos de contención de los individuos. Centrándose en el caso latinoamericano, pero en diálogo crítico con consideraciones generales establecidas desde las ciencias sociales mainstream, se exploran cuatro grandes modos de contención (moral, legal, social y fáctico), recordando, en cada caso, su realidad histórica y sus recientes inflexiones. Todo esto lleva a que los individuos se sientan y se conciban contenidos (o no, o poco, o intermitentemente) de otra manera, con otras intensidades y sanciones. Sin menoscabo de la pertinencia de otras interpretaciones, el análisis indisociablemente psicológico y sociológico, interno y externo, subjetivo y colectivo, de las distintas contenciones de los individuos, sus transformaciones y efectividades, invita a perfilar una cartografía distinta de las fuentes del sufrimiento contemporáneo.
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The article analyzes one of the great sources of production of contemporary subjective malaise: the changes that have occurred in the processes of containment of individuals. Focusing on the Latin American case, but in a critical dialogue with general considerations established from the mainstream social sciences, four major modes of contention are explored (moral, legal, social and factual), recalling in each case their historical reality and their recent changes. All this leads individuals to feel and conceive content (or not, or little, or intermittently) in another way, with other intensities and sanctions. Without undermining the relevance of other interpretations, the inextricably psychological and sociological, internal and external, subjective and collective analysis of the different modes of contention of individuals, their transformations and effectiveness, allows us to outline a different cartography of the sources of contemporary suffering.
Equality Does Not Make You Happy: Effects of Differentiated Leader-Member Exchange and Team-Member Exchange on Developer Satisfaction in Agile Development Teams
Authors: Venkatesh Viswanath , Thong James Y. L. , Spohrer Kai , Chan Frank K. Y. , Arora Ankur , Hoehle Hartmut , Venkatraman Srinivasan
Published: September 2023

Prior work on leadership in information systems development (ISD) teams has assumed that all developers are treated equally by their team leader and ignored the possibility that differentiated leader-member exchange (LMX) may be an important instrument for team leaders to influence self-organizing, agile ISD teams. We conducted a concurrent mixed methods inquiry to understand how LMX differentiation is associated with developer satisfaction in agile ISD teams and through which team processes agile ISD teams address LMX differentiation. We ran a multilevel, multistage survey of 1,894 software developers in 217 teams and an embedded case study of five ISD teams drawing on qualitative data from 40 interviews of developers and team leaders. Two focus groups (one with 10 developers and one with 10 team leaders) helped to substantiate the meta-inferences from the quantitative and qualitative studies. The results showed that LMX differentiation was positively associated with developer satisfaction, especially in teams with high-quality team-member exchange (TMX). We identify three team processes (i.e., collectivization of resources, visible appreciation of privileges, and freeing up leader capacities) that are enacted through agile ISD practices and allow ISD teams to leverage benefits from LMX differentiation for all their members.
Ambivalence Is Better than Indifference: A Behavioral and Neurophysiological Assessment of Ambivalence in Online Environments
Authors: Lakhiwal Akshat , Bala Hillol , Léger Pierre-Majorique
Published: September 2023

Information representations such as ratings and reviews play an important role in assisting users in making decisions in online environments. Prior information systems (IS) research has mostly focused on the role of extreme valence, i.e., the positivity/negativity of information, portrayed by such representations. Yet this bipolar approach discounts how the coexistence of positivity and negativity (i.e., ambivalence) or their absence (i.e., indifference) is formed and leads to distinct attentional processes and outcomes such as purchase decisions. We theorize how and why the valence of information projected through such representations may elicit mixed feelings and influence decision-making in online environments. We conducted four randomized controlled experiments, including an electroencephalography (EEG) study, to disentangle the influence of ambivalence and indifference on decision-making in an online shopping context. We found that ambivalence and indifference to online information distinctly influenced attention and purchase decisions relative to positivity and negativity. Our findings further suggest the inability of incumbent bipolar representations, such as the widely implemented star rating system, to capture the mixed feelings expressed in online content. We propose a bivariate intervention that overcomes the limitations of bipolar representations by not only discerning ambivalence from indifference but also amplifying purchase decisions for products with ambivalent information by at least 50%, compared to incumbent bipolar representations. Our findings advance ongoing research on the role of information valence in online environments and offer implications for practice.
Exploiting Expert Knowledge for Assigning Firms to Industries: A Novel Deep Learning Method
Authors: Zhao Xiaohang , Fang Xiao , He Jing , Huang Lihua
Published: September 2023

Industry assignment, which assigns firms to industries according to a predefined industry classification system (ICS), is fundamental to a large number of critical business practices, ranging from operations and strategic decision-making by firms to economic analyses by government agencies. Three types of expert knowledge are essential to effective industry assignment: definition-based knowledge (i.e., expert definitions of each industry), structure-based knowledge (i.e., structural relationships among industries as specified in an ICS), and assignment-based knowledge (i.e., prior firm-industry assignments performed by domain experts). Existing industry assignment methods utilize only assignment-based knowledge to learn a model that classifies unassigned firms to industries, overlooking definition-based and structure-based knowledge. Moreover, these methods only consider which industry a firm has been assigned to, ignoring the time-specificity of assignment-based knowledge, i.e., when the assignment occurs. To address the limitations of existing methods, we propose a novel deep learning-based method that not only seamlessly integrates the three types of knowledge for industry assignment but also takes the time-specificity of assignment-based knowledge into account. Methodologically, our method features two innovations: dynamic industry representation and hierarchical assignment. The former represents an industry as a sequence of time-specific vectors by integrating the three types of knowledge through our proposed temporal and spatial aggregation mechanisms. The latter takes industry and firm representations as inputs, computes the probability of assigning a firm to different industries, and assigns the firm to the industry with the highest probability. We conduct extensive evaluations with two widely used ICSs and demonstrate the superiority of our method over prevalent existing methods.
Motivating User-Generated Content: The Unintended Consequences of Incentive Thresholds
Authors: He Liuyi , Luo Jifeng , Tang Yisong , Wu Zhiyan , Zhang Han
Published: September 2023

While monetary rewards have been widely used by online platforms to motivate user-generated content (UGC) contributions, users may not always demonstrate the expected behaviors. Unintended consequences of reward policies, exemplified by unchanged or reduced UGC contributions, may occur. Through two natural experiments, this study investigates the implications of providing users with an incentive structure that rewards users’ continued contribution according to the volume of UGC. Using a unique data set on two completion-contingent incentive programs from a popular online aesthetic medicine platform, we examine user responses to reward thresholds. We found that after users reach a threshold to obtain a monetary reward, they are less likely to continue contributing UGC, suggesting a minimal-effort effect. Our findings indicate that social approval from peers helps to mitigate unintended user responses to monetary reward policies. We also observed that monetary rewards primarily improve the quality and website traffic of low- to moderate-quality contributions.
Reputation Spillover from Agencies on Online Platforms: Evidence from the Entertainment Industry
Authors: Kokkodis Marios , Adamopoulos Panagiotis , Ransbotham Sam
Published: September 2023

Digital markets have proliferated in recent years, overcoming many market inefficiencies by facilitating direct interactions between consumers and creators. Thanks to this disintermediation, consumers now have access to a vast number of alternatives, while creators can efficiently reach huge markets. However, the success of digital markets has created a concomitant challenge for creators: differentiation. In crowded markets, agencies (e.g., publishing companies in books, freelance agencies in online labor markets, independent labels in music) can differentiate creators by signaling product quality. But how do agencies’ reputations affect product success for creators? Can some agencies do more harm than good? To investigate these research questions, we theorize how variation in creator and agency reputation leads to asymmetric and heterogeneous effects, namely that (1) more reputable agencies have a stronger positive effect on less reputable creators than they have on more reputable creators, and (2) less reputable agencies hurt more reputable creators more than they hurt less reputable ones. Analyses of more than one million observations from two digital markets provide empirical support for these theory-driven arguments. The findings have design implications for markets and contribute to our understanding of how agencies, depending on creator reputation, can either benefit or hurt product success.
On the Differences Between View-Based and Purchase-Based Recommender Systems
Authors: Peng Jing , Liang Chen
Published: September 2023

E-commerce platforms often use collaborative filtering (CF) algorithms to recommend products to consumers. What recommendations consumers receive and how they respond to the recommendations largely depend on the design of CF algorithms. However, the extant empirical research on recommender systems has primarily focused on how the presence of recommendations affects product demand, without considering the underlying algorithm design. Leveraging a field experiment on a major e-commerce platform, we examine the differential impact of two widely used CF designs: view-also-view (VAV) and purchase-also-purchase (PAP). We found several striking differences between the impact of these two designs on individual products. First, VAV is about seven times more effective in generating additional product views than PAP but only about twice as effective in generating sales due to a lower conversion rate. Second, VAV is more effective in increasing views for more expensive products, whereas PAP is more effective in increasing the sales of cheaper products. Third, VAV is less effective in increasing the views but more effective in increasing the sales of products with higher purchase incidence rates (PIRs). Finally, when aggregated over all products with the same levels of price or PIRs, VAV dominates PAP in generating views and the difference is more striking for products with higher prices or lower PIRs. Interestingly, PAP is more effective than VAV in increasing the sales of products with low prices or moderate PIRs, though VAV generates more sales than PAP overall. Our findings suggest that platforms may benefit from employing different CF designs for different types of products.
Vasily Manchary as the epic ideal of Nikita Leglyarin, the protagonist of Nikolai Mordinov's novel "Springtime"
Authors: Egorova S. I. , Efremova E. I.
Published: September 2023

Vasily  Manchary  was  a  Sakha  legendary  ﬁgure,  who  fought  against  the  local  rich  and was known as a “noble robber”, narrator, and a performer of folk songs.  The article deals with the study of  his  inﬂuence  upon  the  personality  of  Nikita  Leglyarin,  the  main  character  in  the  novel  “Springtime” (“Vesennyaya Pora”) by Nikolai Mordinov. The image of Vasily Manchary, considered by people as their hero,  becomes  the  ideal  for  Nikita  Leglyarin  after  the  folk  legend.  Thanks  to  the  author’s  mastery,  the whole unity of the materials from ﬁction and reality has been reached and revealed. The motifs of the main character’s actions are convincingly shown in combination with the Manchary’s image.
ВЛИЯНИЕ ПОЛОЖЕНИЯ ЗАГОТОВКИ НА ПАЛЛЕТЕ ПРИ ЛАЗЕРНОМ РАСКРОЕ НА ФОРМИРОВАНИЕ ЗОНЫ ТЕРМИЧЕСКОГО ВЛИЯНИЯ
Authors: Ерисов Я.А. , Африкантов В.В. , Горшков Ю.С. , Разживин В.А.
Published: September 2023

В данной работе выполнены исследования свойств и структуры материала зоны термического влияния, возникающей при лазерном раскрое металла, в зависимости от расположения заготовки на паллете: над выступом и между выступами паллеты. Показаны существенные отличия свойств и структуры на этих участках. Даны рекомендации по расположению заготовки относительно выступов паллеты. Свойства материала в зоне реза над выступом паллеты и между выступами существенно отличаются. Значения микротвердости в зоне над выступами паллеты на краю примерно на 50 % меньше, чем в зоне между выступами. По мере движения вглубь образца разница уменьшается. Содержание магния почти в два раза ниже в зоне над выступами, чем между выступами. В поверхностных слоях заготовки в зоне над выступами размеры включений по величине больше, чем в глубине. Это вызвано дополнительным закаливанием металла заготовки находящегося между выступами, и более длительным контактом с ванной жидкого металла из-за затруднения его удаления при резке на выступе паллеты. Удаление дефектного слоя методом фрезерования на глубину 0,5 мм нивелирует разницу свойств металла в зоне над выступом паллеты, между выступами и в глубине.
Hsp40 Affinity Profiling Reveals Protein Destabilization Profiles Following Cellular Manganese and Vanadate Exposure
Authors: Quanrud Guy , Abernathy Macon , Lyu Ziqi , Ying Samantha , Genereux Joseph
Published: September 2023

Heavy metals such as arsenic, lead, and cadmium are well-characterized toxicants and heavily regulated in ground and surface waters. However, even metals that are essential nutrients can be hazardous at higher concentrations. These transition metals may be less aggressively regulated due to the perception that they do not pose health risks even in the ppm range. One such metal is manganese, which is highly abundant in many drinking water sources in the United States despite emerging evidence that these metals can pose a threat. Vanadium is more tightly regulated due to its phosphatase inhibition, but also is commonly present in drinking water at > 100 ppb. Herein, we evaluate the effects of 100 M (~5 ppm) manganese (II) and vanadium (V) exposure on cellular proteostasis, using HEK293T cells. We find that cellular manganese exposure destabilizes hundreds of proteins. These include NKRF, a repressor of NF-kB, explaining the known inflammation phenotype associated with manganese exposure. Vanadium, by contrast, stabilizes RNA-binding splicing factors, explaining its known perturbation of RNA splicing. These studies provide evidence that manganese and vanadium can strongly perturb cellular processes, and provide motivation for further study.
Efficient Method for Twist-Averaged Coupled Cluster Calculation of Gap Energy: Bulk Study of Stannic Oxide
Authors: Shaban Tameh Maliheh , Gladfelter Wayne L. , Goodpaster Jason D.
Published: September 2023

We study gap energy of the semiconducting oxide SnO2 through ab-initio calculations. DFT and coupled cluster calculations are presented and discussed. In this work, we emphasize that GGA+U does not improve the physics of the semicore d electrons in SnO2. We report an overestimation in the gap energy by finite-size scaling at the thermodynamic limit through equation-of-motion (EOM) CCSD calculations. To address one-body and many-body errors, we report a combination of the Kwee-Zhang-Krakauer (KZK) approach with twist averaging to explain twist averaged EOM-CCSD gap energy. In this approach, the correction to the gap energy originates from the difference between mean-field and many-body approximations and at the end the difference is added to the mean-filed gap of an infinite system to estimate the many-body gap in the thermodynamic limit. The efficiency of the twist averaging in reducing the finite-size errors is tested through different functionals.
Positron emission tomography in cardiological practice
Authors: Sergienko Vladimir B. , Ansheles Alexey A.
Published: September 2023

The utility of positron emission tomography in cardiology currently goes beyond the ischemic heart disease and covers an increasingly wider range of non-coronary pathology, which requires timely expert diagnostics, including chronic heart disease of any etiology, valvular and electrophysiology disorders, cardiooncology. Authors emphasize the importance of the development of positron emission tomography technologies in the Russian Federation. This includes the development and implementation of new radiopharmaceuticals for the diagnosis of pathological processes of the cardiovascular system, systemic and local inflammation, including atherosclerosis, impaired perfusion and myocardial metabolism, and also for solving specific diagnostic tasks in comorbid pathology.
Association between cardio-ankle vascular index and markers of thrombosis in hospitalized patients COVID-19
Authors: Podzolkov Valery I. , Bragina Anna E. , Tarzimanova Aida I. , Ogibenina Ekaterina S. , Shvedov Ilya I. , Ivannikov Alexander A. , Megeneishvili Nino К. , Sutulova Angelina V.
Published: September 2023

Aim. To evaluate the relationship between the cardio-ankle vascular index (CAVI) and the marker of procoagulant state D-dimer in hospitalized patients with coronavirus disease 2019 (COVID-19).
Materials and methods. This cross-sectional study involved adult patients admitted to the University hospital with clinically diagnosed or laboratory-confirmed COVID-19. We compared groups of patients with normal and elevated CAVI. Univariate and multivariate logistic regression analyses were performed to assess the association between risk factors and elevated D-dimer levels; odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated to determine the strength of association. A p0.05 was considered statistically significant.
Results. The study included 152 patients [64 (42.1%) men and 88 (57.9%) women], mean age 59.1012.74 years. 45 (29.6%) had elevated CAVI. Patients with elevated CAVI were older, had more comorbid diseases, a higher Charlson comorbidity index and D-dimer levels. Age, the comorbidity index, and CAVI above 9.5 were associated with elevated D-dimer levels in patients with COVID-19. In a multivariate logistic regression, CAVI above 9.5 was an independent predictor of increased D-dimer in patients with COVID-19 (OR 2.513, 95% CI 1.0506.012; p=0.038).
Conclusion. In this study, for the first time, the association between a vascular stiffness marker, elevated CAVI, and increased D-dimer levels in COVID-19 patients was shown. This relationship may be a consequence of endothelial dysfunction and can be used as an additional marker of coagulopathy developing as part of COVID-19.
Dr. Sergey P. Botkin's case sheet
Authors: Dvoretsky Leonid I.
Published: September 2023

The article presents and discusses Botkin's case sheet focused on his cardiac disease. Analysis of the clinical symptoms and course of the disease provides an opportunity from the standpoint of modern clinical cardiology to characterize the features of Botkin's disease course at all stages of its cardiological continuum and assess the diagnostic capabilities and managing approach to such patients. The comorbidity of ischemic heart disease and gallstone disease in the case of Dr. Sergey P. Botkin, a Russian general practitioner, pathologist, physiologist, and one of the founders of scientific medicine in Russia, is being discussed.
YOUTH UNEMPLOYMENT SYNDROME IN NIGERIA: A CASE FOR REVIEW AND POLITICAL INVOLVEMENT
Authors: Olajuwon Ahmed Owolabi
Published: September 2023

Nigeria's youth unemployment rate is at 54.4% in the last quarter of 2020 (National Bureau of Statistics, 2020) which thus gives us an obvious reality of the danger of ever-increasing youth unemployment flooding the landscape of Nigeria, while several governmental initiatives in time past have not been able to help in curbing youth unemployment challenges in Nigeria, this study adopt the systematic review analysis in assessing the capacity of apprenticeship and informal sector capacity in reducing youth unemployment in Nigeria. This study calls for apprenticeship modernization and informal sector support in reducing youth unemployment in Nigeria as both apprenticeship and informal sector were proven to be significant measures in reducing youth unemployment in Nigeria.
Proyecto de aula: una estrategia de educación ambiental para la sostenibilidad
Authors: Alcalá Narváez Mónica , Aricapa Palacio Fernando
Published: September 2023

La sostenibilidad requiere, en su formulación y accionar, un activo ejercicio de reconstrucción de imaginarios, capaz de incidir en el entorno, a través de la comprensión de las dinámicas socioambientales y sus elementos de autogestión comunitaria. La formación de profesionales en Ingeniería Ambiental, en la Fundación Universitaria Tecnológico Comfenalco - Colombia, se compromete en el desarrollo de acciones pedagógicas que conectan al estudiante, en un diálogo directo con las comunidades, en el entendido, de que solo es posible alcanzar la pertinencia de su futuro accionar, cuando se generan competencias para el diagnóstico y educación ambiental. A través de los proyectos de aula, estrategia pedagógica fundamenta en el ABP (aprendizaje basado en proyectos), los estudiantes aprenden técnicas para la estimulación de la participación de actores de un ecosistema objeto de estudio. En el presente artículo se exponen técnicas de abordaje comunitario, como herramientas metodológicas para el reconocimiento de saberes propios o cosmovisiones, generando competencias para el desarrollo de diagnósticos socioambientales. Finalmente, se presentan las razones que justifican una intervención académica contextual, las técnicas empleadas para la identificación de problemas ambientales; y sus aportes para la formulación de planes que tributen a la sostenibilidad.
Estado de arte y aplicación de técnicas de Aprendizaje Profundo desde imágenes reconstruidas a partir de nubes de puntos de sensores de Radar y Lidar
Authors: Avendaño Fernández Eduardo , Roa Martín Nancy Carolina , Montañez Sogamoso Óscar Javier
Published: September 2023

Este artículo presenta una revisión de estado de arte de las técnicas del aprendizaje de máquina para el reconocimiento de patrones, la definición de los algoritmos para la clasificación de objetos (personas) a partir de imágenes construidas desde nubes de puntos adquiridas por sensores de Radar y Lidar, y resultados preliminares de aplicación en escenas reconstruidas a partir de nubes de puntos. En el primer hito del proyecto CLARIFIER (frequenCy-agiLe rAdar-lidaR chIp For surveIllancE moving platfoRms), se ha estudiado e implementado un filtro de Kalman Extendido para fusión de datos de sensores de Radar y LiDAR, cuyo aporte fue la inclusión de la velocidad angular en el modelo cinemático de un drone. En el segundo hito, se ha revisado estado de arte para identificar enfoque (segmentación semántica) y algoritmos que permitan detectar personas en imágenes reconstruidas de escenarios o zonas con requerimientos de supervisión y monitoreo. Como resultado de aplicación preliminar, se ha construido un conjunto de datos de escenas que incluye la clase “personas” y se evaluaron los algoritmos U-Net y Mask R-CNN que aplicas técnicas de segmentación semántica. Dado que la resolución del sensor en particular de Lidar, es mayor a la del radar, así como la diferencia en rangos que cada uno alcanza, se genera un compromiso que requiere múltiples barridos de la escena desde diferentes ángulos y distancias y se requiere aumentar el conjunto de datos, para entrenar los algoritmos y mejorar el porcentaje de detecciones correctas. De acuerdo a las métricas que se han evaluado (pérdidas, exactitud, precisión, exhaustividad y F1 Score), la clasificación de la clase personas en el contexto de segmentación semántica alcanza un 89.91 % para Mask R-CNN, y del 90.53% para U-Net; y con la curva de operación característica del receptor (ROC) y el área bajo la curva (AUC) se obtiene un 90% y 92% en la detección de la clase personas, respectivamente. Este resultado valida la efectividad de estos modelos de redes neuronales convolucionales aplicada a imágenes obtenidas a partir de nubes de puntos.
Análisis de alternativas de potabilización para aguas subterráneas en el corregimiento de Arroyo Grande / Cartagena
Authors: Ávila Remberto , Mendoza Torres Jorge , Quiñones Bolaños Édgar
Published: September 2023

Las aguas subterráneas son una importante fuente de abastecimiento para comunidades rurales con limitaciones en el acceso a agua potable. En el presente estudio tiene por objetivo evaluar distintas alternativas de potabilización de las aguas subterráneas provenientes del acuífero Arroyo Grande (Cartagena de Indias, D, T.), basándose en el índice de riesgo de calidad de agua y la selección de tecnologías de tratamiento establecido en la resolución 0330 de 2017. Se optó por un diseño de investigación no experimental aplicado de forma transversal durante el año 2022. Se llevó a cabo una investigación de forma descriptiva para conocer las características fisicoquímicas del agua subterránea y se evaluaron en total tres alternativas de potabilización enfocadas en el tratamiento de pozos no aptos para el consumo. Se analizaron un total de veintisiete muestras completas de calidad de agua de pozos profundos y dos aljibes de tres estudios atemporales en el acuífero. Como resultado de la investigación, se optó por el punto de extracción con mejor índice de riesgo de calidad de agua. El pozo presenta altas concentraciones de hierro (6.14 mg/L), manganeso (0.91 mg/L), turbidez (155 NTU), color (22 UPC) y Coliformes totales (20 UFC/100 mL). Estos elementos son reducidos por el sistema propuesto que emplea la oxidación por aireación, la filtración en múltiples etapas y desinfección. Dicho sistema es capaz de abastecer hipotéticamente la demanda de seis millones quinientos mil litros de agua potable por día para las poblaciones de Arroyo Grande, Santa Catalina y Clemencia, proyectando una vida útil de sistemas de potabilización de agua de 25 años.
Formulación de política energética en campus universitarios - estudio de caso “Campus Barcelona Universidad de los Llanos”
Authors: Beltrán Gutierrez Ómar Yesid , Torres Mora Marco Aurelio
Published: September 2023

El presente trabajo se presenta como estudio de caso, en el cual se establece una revisión energética del campus Barcelona de la Universidad de los Llanos, como insumo para la construcción de la Política energética institucional, basado en criterios normativos y operacionales que fueron validados por la comunidad universitaria. Durante la construcción de esta política, se generaron espacios de construcción participativa que aseguraron la inclusión de estrategias para la mitigación de los impactos ambientales, la diversificación de la matriz energética mediante el uso de fuentes renovables y además de propender por el ahorro y el uso eficiente de la energía en el campus. Como soporte para el ejercicio se revisó experiencias similares de instituciones de educación superior, aplicación de herramientas de recolección de información tipo entrevistas y encuestas con los grupos de interés principales de la institución. Se ponderaron los objetivos y ejes estratégicos para finalmente validarlos.
Comportamiento mecánico de suelos reforzados con un sistema de confinamiento celular de neumáticos en desuso para el mejoramiento estructural de subrasantes viales
Authors: Hernández Arango Mario Santiago
Published: September 2023

El crecimiento y expansión de la población ha requerido la construcción de infraestructura lineal sobre suelos de características deficientes. Por otro lado, la disposición de neumáticos en desuso implica centros de acopio donde la acumulación de gases aumenta su riesgo de colapso y el almacenamiento de agua, dentro de cada elemento, genera vectores infecciosos perjudiciales para la salud. El refuerzo con sistemas de confinamiento celular de neumáticos en desuso (SND) se presenta como una buena alternativa para el mejoramiento de suelos de bajas características mecánicas y geotécnicas en la construcción de infraestructura. Adicionalmente, es una solución efectiva para la disposición y reactivación del ciclo de vida de estos residuos, que representan un problema de salud pública a nivel mundial. La implementación de procesos sostenibles en el mejoramiento de suelos, las deficiencias en la gestión de la infraestructura, los beneficios mecánicos, ambientales y económicos de los sistemas celulares y la reutilización de los neumáticos en desuso mediante procesos de transformación de bajo costo fundamentaron la presente investigación. Se propone un SND a partir de la reutilización de la huella de rodadura del neumático, donde la transferencia de la carga se genera por la fricción entre los elementos, sin requerir sistemas adicionales de fijación. Por ello, se está desarrollando la evaluación analítica y experimental del SND para el mejoramiento de subrasantes viales, presentándose el modelo físico y matemático preliminar y la construcción del experimento de placa a escala real que será evaluado en condiciones dinámicas de carga. El avance actual de la investigación ha permitido establecer que el comportamiento mecánico del sistema depende de la magnitud de la carga vertical, del efecto membrana inducido por el arreglo de celdas de neumáticos, de la interfaz de fricción entre los elementos, del empuje pasivo del suelo sobre la celda, de la capacidad de soporte del suelo de apoyo y de las características físicas y geométricas de la celda. Igualmente, se determinó las condiciones del ciclo de carga y de la instrumentación geotécnica requerida para evaluar experimentalmente el comportamiento de los esfuerzos inducidos y las leyes de deformación del SND, con el objetivo de establecer parámetros mecánicos de mejoramiento entre un suelo reforzado y un suelo sin confinamiento.
Kenito, el robot inteligente autónomo para intervención en el manejo del dolor oncológico pediátrico
Authors: Romero Ávarez Fran , Castro Osorio Rubby , Moreno Munévar Gustavo Alejandro , Muñoz Peñuela Juan Sebastián , Domínguez Páramo Diana Katherine , Gaitán Porras Paula Gabriela , Gaitán Pinto Leidy Natalia
Published: September 2023

El cáncer en los niños causa diferentes síntomas físicos, estos pueden ser originados propiamente por la enfermedad o por los efectos del tratamiento. Dentro de estos síntomas se destacan: el vómito, las náuseas, pérdida de peso, dolor o fatiga, los cuales tienen repercusiones también a nivel psicológico. En pacientes pediátricos oncológicos el dolor es el síntoma más importante y frecuente para el niño, la familia y el equipo de salud, de modo que este ha de ser debidamente identificado, evaluado y tratado correctamente. Su aparición se hace constante durante la mayor parte de la enfermedad y del tratamiento, lo cual tiene implicaciones en el desarrollo físico, psíquico y social del paciente. La población pediátrica presenta unas características fisiológicas y psicológicas diferentes a la de los adultos; si a esto se le suma un proceso oncológico en el cual los pacientes son sometidos a numerosas experiencias dolorosas durante su diagnóstico y tratamiento, se hace de vital importancia un adecuado manejo del dolor. En el contexto sanitario, las Tecnologías de la Información y las Comunicaciones - TIC, son mayormente utilizadas para el tratamiento de diversos problemas de salud en menores de 18 años y un ejemplo son los problemas de dolor. Se evidencian las múltiples posibilidades y ventajas de utilizar tecnologías 4.0 tales como la Robótica, la Inteligencia Artificial, el Procesamiento de Lenguaje Natural y la Visión por Computador en los procesos de evaluación y tratamiento del dolor oncológico en pacientes pediátricos. El objetivo no es sustituir al profesional de la psicología, como sí entregarle un instrumento que contribuya efectivamente al cumplimiento de su labor y que pueda ser incluso utilizado por otros profesionales de la salud a cargo de estos casos. Con el proyecto Kenito - Fase 3 se espera obtener evidencia técnica y empírica del adecuado funcionamiento de la terapia cognitiva-conductual con técnicas de relajación e imaginería a través de un robot inteligente autónomo. El artefacto está siendo desarrollado por cuatro semilleros de investigación en las áreas de Psicología, Ingeniería Electrónica, Ingeniería de Sistemas y Diseño Industrial. Este proyecto se perfila como una experiencia exitosa de Transformación Digital y uso de tecnologías 4.0 en el ámbito de la psicología oncológica pediátrica.