bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of User-Generated Content in Industry 4.0
Authors: Rani Anshu , Sharma Ruchika , S. Pavithra , Singh Raghvendra Kumar
Published: January 2023

User-generated content (UGC) has grown in popularity in recent times. The researchers have examined the significance of UGC on consumer behaviour in the era of Industry 4.0. Therefore, measuring UGC in eWOM communication will allow stakeholders to evaluate their effectiveness on the internet and amplify the digital process needed to perform modern marketing. A comprehensive literature review has been conducted to piece together the disparate pieces of knowledge to comprehend the entire conceptual framework of UGC. Several research papers have been classified into seven categories, each of which could elaborate on the concepts of UGC, eWOM, UGC/eWOM effect, factors of source credibility, factors of content credibility, receiver's behaviour, and platform credibility in order to conceptualize the concept under consideration. The goal is to connect ideas available in the literature and offer a comprehensive picture of UGC by focusing on the future research perspective. UGC and eWOM will let firms strategize their resources and effort.
Sustainable Big Data Analytics Process Pipeline Using Apache Ecosystem
Authors: Cheng Jane , Zhao Peng
Published: January 2023

This article provides a comprehensive understanding of the cutting-edge big data workflow technologies that have been widely applied in industrial applications, covering a broad range of the most current big data processing methods and tools, including Hadoop, Hive, MapReduce, Sqoop, Hue, Spark, Cloudera, Airflow, and GitLab. An industrial data workflow pipeline is proposed and investigated in terms of the system architecture, which is designed to meet the needs of data-driven industrial big data analytics applications concentrated on large-scale data processing. It differs from traditional data pipelines and workflows in its ability of ETL and analytical portals. The proposed data workflow can improve the industrial analytics applications for multiple tasks. This article also provides bid data researchers and professionals with an understanding of the challenges facing big data analytics in real-world environments and informs interdisciplinary studies in this field.
Cognitive Biases and Data Visualization
Authors: Anderson Billie , Hardin J. Michael
Published: January 2023

This article will provide background on cognitive biases related to data visualizations, with a particular interest towards visual analytics in big data environments. Cognitive biases that appear in visualizations will be discussed. A review of recent studies related to designing experiments to mitigate cognitive biases in data visualizations will be presented. Recommendations, using applied frameworks for detecting and mitigating biases in single visualizations and visual analytic systems, will be provided to practitioners.
Software for Teaching
Authors: Da Silva F. Kenia C. , Raidi Ch. Coromoto D. M. , Hernández G. Gilberto J. , García G. María J. , Hernández R. José G.
Published: January 2023

Interactive tools, in English and Spanish, have been produced to facilitate the teaching. One that stands out is the one created to facilitate the teaching of the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE). This article presents some comments on the process of creating this software, and to illustrate it will use the case of PROMETHEE. Hence, the objective of this work is to present the process of creating a teaching tool, specifically that of the PROMETHEE case. The methodology to be used to complete this work is the integrated-adaptable methodology for the development of decision support system.
Machine Learning for Decision Support in the ICU
Authors: Lin Yu-Wei , Chang Hsin-Lu , Karhade Prasanna , Shaw Michael J.
Published: January 2023

In this article, the authors provide an overview of the potential and challenges of machine learning for healthcare decision support. They first discuss the healthcare decision support ecosystems, including (1) beneficiaries, (2) health data, and (3) models. They then introduce the three main challenges of the healthcare decision support systems: data complexity, decision criticality, and model explainability. From there, they use unplanned intensive care unit readmission predictions in tackling the three main challenges of machine learning-based healthcare decision support systems. They investigate the data complexity issue by adopting dimension reduction techniques on patients' medical records to integrate patients' chart events, demographics, and the ICD-9 code. To address the decision criticality issue, they perform an in-depth deep learning performance analysis, and they analyze each feature's contribution to the predictive model. To unpack the model explainability issue, they illustrate the importance of each input feature and its combinations in the predictive model.
Artificial Intelligence Into Democratic Decision Making
Authors: Vidalis Takis
Published: January 2023

Although political decisions deeply affect our personal and social lives and determine the future of any society, their quality is often disputable. This is due to elements of poor information and irrationality that conventional decision-making involves, like insufficient documentation, biased evaluation of the data collected, absurd preferences, or even corrupting practices of the responsible politicians or administrative personnel. This article explores the possibility to improve the quality of political decisions in general, and more specifically of governmental decisions concerning legal regulation, by introducing artificial intelligence applications into the process of decision-making. Three topics deserve special attention: 1) the question on compliance with constitutional prerequisites that characterize every modern democracy, 2) the problem of personal data collection and processing, and 3) the question related to political accountability.
Educational Data Mining and Learning Analytics in the 21st Century
Authors: Lampropoulos Georgios
Published: January 2023

This article aims at offering an overview of educational data mining and learning analytics and highlighting their essential role in improving 21st century education. Hence, it analyzes their concepts, goes over the recent literature, and extracts invaluable information according to the results and outcomes of related studies. Furthermore, it discusses their use in educational settings, examines their benefits, and suggests ways to address some of the current open challenges, issues, and limitations. In addition, it presents the summary of the main findings, draws conclusions, and provides directions for future research. Based on the results, educational data mining and learning analytics fields can significantly influence the current educational system and provide opportunities for new learner-centered tools and smart learning environments that provide customized experiences and meet students' specific needs to be developed. Finally, it was evident that for the complete adoption of these fields, a data-driven culture should be followed by the educational institutions.
Machine Learning in the Real World
Authors: Kampakis Stylianos
Published: January 2023

Most data scientists and machine learning practitioners focus on algorithm development and implementation. However, the proper and successful application of data science in an organisation cannot be separated from business objectives and organisational dynamics. This way of thinking, however, can feel foreign to many data scientists who focus mostly on technical details. The goal of this article is to outline some of the considerations that a data scientist needs to take into account when implementing data science within an organisation. More specifically, this article discusses the topics of data strategy, data science processes, and some recent developments like MLOps.
Effective Bankruptcy Prediction Models for North American Companies
Authors: Cardarelli Rachel , Nguyen Son , Gorvett Rick , Quinn John
Published: January 2023

Bankruptcy prediction is a widely researched topic. However, few studies focus on dealing with the imbalance problem. This article proposes a new technique that applies a bagging undersampling procedure to balance the data and compares it to random undersampling and five oversampling techniques. The performance of the algorithm is evaluated by a random forest's balanced accuracy, sensitivity, and specificity. The results show that models trained after applying the oversampling techniques are prone to overfitting, and the model trained after applying the proposed method had the highest balanced accuracy without overfitting.
Product Offer and Pricing Personalization in Retail Banking
Authors: Ke Wei , Vleming Rogan Johannes , Shah Rohan
Published: January 2023

The rise of parametric and non-parametric modeling capabilities has opened up new possibilities for banks to shift from a fragmented, siloed, and product-centric approach when it comes to pricing and marketing towards orchestrated one-to-one marketing where the bank is able to automate and tailor communications, pricing, and products offers to speak directly to their customers in context-appropriate, relevant ways. Developed using internal and external data, these models can consider a customer's wider relationship with the bank to personalize next-best offers, adapt messages based on reactions and feedback, and nudge customers towards desired actions with high-levels of accuracy and relevance. To optimize the application of machine-learning (ML)-powered personalization in the retail bank setting, a number of critical elements are required including data reliability, supporting response models, behavior-based customer segmentation grids, and customer lifetime value models for commercial effectiveness. A level of organizational maturity is also needed.
Best Practices of Feature Selection in Multi-Omics Data
Authors: Ipekten Funda , Ertürk Zararsız Gözde , Doğan Halef Okan , Eldem Vahap , Zararsız Gökmen
Published: January 2023

With the recent advances in molecular biology techniques such as next-generation sequencing, mass-spectrometry, etc., a large omic data is produced. Using such data, the expression levels of thousands of molecular features (genes, proteins, metabolites, etc.) can be quantified and associated with diseases. The fact that multiple omics data contains different types of data and the number of analyzed variables increases the complexity of the models created with machine learning methods. In addition, due to many variables, the investigation of molecular variables associated with diseases is very costly. Therefore, selecting the informative and disease-related molecular features is applicable before model training and evaluation. This feature selection step is essential for obtaining accurate and generalizable models in minimum time with minimum cost. Some current methods used for feature selection are as follows: recursive feature elimination, information gain, minimum redundancy maximum relevance (mRMR), boruta, altmann, and lasso.
Deep Learning for Cyber Security Risk Assessment in IIoT Systems
Authors: Stojanović Mirjana D. , Marković-Petrović Jasna D.
Published: January 2023

This article addresses cyber security risk assessment in industrial internet of things (IIoT) networks, and particularly the continuous risk assessment (CRA) process, which assumes real-time, dynamic risk evaluation based on the run-time data. IIoT cyber security risks, threats, and attacks are briefly presented. Requirements for cyber security risk assessment of industrial control systems as well as applicability of machine learning for that purpose are considered. The architectural view of the CRA process in the IIoT environment is presented and discussed. Possibilities of deep learning approaches to achieve CRA in IIoT systems are explored. Deep learning can be integrated into edge-computing-based systems and used for feature extraction and risk classification from massive raw data. Several research works are presented and briefly discussed. The article ends with emphasizing the future research directions and concluding remarks.
Analysis of Frequency Domain Data Generated by a Quartz Crystal
Authors: Murrieta-Rico Fabian N. , Rivas-López Moisés , Sergiyenko Oleg , Petranovskii Vitalii , Antúnez-García Joel , Rodríguez-Quiñonez Julio C. , Flores-Fuentes Wendy , Mercado Herrera Abelardo , Gárate García Araceli
Published: January 2023

During the monitoring of a process, there are multiple information sources that can generate large amounts of data in a continuous fashion. Accordingly, the appropriate use of data science tools is required. In this work, data was generated from the measurement of the frequency in a signal, whose frequency was defined by a quartz crystal. In order to generate a stable frequency, the quartz crystal was connected to a gate-oscillator. Then the frequency was measured using a frequency counter that implements the principle of rational approximations. In this method, the desired signal is compared with other signals whose frequency is known. After some conditions are fulfilled, the desired frequency is approximated. In this experimental set-up, besides of the desired frequency, other parameters were measured, such as temperature and relative humidity. As a result, a large amount of data was generated and analyzed using the principal components analysis.
Challenges and Chances of Classical Cox Regression
Authors: Xia Mengying , Wang Leigh
Published: January 2023

Cox regression is the method for investigating the effect of several variables upon the time a specified event takes to happen. It is also known as the proportional hazards regression because it is all revolved around survival analysis. The Cox proportional hazards (CPH) model is the most frequently used approach for survival analysis in a wide variety of fields. This article summarizes current research, especially its applications in the area of diagnosis and treatment of coronavirus disease 2019 (COVID-19). Also, the pros and cons of competitive machine learning (ML) models for targeting the same object will be presented.
Quantile Regression Applications in Climate Change
Authors: Wang Leigh , Xia Mengying
Published: January 2023

Climate change has become one of the most severe and pressing world issues due to its destructive effects of environmental degradation. Climate change aggravates global warming and brings about potential risks for both human society and natural systems. The quantile regression being used to help with climate change is exceptionally new. The article scrutinizes the newest developments in this important research area and provides the future research directions.
Investigating the Character-Network Topology in Marvel Movies
Authors: Kumar Sameer , Verma Tanmay
Published: January 2023

Marvel Entertainment movie production house has rolled out movies that have seen record commercial success over the years. In this article, the authors investigate the social network formed by connecting the characters that have featured in the Marvel movies and thus examine their structural topology. Characters like Quicksilver and Hulk emerge as the main “bridging” characters. Movies, such as the Avengers series, emerge as central “bridging” movies. A positive relationship between user ratings and commercial success was seen with larger star cast being preferred choice of the audience in the recent years – especially the ones that bring supermen together. The network of 393 actors consists of 2814 unique edges. Cluster analysis using the Clauset-Newman-Moore cluster algorithm detects communities of actors who have acted together, but yet may be connected to the overall character network through a character who may have co-acted in two different movies dominated by the different “universes.”
Use of “Odds” in Bayesian Classifiers
Authors: Kapoor Bhushan , Mitra Sinjini
Published: January 2023

Odds, log odds, and odds ratio concepts can be effectively applied in several machine learning algorithms and model evaluations. The use of these concepts has potential to make the algorithms simple, easy to interpret, and computationally more efficient. However, their implementation among the machine learning professional community has been concentrated mainly in the context of logistic regression. In this article, the authors discuss how odds, odds ratio, and log odds can be used in Bayes' theorem and multinomial naïve Bayes' classifiers. The authors will reformulate Bayes' theorem and multinomial naïve Bayes' classifiers in terms of “odds” and illustrate their applications with examples dealing with “loan application” approval.
Machine Learning for Housing Price Prediction
Authors: Annamoradnejad Rahimberdi , Annamoradnejad Issa
Published: January 2023

The housing market is one of the earliest and most influential industries with interests among general populations. In recent years and with the advent of computer approaches, many studies used the latest machine learning models to analyze the housing market and identify its most important influential variables in order to suggest a proper price or to predict price fluctuations. This article follows the general phases of the CRISP-DM process model for data mining to elaborate on the problem statements, data collection and preparation, modeling, and evaluation. It suggests proper ways to design steady and accurate models in relation to previous methods and approaches for predicting housing prices. Based on this investigation, previous methods suffer from reaching steady results on multiple datasets, which can be largely attributed to the existence of bias in training, as it is essential to predict prices by considering external economic variables.
Hybrid Machine Learning for Matchmaking in Digital Business Ecosystems
Authors: Benramdane Mustapha Kamal , Bouzefrane Samia , Banerjee Soumya , Maupas Hubert , Kornyshova Elena
Published: January 2023

Digital platforms bring together organizations from different market segments. Consequently, digital business ecosystems orient themselves gradually according to the constraints imposed by different organizations although they are under the same segments. This phenomenon of influence also considerably enriches the data corpus. It has seldom been observed that the existing data features are always dynamic in nature. The context has become more challenging as many companies are often reluctant to share their information probably due to its confidentiality. Hence, with this paradigm of several variations, conventional matching to search a particular enterprise from the largest data corpus fails to deliver optimal matching prediction with respect to the different roles of the enterprises. This article presents an analytical and practical case study deploying a hybrid machine learning algorithm. The proposed methods depict the background of the digital business ecosystem, missing data imputation, and supervised machine learning approaches towards developing such models.
Integration of Knowledge Sharing Into Project Management
Authors: Novais Zinga , Gomes Jorge , Romão Mário José Batista
Published: January 2023

Projects have been increasingly used in the implementation of organizations' business operations. Knowledge sharing has been considered essential in project environment; therefore, the integration of knowledge management within project management becomes crucial for project success. The objective of this research is to study how knowledge sharing is integrated within the context of a project, and what the perception of project team members about it is. A study was carried out in a company within the financial sector, focused on a project team of the entity. The results revealed that project managers, other professionals in project management, and the organization itself are very aware of the importance of knowledge sharing. The results also emphasized that, regardless of the lack of incentives by top management, project team members consider that knowledge sharing highly contributes to a successful execution of projects.
Enhancing IT Graduates’ Employability Skills for Surviving in New Normal: Perspective of IT Professionals
Authors: Samarasinghe H. M. U. S. R. , Kumarapperuma C. U. , Rathanayke R. M. N. M. , Karunarathne K. N. P.
Published: January 2023

This research focused on how Information Technology (IT) Higher Education Institutes (HEIs) contribute to equip IT graduate employability, from the perspective of IT industry experts in Sri Lanka. The research further identifies the mismatches between IT HEIs’ contributions to equip IT graduate employability and the industry demands after COVID 19 in Sri Lanka. Thirteen semi structured interviews were conducted via zoom platform with the industry experts representing major IT companies in Sri Lanka. The interview protocol was designed to get the expert opinion about the contribution which HEIs can make to equip future graduates with necessary employability skills in general and specifically in the new normal. According to key findings of the study, providing opportunities for industrial experience, sharing technical and practical knowledge, up-to-date syllabus, firm foundation of knowledge, trainings on online platforms and tools, developing soft skills and remote working skills of graduates such as trustworthiness, minimum supervision, stress management, self-driven, attitude, team spirit, ability to take challenges and responsibilities were identified as the areas in which HEIs could contribute towards creating smart IT graduates with a digital presence ready to be employed in new normal. The outcome of this study will strengthen HEIs with necessary requirements to upgrade their IT education quality and quantity wise as then graduates can meet industry expectations for better employability.
Role of Big Data in Human Resource Management: A Review and Bibliometric Analysis
Authors: Mathushan Packiyanathan , Gamage Aruna S. , Thero Ven. Wachissara
Published: January 2023

During the last decades, big data has been recognized as a salient enabler of human resource management performance. Although increasing academic attention on big data in human resource management has been generated, there is still a void in this research domain. Due to the increasing academic interest in big data in HRM, a thorough bibliometric analysis of the structure and development of this research topic is required. Correspondingly, classic narrative literature evaluations provide substantial contributions, notwithstanding inadequate to give an exhaustive overview of a particular research area. Consequently, scientific mapping, which garners bibliometric techniques to structure and develop a specific area graphically, is gaining salience. Thereby, the overriding aim of this research is to examine Scopus publications related to big data and human resource management. Bibliometric analysis was performed to explore the growing trends, global distribution, thematic evolution, influential articles, researchers, keywords, and dominating countries in big data and HRM. The cluster analysis results highlight the most important topics for current and future academics in the fields of HRM and AI. Emerged clusters include Cluster1: adoption of HR analytics; Cluster2: decision support systems; Cluster 3: dynamic capabilities; Cluster4: digital innovation; Cluster5: organizational ambidexterity; Cluster6: internet of things; Cluster 7: cloud computing. The result is intended to show academics and practitioners a state-of-the-art and comprehensive view of the diverse and multidimensional phenomena of big data and HRM research.
Iatrogenic Rupture of the Urinary Bladder in an Infant During Retrograde Cystourethrography
Authors: Foura Salma , Fouraiji Karima , Aballa Najoua , Kamili El Ouafi EL Aouni , Saiad Mohamed Oulad
Published: January 2023

Iatrogenic bladder rupture in children during a retrograde cystourethrography is very uncommon. We present a case of iatrogenic intraperitoneal bladder rupture in a 9-month child during the retrograde cystourethrography performed by a radiologist. The child presented in a paediatric emergency after 6 h with an acute abdomen indicating urinary peritonitis. An urgent laparotomy was performed and the perforation was repaired in two layers. The follow-up was unremarkable. This report emphasises the importance of respecting the criteria of the proper retrograde cystourethrography imaging procedure.
Amenability and acyclicity in bounded cohomology
Authors: Moraschini Marco , Raptis George
Published: January 2023

Johnson’s characterization of amenable groups states that a discrete group

\Gamma

is amenable if and only if

H_b^{n \geq 1}(\Gamma; V) = 0

for all dual normed

\mathbb{R}[\Gamma]

-modules

V

. In this paper, we extend the previous result to homomorphisms by proving the converse of the
mapping theorem
: a surjective group homomorphism

\phi \colon \Gamma {\to} K

has amenable kernel

H

if and only if the induced inflation map

H^\bullet_b(K; V^H) {\to} H^\bullet_b(\Gamma; V)

is an isometric isomorphism for every dual normed

\mathbb{R}[\Gamma]

-module

V

. In addition, we obtain an analogous characterization for the (smaller) class of surjective group homomorphisms

\phi \colon \Gamma \to K

with the property that the inflation maps in bounded cohomology are isometric isomorphisms for
all
Banach

\Gamma

-modules. Finally, we also prove a characterization of the (larger) class of
boundedly acyclic
homomorphisms, that is, the class of group homomorphisms

\phi \colon \Gamma \to K

for which the restriction maps in bounded cohomology

H^\bullet_b(K; V) \to H^\bullet_b(\Gamma; \phi^{-1}V)

are isomorphisms for a suitable family of dual normed

\mathbb{R}[K]

-modules

V

including the trivial

\mathbb{R}[K]

-module

\mathbb{R}

. We then extend the first and third results to topological spaces and obtain characterizations of
amenable
maps and
boundedly acyclic
maps in terms of the vanishing of the bounded cohomology of their homotopy fibers with respect to appropriate choices of coefficients.
Lógicas y orientaciones del activismo digital. Del uso y la apropiación al desarrollo de herramientas autónomas
Authors: Candón Mena José Ignacio , Montero Sánchez David
Published: January 2023

Introducción: A partir de la revisión teórica el presente artículo distingue dos lógicas diferenciadas que van desde el uso por parte de los activistas de herramientas comerciales al desarrollo de tecnologías autónomas impulsadas por los propios movimientos. Objetivos: El objetivo del texto es definir distintas orientaciones del activismo digital a partir de contribuciones que nos permiten reconocer lógicas de acción diferenciadas en torno a la relación entre movimientos sociales y tecnologías digitales. Se analiza críticamente dichas aportaciones y las contrastamos con la realidad empírica para cuestionar y complejizar las nociones de partida, señalando contradicciones o usos complementarios que trascienden etapas y cuestionan la lógica bipolar o evolucionista que a veces se perfila en otros enfoques. Conclusiones: Las conclusiones apuntan a una multidimensionalidad de factores que inciden en las formas en que los movimientos usan la tecnología: prácticos o utilitaristas, estratégicos y tácticos, e ideológicos o identitarios.
Qua maxima Roma est
Authors: Boldrer Francesca
Published: January 2023

L’articolo approfondisce il rapporto tra la letteratura latina e il principato augusteo con attenzione alle elegie romane di Properzio. Vengono prese in esame le trasformazioni del suo genere letterario nel IV libro, ricco di nuovi temi (religiosi, eziologici, morali), sia nel contesto storico-culturale che nel rapporto con gli altri membri del circolo di Mecenate (Virgilio, Orazio), evidenziando anche i possibili influssi dell’autore sul princeps.
South America’s military governments during the Cold War: a discussion of inter-state warfare
Authors: Sánchez Wilder Alejandro
Published: January 2023

During the Cold War, dozens of military governments existed in South America. Some lasted only days or weeks, while others lasted years and even decades. The human rights abuses carried out by these military governments have been well analysed, like Argentina’s Dirty War. However, an interesting fact about this period tends to be ignored: inter-state warfare between South American states, even during military governments, was very scarce. The Falklands / Malvinas war is the only case of a South American military government, Argentina, beginning a war against another state, the United Kingdom. There were other incidents that could have caused inter-state warfare during this era, but war was avoided. The only other inter-state war during the Cold War in South America happened in 1981 between Ecuador and Peru, both being under civilian rule. There were (and still are) reasons for South American states to attack one another, particularly to regain lost or disputed territory; however, as this essay demonstrates, war was almost non-existent. This essay will discuss why South American military governments did not attack their neighbours during this turbulent period.
Trajectories, bifurcations and hysteresis in the Argentine economic cycle: the economic policy of Sudden Stops
Authors: Schiaffi Pablo
Published: January 2023

This paper analyzes the evolution of the Argentine gross domestic product between 1875-2010. It intends to analyze its trajectory over time according to the periods of greater or lesser economic integration that the country experienced. An explanation of the poor performance that occurs between 1970-2010 (second globalization) is presented and compared with the period 1885-1914 (first globalization). This paper presents a series of graphic arguments that will allow us to analyze the evolution of the Argentine gross product from 1885 to 2010. It is not intended to explain or investigate the specific causes or reasons for the prosperity or depression that Argentina experienced in each of its episodes. Instead, an attempt is made to present longterm stylized facts seeking to compare moments of opening versus those of a closed economy over which the country oscillated in order to analyze long-term growth and economic volatility.
ALTERNATIVAS METODOLÓGICAS E SUAS CONTRIBUIÇÕES FRENTE A BIOLOGIA MOLECULAR NO ENSINO MÉDIO
Authors: Cabral Ivanna Aparecida de Oliveira
Published: January 2023

As novas metodologias têm sido cada vez mais exploradas pelos professores, em todas as disciplinas, incluindo a Biologia Molecular, contribuindo para transformar a aula num momento mais dinâmico e participativo, levando os alunos a desenvolverem a imaginação, a observação e o senso crítico. A presente pesquisa tem como objetivo analisar de que forma as metodologias podem contribuir para a construção da aprendizagem no ensino de Biologia Molecular no ensino médio. Inicialmente foi realizada uma pesquisa bibliográfica com estudiosos dessa temática, tais como: Pinho (2006), Orlando et al (2009), Moura (2013), dentre outros. Acredita-se que as metodologias são ferramentas atrativas, que adotada pelos professores dentro de um planejamento coerente é capaz de motivar o aluno para novas aprendizagens.
MAINTAINING THE QUALITY OF CARNATION CUT FLOWERS DEPENDING ON TEMPERATURE
Authors: Gocan Tincuța-Marta , Andreica Ileana , Poșta Daniela-Sabina , Rozsa Melinda , Lazăr Vasile , Rózsa Sándor
Published: January 2023

In the assortment of cut flowers, carnations (Dianthus caryophyllus L.) fall in the first places, with a large number of varieties, of various colors, being appreciated on the cut flowers market. Carnations flowers that cannot be sold immediately after harvest, being a time of year when the market offers an abundance of cut flower species, they are prone to rapid depreciation under normal environmental conditions. Carnation is an important ornamental plant, which is used as a potted plant as well as a cut flower. One factor that influences the shelf life is temperature. From the flowering stage to the total depreciation of the inflorescence, it plays an important role. In this experiment, the flowers were harvested on two different dates for about a month. The temperatures at which the varieties were kept had 6 graduations (from 10 to 22 °C). The parameters followed were: bud height, corolla height above the calyx, bud diameter and flower stem length. Storing flowers in water at 4 °C for 6 to 15 days, did not increase the diameter of the flower bud. In flowers kept at 22 °C for 6 days, the values of several parameters of cell senescence fell below the values of fresh flowers. However, in flowers kept at 4 °C there was no expected slow decrease in these parameters, but rather an increase above the levels found in fresh flowers. We conclude that storage at low temperatures has effects on carnation cut flowers, other than slowing down the aging process.
Do Cashflow Components and net profit affect earnings per share in the IDX-listed LQ-45 company?
Authors:   Trisakti University, Jakarta, Indonesia, Putri Fifia Aryanto , Khomsiyah Khomsiyah
Published: January 2023

The purpose of this study is to test the relationship between Cash Flow Component Disclosures and Net Income to Earnings Per Share in LQ-45 companies. The population in this study was LQ-45 companies listed on the Indonesia stock exchange during the period 2017 to 2020 consisting of 28 companies. The sampling technique used in this study was purposive sampling. Multiple regression analysis is used to analyze the data. The results of this study Through multiple linear regression analysis, it is known that the components of cash flow and net profit affect earnings per share. Simultaneously independent variables show can jointly affect earnings per share.
Utilizing Demographic Bonuses in the Era of the Industrial Revolution 4.0 in the North Tatura Village, South Palu District, Palu City
Authors:   College of Development Administration Science-Palu, Sussanti Sussanti
Published: January 2023

The purpose of this study was to find out the ways in which the North Tatura sub-district government took advantage of the demographic bonus to serve the community well in the Industrial Revolution 4.0 era. Based on the results of the research conducted, it is known that the North Tatura sub-district government did not take advantage of its demographic increase to provide services to the community in the Industrial Revolution 4.0 era. The North Tatura Sub-district continues to strive to innovate in providing services because it still refers to service standards that force people to come directly to the Kelurahan when they get the desired service. Apart from that, the lack of soft skills in the North Tatura sub-district apparatus is also one of the reasons for the lack of implementation of digital public services
Aplasia pura de células rojas como forma de presentación de lupus eritematoso sistémico
Authors: Martín-Serradilla José I. , Del Castillo Tirados Francisco Javier , Álvarez De Buergo María , Alonso Alonso José M. , Sánchez Barranco Fernando , Álvarez Artero Elisa
Published: January 2023

La aplasia pura de células rojas (APCR) es un síndrome definido por anemia normocítica normocrómica, con reticulopenia severa y reducción importante o ausencia absoluta de precursores eritroides en la médula ósea. Ocasionalmente se desencadena en el curso de una colagenopatía o una enfermedad autoinmune. Presentamos el primer caso descripto en la literatura de un varón con APCR como forma de debut de lupus eritematoso sistémico (LES). Se trata de un hombre de 65 años que presentó anemia normocítica normocrómica, ANA 1/5120 y anti-Sm 2,61. Refería úlceras orales, poliartralgias, tumefacción de ambos tobillos y fotosensibilidad. Se realizó estudio de médula ósea con evidencia de hipoplasia de serie roja por paro madurativo a nivel de eritroblasto basófilo, ausencia casi completa de los elementos maduros y contenido muy elevado de proeritroblastos de gran tamaño. Con el diagnóstico de APCR como debut de LES, se lo trató con prednisona con buena respuesta. Podemos concluir que el despistaje de enfermedades sistémicas en pacientes con APCR es esencial para asegurar un correcto manejo y un mejor pronóstico.
El secreto que revelan los ojos. Compromiso ocular como manifestación de enfermedades sistémicas no infecciosas
Authors: Correa Lemos María Eugenia , Paira Noelia , Gallo Jesica , Ortíz Alberto , Paira Sergio
Published: January 2023

La coroides es el tejido ocular más comúnmente afectado por la enfermedad metastásica debido a su abundante vascularización y, en ocasiones, la primera manifestación (44-70% según las series) de cáncer de pulmón en hombres o de cáncer de mama en mujeres (3%). Síntomas oculares de inicio abrupto en pacientes jóvenes y signos al examen oftalmológico como engrosamiento de la pared posterior o lumpy‑bumpy surface, entre otros, son orientativos. La uveítis anterior granulomatosa, la uveítis intermedia bilateral, la panuveitis bilateral o las lesiones granulomatosas a nivel coroideo o del nervio óptico se consideran indicativas de sarcoidosis en presencia de un cuadro radiológico compatible. Estas pueden preceder a los signos sistémicos en un 30% de los casos.

Se presentan tres pacientes con signos y síntomas oftalmológicos que precedieron al diagnóstico de enfermedades sistémicas no infecciosas.
IDENTIFY THE CHALLENGING BEHAVIORS OF CHILDREN WITH AUTISM IDENTIFIED BY THE PARENTS
Authors: anupama Ms. Anupama , mani k Dr Rukmani
Published: January 2023

Children with Autism Spectrum Disorders (ASD) are not genuinely sick or impaired like somebody with mind
injury. ASD are generally described by some or all of the followings: 1. Challenges communicating with others
or associating with others 2. Communication difficulties and 3. Repetitive way of behaving (National foundation
of Mental Health 2017). Settings and design: Quantitative approach was used in the present study. Quasi
experimental, one group pre test post test design was used. The study design was an institution based cross
sectional study. The review was directed among parents of children with ASD who have a child taking therapy
in establishments in particular: Child Development Center (CDC), National Institute of Speech and Hearing
(NISH), Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), Central Institute on Mental
Retardation (CIMR), Buds school Venganoor and Malayalamkeezhu. CDC, NISH and SCTIMST are the three
trailblazer foundations in Kerala where particular groups determine and get children have formative issues. The
anticipated sample size was 500. A total of 510 subjects participated in the study. Results: Majority of children
in the present study were in 1-3 years age group.
Shoulder Dislocation in the Emergency Department: Experience within a Large District General Hospital
Authors: Victor Ameh  , Ayaz Abbasi  , Hareem Basir
Published: January 2023

Objectives: To evaluate the incidence of shoulder dislocation, age and gender distribution, success and failure rate following attempts at reduction in the ED and factors associated with failed reduction. Secondary outcome measures include type and number of medications required for successful reduction and complications associated with reductions attempts.
Methodology: A retrospective chart review of all patients presenting to the Emergency department with shoulder dislocation within the study period was undertaken. The study was undertaken over a one-year period from 1st December 2018 to 30th November 2019 within the ED of a large DGH that receives approximately 100,000 attendances per annum. Data was extracted on to a proforma including patient demographics, type of dislocation, number of attempts at reduction and complications. The data was reviewed and analysed by two of the study authors.
Results: We found an incidence of shoulder dislocation of 16.5 per 100,000 attendances (less that 1% of ED) presentations per annum. The mean age was 58.8 years. There was a male preponderance in terms of gender distribution with males making up 67% and females 33%. There was a peak incidence in men within the age range 21-30 years.Â  There was a 76% (n=25) successful reduction rate in the ED.
Attempts at reduction failed in 8 cases (24%). The mean age of the failed reduction group was 46.5 years (95% CI, 24.96-58.79). It was 61.6 years (95% CI, 57.3-75.2) in the successful reduction group. The use of morphine, paracetamol and sedation were associated with successful reduction. All failed reduction attempts required general anaesthesia to achieve reduction.
Antibacterial Activities of Biosynthesized Zinc Oxide Nanoparticles and Silver-Zinc Oxide Nanocomposites using Camellia Sinensis Leaf Extract
Authors: Jha Pankaj Kumar , Chawengkijwanich Chamorn , Pokum Chonlada , Soisan Pichai , Techato Kuaanan
Published: January 2023

Green route of nanomaterials synthesis is increasing in demand due to ecofriendly to the environment. In this research, objective is to biosynthesize and evaluate the antibacterial performance of pure ZnO and Ag/ZnO nanocomposites using Camellia sinensis leaf extracts. Pure ZnO nanoparticles and Ag/ZnO nanocomposites were synthesized using Camellia sinensis leaf extract. The antibacterial effectiveness against gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) bacteria were examined and compared with 1 % Chlorox as a commercial disinfectant by well diffusion method based on the zone of inhibition. Pure ZnO nanoparticles and Ag/ZnO nanocomposites had hexagonal shape ZnO nanoparticles and rectangular shape Ag nanoparticles in Ag/ZnO nanocomposites with a particle crystal size between 20 - 30 nm with carboxylic and phenolic functional group attached on it. Ag/ZnO nanocomposites exhibited antibacterial effectiveness against both gram-positive and gram-negative bacteria, while pure ZnO nanoparticles exhibited antibacterial effectiveness against only gram-positive bacteria. Conversely, 1 % Chlorox and 1 % DMSO showed no significant antibacterial activity against gram-positive and gram-negative bacteria. Camellia sinensis mediated ZnO and Ag/ZnO nanoparticles showed antibacterial potential against S. aureus and E. coli suggesting that green route to synthesis of antibacterial nanoparticles can be an excellent strategy to develop eco-friendly disinfectant products
HIGHLIGHTS

Zinc oxide nanocomposites biosynthesis by Camellia sinensis at low pH, Antibacterial properties of ZnO nanoparticles and Ag/ZnO nanocomposites on Escherichia coli ATCC 8739 and Staphylococcus aureus ATCC 6538P strains, Disinfection application.

GRAPHICAL ABSTRACT
neurociencia como fundamento de la educación emocional
Authors: Bueno David
Published: January 2023

Educar es, según el diccionario, “desarrollar o perfeccionar las facultades intelectuales y morales del niño o del joven por medio de preceptos, ejercicios, ejemplos, etc.”. Procede del vocablo latino educare, textualmente “e” (por “ex»”), es decir, fuera, y “ducare”, conducir. Educar es, por consiguiente, “conducir desde fuera”. Sin embargo, una de las aspiraciones máximas de la educación debe ser contribuir a que los niños, los adolescentes y los jóvenes desarrollen capacidades que les permitan conducirse a sí mismos, para que sean no sólo los protagonistas, sino también los directores de su propia vida. La capacidad cognitiva que se relaciona con esta capacidad de dirigir la propia vida forma parte de las denominadas funciones ejecutivas, una de cuyas vertientes más importantes es la gestión emocional, que es imprescindible para la toma de decisiones reflexivas. La educación emocional se convierte, por este motivo, en un aspecto clave de la educación de las personas. Esta afirmación, sustentada hace ya algunas décadas desde la pedagogía y la psicología, ha encontrado también un soporte equivalente con los avances de otro campo del conocimiento, la neurociencia. En este artículo se aborda el tema de la generación y la gestión de las emociones en un contexto neurocientífico, a partir de las áreas cerebrales implicadas, y se relaciona con un concepto crucial para fomentar el bienestar y la dignidad individuales y colectivas, el éxito vital, que es la sensación subjetiva de sentirse razonablemente bien con uno mismo y con su entorno, de forma proactiva y transformadora.
vocabulario emocional de los jóvenes
Authors: Gomis Cañellas Raquel , Garcia Blanc Núria , Filella Guiu Gemma , Ros Morente Agnès
Published: January 2023

Si entendemos la salud desde una perspectiva global, es decir, no sólo física sino también mental, el bienestar emocional es clave para poder tener un completo estado de salud. La adolescencia es una etapa en la que se producen muchos cambios y las emociones juegan un papel fundamental. Así pues, la educación emocional adquiere gran importancia en este periodo. Para entender las emociones, el primer paso es tener conciencia emocional y, en este sentido, es básico tener un buen vocabulario emocional ya que, si no podemos poner nombre a las emociones, éstas dejan de existir en su totalidad. Por este motivo, el siguiente estudio consiste en examinar y hacer un análisis sobre el vocabulario emocional en adolescentes.

Para ello se ha contado con una muestra de 431 adolescentes de entre 14 y 18 años, en concreto, 173 alumnos de segundo ciclo de ESO y 258 alumnos de Bachillerato. Se ha analizado el vocabulario del alumnado mediante una prueba estandarizada que consiste en escribir en tres minutos el número máximo de emociones posibles. Una vez obtenidos los datos se ha realizado un análisis estadístico, observando así las diferencias significativas entre las diferentes variables del alumnado. Como principales resultados se ha obtenido que el número de emociones tanto de ESO como de Bachillerato no es muy elevado. Además, hay más cantidad de palabras en las familias emocionales de emociones negativas y la familia en la que más palabras se han escrito es la de tristeza con gran diferencia con respecto a las otras, tanto en ESO como en Bachillerato.
Rimskopravni elementi u osmanskom građanskom zakoniku (Medželle i ahkjāmi šerijje)
Authors: Drino Dževad
Published: January 2023

ROMAN LAW ELEMENTS IN THE OTTOMAN CIVIL CODE (THE MAJALLA AND AHKAM AL-SHAR’IYYAH) The Majalla represents the first official codification of civil law in the Ottoman Empire, and also the first codification of sharia law in general, most often cited as the Ottoman Civil Code, which was published in the period between 1869 and 1876. In contrast to Islamic, Sharia law, the influence of the largest legal system of the ancient world, Roman law, which is bequeathed by the development of mankind in Europe, is visible in the Majalla; while Islamic law is considered Di-vine law and fundamentally immutable, Roman law finds that law should be the highest expression of the mind (Cicero). The Code sought to achieve the unity of two different legal traditions, striving to bridge any dualism on the path to modernism, thus opening new doors for its in-depth reading and understanding, in a concrete historical background. The application of Majalla was the widest in Bosnia and Herzegovina because its norms were binding on both Sharia and regular civil courts, so the analysis of its Roman legal basis is all the more important for our own legal history. Keywords: Majalla, Ottoman Empire, Roman law, Sharia law