bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Prediction of Cesarean Delivery Using Artificial Intelligence
Authors: Maniiarasan P. , Ramkumar P. , Uma R. , Abinaya K. , Deepika M.
Published: September 2023

Artificial intelligence (AI) techniques are used to extract crucial information. Data from cases of caesarean birth were analysed in this study. A caesarean section is typically performed when a normal delivery would be difficult for a variety of reasons or if a normal delivery could lead to future difficulties. With the use of actual instances obtained from a Tabriz health centre, this chapter investigated a number of AI approaches in this research to determine which delivery method is the safest for both mother and kid. In order to ensure more accurate and trustworthy outcomes, it also employed a cross-validation (CV) method to assess the deployed prediction models. With an accuracy rate of 65%, the Bayesian (NB) classifier fared better than the other chosen classifiers. In order to improve prediction, more data on caesarean deliveries are needed.
Prediction of Preeclampsia in Pregnant Women Using Machine Learning Paradigm
Authors: Devi K. Renuka
Published: September 2023

Machine learning is an area that helps to predict outcomes more accurately. It was utilized in different domains such as banking, healthcare, education, etc. Among all the domains, machine learning was largely utilized in the healthcare sector for predicting and diagnosing the disease in advance for saving millions of lives. ML has different kinds of algorithms which help to make the prediction process effective. This chapter focussed on explaining different machine learning algorithms for making better predictions in pregnancy complications in the healthcare domain. In general, there are different complications that women encountered during their pregnancy periods such as High BP, preeclampsia, anemia, etc. This work specifically aims to describe the preeclampsia complication during pregnancy. In machine learning, various kinds of regression algorithms are compared and analyzed. It also focused on which predictive technique would be more efficient for predicting the condition of preeclampsia in advance to save lives of pregnant women and also take necessary precautions.
Prediction of Baby Movement During Pregnancy Using Back Propagation and ID3
Authors: Alikkal Vinish , Sujina S.
Published: September 2023

The back propagation algorithm can be used to predict baby movement during pregnancy. This algorithm works by using a feed-forward neural network to identify patterns in the data that represent the baby's movements. It then uses back propagation to adjust the weights of the neural network to accurately predict the future movements. The ID3 algorithm can also be used to predict baby movement during pregnancy. This algorithm works by using a decision tree to identify patterns in the data that represent the baby's movements. It then uses the ID3 algorithm to identify the best decision at each node and to create a decision tree that can accurately predict the future movements. AI and machine learning can be used to monitor a fetus's vital signs in a number of ways. Back propagation and ID3 algorithms were used to detect any abnormality in the heartbeat, breathing patterns, or other physiological changes and used to track fetal movements, such as kicks and hiccups, as well as any changes in fetal position. Finally, AI and machine learning can be used to predict when a baby is ready to be born.
Solar Radiation Analysis for Predicting Climate Change Using Deep Learning Techniques
Authors: Kumar Rajendra
Published: September 2023

Solar radiation, Earth's main energy source, affects surface radiation balance, hydrological cycles, plant photosynthesis, weather, and climatic extremes. A stacking model based on the best of 12 machine learning models predicted and compared daily and monthly sun radiation levels. The results suggest machine learning algorithms use climatic parameters. A trend study of high land surface temperatures and solar radiation showed how solar radiation compounds catastrophic climatic events. GBRT, XG Boost, GPR, and random forest models better predicted daily and monthly sun radiation. The stacking model, which comprises the GBRT, XG Boost, GPR, and random forest models, exceeded the single models in daily solar radiation prediction but did not outperform the XGBoost model in monthly prediction. Stacking and XG Boost models estimate sun radiation best.
Plant Disease Classification Using Deep Learning Techniques
Authors: Kondaveeti Hari Kishan , Simhadri Chinna Gopi , Mathe Sudha Ellison , Vanambathina Sunny Dayal
Published: September 2023

Artificial intelligence (AI) has been a growing field in recent years, with the development of deep learning (DL) techniques providing new opportunities for plant disease classification. Convolutional neural networks (CNNs) and other advanced techniques such as transfer learning, deep ensemble learning, and others have been used to classify plant diseases with high accuracy. However, these techniques are not only complex but also challenging to implement, making it important to provide a comprehensive understanding of their use in plant disease classification. This chapter aims to explore the use of deep learning techniques for plant disease classification. It will provide an overview of the various DL techniques and their applications in the classification of plant diseases. It will also provide a comprehensive understanding of transfer learning, deep ensemble learning, and other advanced methods in plant disease classification. Additionally, the chapter will provide case studies to illustrate the practical applications of DL techniques in plant disease classification.
Investments in IS/IT Projects
Authors: Gomes Jorge Vareda , Romão Mario
Published: September 2023

The main objective of investments in information systems and technology is to increase operational efficiency, reduce costs, and improve the quality levels provided by organizations. In the last decades, IS/IT has positioned itself as a strategic tool that, through innovative combinations, has allowed the flexibility that organizations need to respond to current challenges. The health sector has sought to improve its effectiveness and efficiency through the adoption of IS/IT solutions to enhance quality of services, i.e., patient safety, organizational efficiency, and end-user satisfaction. Hospitals are complex organizations, and this complexity increases the opportunity for unavoidable human error. A poorly integrated system can decrease operational efficiency and reduce the quality of health services. The issue remains controversial. This study aims to review the literature on the topic and explore the trends and challenges that arise today. The study concludes that emerging technologies can offer opportunities for all organizations that effectively know how to better exploit them.
Machine Learning and IoT for Smart Parking Models and Approaches
Authors: Abilasha R. , Kumar A. V. Senthil , El Emary Ibrahiem M. M. , Mishra Namita , Talukdar Veera , Latip Rohaya , Musirin Ismail Bin , Sharma Meenakshi
Published: September 2023

There is an increase in the number of vehicles in last two decades. So, it becomes important to make effective use of technology to enable free parking in public and private places. In conventional parking systems, drivers face complexity in finding vacant parking slots. It requires more human involvement in the parking zone. To deal with the issue, the authors propose a smart parking system based on IoT and machine learning techniques to manage the real time management of parking and qualms. The proposed solution makes use of smart sensors, cloud computing, cyber physical system. It is victorious in addressing the challenges such as demonstrating status of parking slot in advance to end-user, use of reserved and unreserved parking slots, erroneous parking, real-time analysis of engaged slots, detecting numerous objects in a parking slot such as bike in car slot, error recognition in more mechanism, and traffic management during crest hours. This minimizes the individual interference, saves time, money, and liveliness.
Female Employment Patterns in the Tourism Sector
Authors: Alkan Hatice Işıl , Alkan Bora
Published: September 2023

Tourism has a strategic position in terms of production and employment, and stands out as a labor-intensive and feminized sector when examined in terms of employment. Asia-Pacific and Caribbean, Europe, and America come to the fore as geographies where female employment is very intense. This chapter strives to examine women's employment patterns in the tourism sector in the world, both in terms of regions and in the period before and after the pandemic. It is observed with the study that horizontal and vertical discrimination in the sector is quite evident. While women concentrate mostly in labor-intensive, low-paid, and informal jobs, their presence in jobs requiring high qualifications is extremely low. On the other hand, precarious employment of women as unpaid family workers is quite common. The Covid 19 pandemic has also adversely affected the female workforce. As the pandemic has increased inequalities in the sector, the hard-earned gains of women have also been eroded.
Commodification of Labor in Tourism
Authors: Dilek Nur Kulakoğlu , Dilek Sebahattin Emre
Published: September 2023

Tourism activities contribute to the economic development of countries through the transformation of values such as nature, culture, and history into attractive elements for tourists. However, the continuous growth of the tourism industry brings along numerous environmental and social issues, alongside the economic benefits it generates. To the extent that the tourism industry can perceive a country's culture, natural resources, historical sites, people, and even animals as commodities that can be used for capital gain. In this context, the study primarily evaluates the commodification of human and non-human labor in this industry. Subsequently, all tourism activities that exploit migrants, women, children, and animals, subjecting them to poor working conditions or sexual objectification, are examined through a cause-and-effect relationship. Regarding the concept of labor, a critical assessment is conducted based on the social reality where women, children, and animals are potentially seen as commodities in the tourism sector, and the topic is extensively addressed with examples.
Authenticity Under the Pressure of Commodification in Tourism
Authors: Yılmaz Özgür Devrim , Demirci Yavuz
Published: September 2023

The chapter begins by defining the concept of authenticity and discusses different types of authenticity. The concept of commoditization is then introduced, followed by a review of the literature on commoditization in terms of its positive and negative aspects. As a result, it seems obvious that a broad consensus on topics such as definition, classification, effects, precautions, or management decisions to be made on the idea of authenticity in tourism and the commodification of culture or cultural elements is not yet achievable. While it continues to be discussed in the relevant literature whether tourists today seek authenticity, it can be noted that certain cultural elements have become commodities and started moving away from authenticity in tourism destinations. Some cultural elements that provide a competitive advantage have become ordinary; and this situation is mostly accepted by local people who acquire an income from tourism. Moreover, when the relevant literature is reviewed, there are also studies claiming that commodification positively affects cultural authenticity.
Drugs and Psychedelics in Tourism
Authors: Altınok Feyza Alyu
Published: September 2023

Psychedelics are a class of substances that induce profound alterations in perception, cognition, and consciousness. They include substances such as psilocybin (found in certain mushrooms), LSD, and DMT. Drug tourism, on the other hand, refers to the practice of traveling to destinations specifically to engage in the consumption or exploration of drugs, both legal and illegal. It encompasses a range of experiences, from seeking out prescription medications at lower costs to participating in psychedelic retreats or engaging in recreational drug use. Drug tourism, encompassing legal and illegal drugs, is a significant part of the tourism industry, generating substantial revenue and attracting tourists to various destinations. This chapter delves into the fascinating and complex world of drugs and psychedelics in tourism, examining the resurgence of interest in psychedelic substances, the implications for tourist destinations, the therapeutic potential of psychedelics, and the associated health risks and ethical considerations.
Development of a Methodology for Educational Management Entailing Government, Economic Sectors, and Educational Institutions for Sustainable Development
Authors: Raygoza L. María E. , Jiménez-Sánchez Roxana , Orduño-Osuna Jesús Heriberto , Bonilla G. Diego Ramon , Mercado-Herrera Abelardo , Morales Carlos , Ortiz Rafael , Cota-Rivera Ivette , Limón-Molina Guillermo M , Murrieta-Rico Fabian N. N.
Published: September 2023

Worldwide guidelines since the 1980s have developed mechanisms with national and international economic funds for scientific and technological development that reduce greenhouse gas emissions (GHG) and mitigate environmental impacts. The objective of this chapter is to analyze the political, socioeconomic, and regulatory characteristics of Mexico as a country with a developing economy, as well as the actions that have made the country go backward in the energy transition, to make a proposal that serves as a guide. Among the precedents have been the Montreal Protocol and the Kyoto Protocol, which have sought to mitigate the use of greenhouse gases in industrialized countries and involve developing countries through various mechanisms that encourage the reduction of GHG, such as carbon credits. The UN (United Nations) continues to work with cutting-edge initiatives and programs such as the sustainable development goals (SDGs).
Teacher Candidates' Views on the Theme of Gender Equality in Curricula
Authors: Derman İpek
Published: September 2023

This study aims to determine the awareness of teacher candidates about gender equality to reveal their views on the emphasis on gender equality in national curricula and the importance of gender equality in teacher education. For this purpose, in the research designed according to the phenomenology design, it was ensured that teacher candidates examine the national curricula of their own branches under the theme of “gender equality” and reveal their views on gender equality based on the national curricula. The data obtained through semi-structured interview questions were analyzed by content analysis. The findings of the study indicate that the national curricula and teacher education programs in practice need to be reconsidered from the perspective of gender equality.
Optimization in the Selection and Use of Audiovisual Resources for Superior Education
Authors: Millan-Tudela Luis A. , Marco-Lajara Bartolomé , Martínez-Falcó Javier , Sánchez-García Eduardo
Published: September 2023

The use of audiovisual content (short self-elaborated videos, movie extracts, and similar) in teaching has been adopted since the digitalization in education facilities took place. However, the inclusion of these materials should be assessed to check for the fit with the learning goals established in each learning environment. This chapter proposes a methodology to validate the adequacy and the level of congruence of a given audiovisual content with those objectives, providing a deep analysis on the requirements that the selection of materials should meet.
Physical School Environment and Infectious Diseases
Authors: Hossain Afzal , Uddin Emaj
Published: September 2023

The mechanisms underlying relationships between unhealthy physical environment in schools and infectious disease transmission among students are understudied. Drawing from Bronfenbrenner's ecological systems theory, this chapter analyzes behavioral patterns as mechanisms by which an unhealthy physical school environment transmits infectious diseases to primary students in Bangladesh. For the study, the authors randomly selected 300 students from grade-C primary schools located in disadvantaged areas in Rajshahi City, Bangladesh; over 12 months, they collected data on the physical school environment, children's behavioral patterns, and their infections from infectious diseases in the primary school context. The study found that 20-45% of the students suffered from various infectious diseases during the study period. The results from structural equation modeling suggested that poor qualities of the physical school environment via unhealthy behavioral patterns transmitted infectious diseases, affecting the students' physical health in the primary schools.
The Economic Development Model and Strategy Selection of the Internet of Things Based on Big Data
Authors: Chen Xuelin , Zhao Xia , Ye Na
Published: September 2023

The internet of things (IoT) has become a key support object for Chinese strategic emerging industries. It is of great practical significance to promote the construction of the internet of things. Driven by national policies, the development of the internet of things in China has achieved certain results, but it also faces many problems. For example, there are few theoretical and empirical studies on the internet of things economy. In this context, from the perspective of big data, this paper studies the development model and influencing factors of the internet of things economy, and takes Jiangsu Province as an example to put forward development strategies. This article studies the three-stage development model of the IoT economic big data ecosystem: the primary stage, the growth and maturity stage, and the integration stage. On the basis of the research on the development model, the general evaluation method of the economic development model of the internet of things from the perspective of big data is studied, and the general model of strategy selection is established.
From the Editor…
Authors: Karunananda P. A. K.
Published: September 2023

No abstract available
Estimation Criteria for Static Rock Mass Deformability Modulus for Rock-Socket Design in Metamorphic Rock Masses
Authors: Samarawickrama M. N. C. , Puswewala U. G. A. , Thilakasiri H. S. , Udamulla K. M. L. A.
Published: September 2023

This study investigates the most appropriate empirical criteria to estimate the static rock mass deformability modulus (𝐸𝑚) in the design of rock-sockets in cast-in-situ bored pile construction. The in-situ 𝐸𝑚 values are initially estimated through back analysis of static pile load test data. Secondly, the rock mass deformability estimated from back analysis (𝐸𝑚b) are tested statistically against selected established empirical equations to determine whether the latter are appropriate for use in metamorphic rock terrain of Sri Lanka. It is found that the existing empirical criterion based on the square root of intact unconfined compressive strength (𝜎𝑐) derived from back analysis of pile load test results is appropriate for weak-poor rock masses. For strong-poor rocks, it is recommended to employ the equation based on 𝜎𝑐', and in general the two equations generate lower and upper bound solutions. The equation based on intact deformability modulus (𝐸𝑖) performs well in strong-excellent quality rock masses, while the equations based on 𝐸𝑖 and rock quality designation (𝑅QD) are found to be appropriate for weak-fair to excellent rock masses. Finally, a new set of equations appropriate for different rock mass types have been proposed through regression analysis along with appropriate design measures to be adopted.
Cognitive impairment in cerebral small vessel disease induced by hypertension
Authors: Wei Weipeng , Ma Denglei , Li Lin , Zhang Lan
Published: September 2023

Hypertension is a primary risk factor for the progression of cognitive impairment caused by cerebral small vessel disease, the most common cerebrovascular disease. However, the causal relationship between hypertension and cerebral small vessel disease remains unclear. Hypertension has substantial negative impacts on brain health and is recognized as a risk factor for cerebrovascular disease. Chronic hypertension and lifestyle factors are associated with risks for stroke and dementia, and cerebral small vessel disease can cause dementia and stroke. Hypertension is the main driver of cerebral small vessel disease, which changes the structure and function of cerebral vessels via various mechanisms and leads to lacunar infarction, leukoaraiosis, white matter lesions, and intracerebral hemorrhage, ultimately resulting in cognitive decline and demonstrating that the brain is the target organ of hypertension. This review updates our understanding of the pathogenesis of hypertension-induced cerebral small vessel disease and the resulting changes in brain structure and function and declines in cognitive ability. We also discuss drugs to treat cerebral small vessel disease and cognitive impairment.
Microglial response to aging and neuroinflammation in the development of neurodegenerative diseases
Authors: Han Tingting , Xu Yuxiang , Sun Lin , Hashimoto Makoto , Wei Jianshe
Published: September 2023

Cellular senescence and chronic inflammation in response to aging are considered to be indicators of brain aging; they have a great impact on the aging process and are the main risk factors for neurodegeneration. Reviewing the microglial response to aging and neuroinflammation in neurodegenerative diseases will help understand the importance of microglia in neurodegenerative diseases. This review describes the origin and function of microglia and focuses on the role of different states of the microglial response to aging and chronic inflammation on the occurrence and development of neurodegenerative diseases, including Alzheimer’s disease, Huntington’s chorea, and Parkinson’s disease. This review also describes the potential benefits of treating neurodegenerative diseases by modulating changes in microglial states. Therefore, inducing a shift from the neurotoxic to neuroprotective microglial state in neurodegenerative diseases induced by aging and chronic inflammation holds promise for the treatment of neurodegenerative diseases in the future.
Design of a Shell to Protect Sensors and Drones
Authors: Hei Tjan Ling , Kulshrestha Mehasvi , Randhawa Princy
Published: September 2023

This paper presents a novel protective shell system designed to safeguard both the drone and its accompanying sensors. The objective of this project is to develop and test the shell-shaped container to check its capability of securely housing the drone. The system may incorporate a circuit board housing a processor that receives data from sensors and controls the opening and closing motions of the container. By analyzing the sensor information, the system may intelligently respond to adverse weather conditions by automatically closing the container to ensure the drone’s protection. This innovative solution addresses the challenges associated with deploying drones in outdoor environments and offers enhanced safety and durability for extended drone operations.
Potencial de espécies arbóreas nativas para fitorremediação sob solos de cerrado: revisão bibliográfica
Authors: Franca Roberta Sorhaia Samayara Sousa Rocha de , Miranda Elka Élice Vasco de , Paim Guilherme Willkomm
Published: September 2023

O Cerrado é um dos biomas mais importantes do país. O avanço das fronteiras agrícolas em suas áreas tem causado, além da diminuição da vegetação nativa, a contaminação do solo através da má utilização de fertilizantes, herbicidas e pesticidas. O uso de plantas e sua microbiota associada para extrair ou reduzir a toxicidade de contaminantes no solo ou na água é denominado fitorremediação. Essa técnica é considerada não destrutiva e ecologicamente correta, além de ser social e economicamente aceita para a remediação de solos contaminados. Assim, objetivou-se com este trabalho, por meio de revisão bibliográfica, relatar e relacionar estudos utilizando espécies arbóreas nativas do Cerrado com potencial para fitorremediação de metais poluentes.
Territorialidades entre grupos sociais não hegemônicos e as formas tradicionais de organização político-estatal no município de Mirabela – MG
Authors: Silva Amanda Maria Soares , Silva Cássio Alexandre da
Published: September 2023

O artigo aborda as territorialidades entre grupos sociais não hegemônicos e as formas tradicionais de organização político-estatal no município de Mirabela – MG. A análise teórica é norteada a partir das espacialidades, com ênfase na categoria território, resultado dos “entrelaçamentos” de processos históricos, da base material e social das dinamicidades humanas locais e regionais. O caminho metodológico utilizado consistiu em pesquisa bibliográfica, trabalho de campo com o apoio da pesquisa-participante como insrtrumento de coleta de dados a entrevista semiestruturada. A investigação apresenta-se dentro do contexto da entrada das empresas de monocultura de eucalipto no Norte de Minas na década de 1960 nos processos de conformação dos territórios às premissas dessas corporações empresarias, com auxílio da máquina estatal e seus subsídios. O território como categoria, em suas multidimensionalidades, sujeito-relação-espaço, delimitado no campo de conflitualidade e disputa pelo “poder”, tanto material como imaterial. As concepções, político-jurídicas, econômicas e culturais, e às territorialidades são presentes cotidianamente no município de Mirabela. Nessa perspectiva geográfica o território apresenta diferentes nuances, seja, pelos processos geográficos de Territorialização, Desterritorialização e Reterritorialização que são erguidos e reconstruídos conforme a relação de grupos para com seus devidos territórios. As relações de poder entre os raizeiros e as empresas de monocultura de eucalipto conjugam determinados significados ao espaço e território, consolidam sentidos, noções que legitimam ações de cunho sociais por políticas.
Entre diferenciação e desigualdades socioespaciais: a percepção dos moradores da Zona Sul de Poços de Caldas (MG)
Authors: Silva Eduardo de Araujo da , Francisco Pedro Gabriel de Paiva
Published: September 2023

A estrutura espacial urbana brasileira é marcada por expressivas diferenciações e desigualdades socioespaciais. As diferenças e injustiças espaciais podem ser vistas na maioria das cidades do território nacional, sendo, em algumas localizações desigualdades expressivas, em outras, mais sutis. Nosso objetivo com este estudo foi analisar a percepção das diferenças e desigualdades de Poços de Caldas (MG), por meio de relatos dos moradores da Zona Sul da cidade. Para tanto, utilizou-se dos seguintes procedimentos metodológicos: (i) levantamento bibliográfico do tema “diferenciação e desigualdades socioespaciais”, a partir de textos de Geografia urbana; (ii) revisão bibliográfica acerca da (re)produção do espaço urbano da Zona Sul de Poços de Caldas; (iii) trabalhos de campo com registro de fotografias e descrições; (iv) entrevistas semiestruturadas com moradores da Zona Sul. Por meio das entrevistas, os citadinos relataram que há diversos fatores que impactam a vida urbana local, como: a distância entre o setor urbano sul e o restante do tecido urbano; a ineficiência do sistema de transporte coletivo; certa insegurança urbana; a ausência de algumas infraestruturas; a falta de conservação de determinados espaços públicos. Em suma, observou-se que a percepção dos próprios moradores traz importantíssimos elementos para entender o espaço urbano local e, com efeito, os respondentes percebem as diferenças e desigualdades socioespaciais da/na cidade.
Nghiên cứu đặc điểm lâm sàng, cận lâm sàng và kết cục thai kỳ của các trường hợp nhau tiền đạo ở Khoa Phụ sản, Bệnh viện Trường Đại học Y - Dược Huế
Authors: Trương Thị Linh Giang , Trần Thị Mỹ Chi
Published: September 2023

Mục tiêu: Mô tả đặc điểm lâm sàng, cận lâm sàng và đánh giá kết cục thai kỳ các trường hợp nhau tiền đạo tại Khoa Phụ sản, Bệnh viện Trường Đại học Y - Dược Huế.   

Đối tượng và phương pháp nghiên cứu: Những sản phụ được chẩn đoán xác định nhau tiền đạo bằng siêu âm trước sinh và xác nhận chẩn đoán sau sinh hoặc chẩn đoán nhau tiền đạo sau sinh. Phương pháp nghiên cứu mô tả hoàng loạt ca.

Kết quả: Nhau tiền đạo gặp nhiều nhất ở sản phụ có nhóm tuổi từ 35 tuổi trở lên chiếm tỷ lệ 46,9%. Sản phụ có tiền sử mang thai từ 2 lần trở lên chiếm tỷ lệ 65,6%. Đặc điểm lâm sàng: ra máu âm đạo chiếm 65,6%; ngôi bất thường chiếm 15,6%. Nhau tiền đạo trung tâm chiếm 59,4%. Tỷ lệ mổ lấy thai chiếm 93,8%. Tuổi thai chấm dứt thai kỳ trung bình là 37,25 tuần. Thời gian nằm viện trung bình 12,19 ngày.

Kết luận: Chảy máu âm đạo là triệu chứng phổ biến của nhau tiền đạo. Tuổi thai chấm dứt thai kỳ > 37 tuần làm giảm biến chứng cho trẻ sơ sinh.
The Responsibility Of The National Land Agency For The Issuance Of Certificate Breakdown Whose Parent Certificate Has Not Been Split
Authors: Nurfadila Altina Intan , Tjempaka Tjempaka
Published: September 2023

Multiple certificates, namely a plot of land that has more than one certificate, causing legal uncertainty for holders of land rights which is highly undesirable in land registration in Indonesia. The purpose of this study, among other things, is to find out and analyze the responsibility of the National Land Agency when it was discovered that there were multiple certificates based on Decree Number: 177/Pdt.G/2022/PN Tjk. The research method uses a normative and empirical juridical approach. This case of multiple certificates can occur because the main certificate has not been mapped, so when an online check is carried out through an application it cannot be read, resulting in the re-creation of the certificate either partially or wholly on the same land by another party. If there are several certificates, the responsibility of the National Land Agency is to assist in mediation between certificate holders. If it cannot be resolved through mediation, the National Land Agency will help direct it to a settlement in the District Court or State Administrative Court because it is the State Administrative Court or District Court that can decide whether or not the certificate is cancelled.
PHENOTYPIC VARIABILITY EVALUATION OF WHEAT VARIETIES FROM THE SUCEAVA GENE BANK COLLECTION
Authors: SARBU Tiberiu Emilian , GABUR Iulian , SIMIONIUC Danut Petru , PLACINTA Daniela Domnica , MURARIU danela , SIMIONIUC Violeta
Published: September 2023

The intensity of selection, inadvertent pathways of domestication, and the influence of climate change collectively amplify the frequency of detrimental alleles. This phenomenon, in turn, triggers genetic drift, leading to an in-advertent decline in the diversity of plant genetic resources. Genetic variability is of utmost importance for a species’ adaptability and overall fitness. Our investigation centres on Triticum germplasm within the agroclimatic conditions of the Suceava Gene Bank, encompassing 2021–2022 field trials. Comprehensive morphophysiological characterisation was conducted across 200 cultivated varieties, spanning three Triticum species (T. aestivum, T. turgidum and T. monococcum). Initially, the data underwent meticulous processing involving the computation of amplitude of variation, variance (s2), standard deviation (√s), and coefficients of variation (s%) for three pivotal agronomical traits: plant height, spikelets per spike, and total seeds per spike. Furthermore, an extensive cluster analysis was performed, encompassing multiple vital plant descriptors. The findings unveiled a remarkable dispersion of data, with standard deviation, amplitude of variation, and coefficient of variation collectively indicating substantial variability among the cultivated varieties. Within the same population, an intriguing observation emerged; of the 200 genotypes analysed, 83 exhibited immunity to Septoria tritici. Delving deeper into the statistical analysis, we identified two primary clusters within the population. Overall, a significant proportion of this germplasm showcased elevated phenotype scores, rendering them well-suited for further exploration as foundational material in pre-breeding initiatives.
Food Sector Stock Investment Portfolio Optimization using Mean-Expected Shortfall Model with Particle Swarm Optimization
Authors: Tampubolon Carlos Naek Tua , Subartini Betty , Sukono Sukono
Published: September 2023

One of the most promising investment products is stocks. Stocks have great profit potential, but the risks associated with this investment should not be ignored by investors. Therefore, an optimal investment strategy is needed by forming an investment portfolio, in order to minimize risk and maximize profits that can be obtained. This study aims to optimize the investment portfolio. The method used in this research is based on the Mean-Expected Shortfall (Mean-ES) model. The use of this method is expected that investors can get a more accurate picture of the level of risk associated with their stock portfolio. In addition, Particle Swarm Optimization (PSO) can also be used to optimize the allocation of funds in a stock portfolio.Â  Applying PSO, investors can find the optimal combination of fund allocation to achieve a high level of return. Based on the results of the analysis conducted on the following five stocks AALI, BISI, DSNG, LSIP and SMAR, the results show a risk level of 0.0014 and a return level of 0.021%.Â  Thus, investors can form a stock portfolio that has a high potential return, while minimizing the risks associated with stock investment. The implementation of this optimal investment strategy can assist investors in achieving their financial goals in a more effective manner.Â  Considering the potential returns and risks involved, investors can make wiser investment decisions and optimize the performance of their stock portfolio.
ALUCINANTES CUENTOS AMAZÓNICOS
Authors: Gómez Landeo Ángel Héctor , Pacheco Dávila Elizabeth
Published: September 2023

PRESENTACIÓN
En este libro encontraremos una variada selección de cuentos amazónicos, basados principalmente en personajes mitológicos de nuestra vasta e inconmensurable selva. Además de ser un documento valioso por recoger a algunos de los autores más importantes de la Amazonía, lo es también porque la edición es bilingüe y porque al final de cada cuento, hay un cuestionario elaborado y una diversidad de actividades, que promueven desarrollar y fortalecer el pensamiento crítico y reflexivo de los lectores, quienes con la práctica adecuada incrementarán su vocabulario, mejorarán en la comprensión y aplicación de las estructuras gramaticales, mejorando la competencia comunicativa y lingüística.
Cabe resaltar entre sus objetivos principales está enfocado al fortalecimiento del hábito lector en los pueblos de la Amazonía, con la inclusión del aprendizaje del inglés, propuesta que resulta sumamente interesante y genuina, dado a que se está tomando en cuenta los textos regionales, con contenido que rescatan el folclore, la identidad y el valor ancestral de nuestras costumbres.
Desfilan en las páginas de este libro, diferentes autores amazónicos: Ruth Angulo de Saldaña, Juan Sánchez Pacheco, Juan López Ruíz, Grower Cabello Caballero y Welmer Cárdenas Díaz.
Honouring Our Strengths - Moving Forward
Authors: Gorringe Scott
Published: September 2023

Persistent perceptions of deficit and conflict have characterised and constrained the history of relations between Aboriginal and non-Aboriginal Australians since contact. The success of their saturation is apparent in a continuing approach that presents the response to Aboriginal needs in terms of health and education 'gaps‘; 'the Aboriginal problem‘, 'mainstreaming (making them more like us)‘ or 'interventions‘ (and all the lack of ability that such a word implies).

Language in programs and the underlying approach to address very real health, economic and social need continues to carry (and replicate) an implicit assumption of deficit and a positioning of the locus of control away from Aboriginal people (i.e. service 'delivery‘ instead of service 'access‘).

This paper recognises that an erosive mindset of deficit perceptions of Aboriginality is also being widely adopted by Aboriginal people by ourselves and other Aboriginal people – that if un-discussed will continue to impact on the Aboriginal struggle. This paper will unpack an Aboriginal framework (Engoori) that can reconnect people and reignite authentic community engagement discussions.
FORMATION OF SPIRITUAL AND MORAL VALUES AMONG UNIVERSITY STUDENTS
Authors: Karavaeva Svetlana A.
Published: September 2023

In the context of a decrease in the level of personality culture in a post-industrial society, the problem of the formation of spiritual and moral values in the younger generation is becoming increasingly important. The essence of such concepts as spirituality, morality, spiritual and moral values is considered. The ways and conditions for the formation of spiritual and moral values among students are determined.
The Diversity of Knowledge Concerning Geographical Areas Based on Surveys Conducted in Institutions of Primary Education in Hungary
Authors: Lupfer-Juhász Eszter
Published: September 2023

My study will discuss the Hungarian public education system, more specifically, the knowledge about and the measurement of the concept of geographical areas as they appear in the subject Hon- és népismeret [approximately: Our Homeland and Its People(s)] in the Hungarian primary education system. The cultural landscape formed by human activity is an important part of Hon- és népismeret education, which also includes knowledge of spatiality, ethnographic geographical areas and maps.
In my research, I was interested what students taking Hon- és népismeret courses think and know about geographical areas; moreover, if they can use maps and place major Hungarian and ethnographic geographical areas (provinces) on blind maps. In my search, I have conducted a survey among students learning Hon- és népismeret in primary schools in Debrecen with the aim of measuring their knowledge of geographical areas and ethnographic geographical areas, especially related to the use of maps. So, in my study, I present all the tasks of the survey and the students’ answers. Furthermore, I describe the method used during the survey and the data processing.
Brauchtumspflege als Zukunftsperspektive?
Authors: Kasten Tilman
Published: September 2023

Diversität ist ein zentrales Stichwort unserer Zeit, das Einzug in die wissenschaftliche Auseinandersetzung mit (historischen) Migrationsphänomenen und deren Folgen gehalten hat. Dies gilt auch für die Geschichte der Zwangsmigration der deutschsprachigen Bevölkerung aus dem östlichen Europa infolge des Zweiten Weltkriegs, welche die sog. Heimatvertriebenen und die „Aufnahmegesellschaften“ vor große, u.a. die „Integration“ betreffende Herausforderungen stellte. Ausgehend von einer kritischen Lektüre eines geschichtswissenschaftlich fundierten Debattenbeitrags zur Bewertung der Integrationsgeschichte der deutschen Vertriebenen in der Bundesrepublik Deutschland reflektiert der Artikel die Frage, inwiefern sich aus dieser Geschichte Orientierungspunkte für aktuelle Debatten über ein gesellschaftliches Selbstverständnis im Zeichen von Diversität ableiten lassen.
Impact of Covid 19 on Stock Market and Exchange Rate in Nigeria
Authors: Bala-Keffi Ladi. R , Oboh Victor. U , Imam Shamsuddeen. Z , Vanni Eguolo. M , Bikefe Grace. G , Okoronkwo Chinecherem. D , Joshua Adams. N , Yusuf Danjuma.S.
Published: September 2023

The study investigates the impact of COVID–19 on the stock market and exchange rate in Nigeria. To achieve this objective, the impulse response function of the Toda-Yamamoto model (TY Model), and the variance decomposition were applied to all-share index, exchange rate, oil prices and Covid-19 cases. The impulse response function reveals that all-share index and exchange rate respond negatively to COVID-19 shocks. More so, the forecast variance decomposition revealed that the impact of COVID-19 pandemic on stock market was minimal. In general, the study found evidence of poor performance in the stock market and depreciation of exchange rate due to fall in oil prices. The study recommends effective exchange rate management during periods of crisis, and the diversification of the economy to broaden export base to mitigate the effect of exchange rate changes on the stock market and other sectors of the economy.
SUBSTÂNCIAS CONSOLIDADAS PARA BIOESTIMULADORES DE COLÁGENO: FORMA DE AÇÃO, INDICAÇÃO E INTERCORRÊNCIA- REVISÃO LITERÁRIA
Authors: Rodrigues Salgado Benedito Mayara , Santos Pozzi Fernanda , Oliveira Bernadino da Silva Larissa
Published: September 2023

Os bioestimuladores de colágeno são uma ótima opção no tratamento para o rejuvenescimento facial, visto sua capacidade de estimular a formação de um novo colágeno através de processo inflamatório local. O PLLA não possui um efeito imediato, já a CaHA assim que injetado provoca uma correção imediata, tendo a dissipação do seu gel carreador de forma mais lenta que no PLLA, mas ambos tem seu efeito alcançado de forma progressiva e gradual. Há uma grande diferença entre os produtos com relação à longevidade dos efeitos. A hidroxiapatita de cálcio, e o ácido poli-L-láctico são considerados biodegradáveis e semi permanentes, tendo a CaHA o menor tempo de duração quando comparada ao PLLA , em média de 12 a 18 meses, podendo chegar até 24 meses. Já o ácido poli-L-láctico apresenta efeitos mais duráveis, de até 4 anos sem necessidade de retoques. As complicações sistêmicas são mais raras, porém existe a possibilidade de nódulos não inflamatórios, pápulas, granulomas, celulite e necrose.
A Review on Digital Twins Technology: A New Frontier in Agriculture
Authors: Dawn Nabarun , Ghosh Souptik , Saha Aloke , Chatterjee Soumya , Ghosh Tania , Guha Sagnik , Sarkar Subhajit , Mukherjee Pronoy , Sanyal Tanmay
Published: September 2023

Farming is crucial for various aspects of daily life, including food, the economy, environment, culture, and community. It provides employment opportunities, generates income, and increases the export of agricultural products, particularly in rural areas. Sustainable farming practices promote soil health, biodiversity, and ecosystem services and are essential in many parts of the world. Farming is deeply rooted in cultures and traditions and is a way of life for many communities, passed down from generation to generation. Without farming, we would not have the abundance and variety of food that we enjoy today. Advancements in technology, such as artificial intelligence, machine learning, and the Internet of Things, have greatly impacted agriculture by producing vast amounts of digital data on crops, soil, and weather conditions. However, managing and analyzing these data can be challenging for farmers, especially those in developing nations. To address this issue, affordable digital farming solutions, including open-source software platforms, sensor networks, and mobile apps, are being developed to help farmers optimize their resources, increase yields, and profits. Digital twin technology can play a crucial role in digital farming by providing farmers with a virtual replica of their physical farm. It is a digital depiction of a real-world asset, such a farm or a particular crop field, that gathers information from sensors, weather stations, and satellite pictures. This technology has arisen that has been hailed as revolutionary in a number of fields, including manufacturing machines, construction, agriculture, healthcare, and the automotive and aerospace industries. However, the technology is still in its early stages in agriculture, and it can be challenging to handle the interactions between different farming-related digital twin components. Additionally, digital twinning can require significant investment in technology and infrastructure, which may be a barrier for small-scale farmers.
 
Received: 31 March 2023 | Revised: 18 July 2023 | Accepted: 8 August 2023
 
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
 
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
 
Author Contribution Statement
Nabarun Dawn: Conceptualization, Writing - original draft. Souptik Ghosh: Conceptualization, Writing - original draft. Aloke Saha: Methodology, Resources, Writing - original draft, Writing - review & editing, Visualization. Soumya Chatterjee: Writing - review & editing. Tania Ghosh: Writing - original draft. Sagnik Guha: Writing - original draft. Subhajit Sarkar: Writing - original draft. Pronoy Mukherjee: Writing - original draft. Tanmay Sanyal: Conceptualization, Supervision.
Random Forest Ensemble Machine Learning Model for Early Detection and Prediction of Weight Category
Authors: Ayua Samuel Iorhemen
Published: September 2023

The number of insurgents in our nation today is significantly rising each day, and the majority of those affected are living as internally displaced persons (IDP) in various IDP camps. These people experience a variety of health problems as a result of numerous factors. Due to financial difficulties and a lack of accessibility to healthcare facilities and medical professionals, these health risk factors may occasionally go undetected for long periods. BMI excesses, such as those in the underweight, overweight, and obese categories, are linked to several health issues, including low birth weight, poor quality of life, diabetes mellitus, cardiovascular diseases, and higher mortality. In the context of this paper, identifying the health status of IDPs depends critically on human body weight. Considering people living in IDP camps, early detection of the weight categories like underweight, overweight, and obese people is crucial because if not, they will be an early death or other health complications. To reduce mortality rates and other health complications that may result from improper and lately identifying underweight, overweight, and obese members in IDP camps, the researcher collected datasets from the IDP camps, trained, and developed a random forest (RF) ensemble model of supervised learning that will aids the medical practitioner in early detection and prediction of the weight category of IDPs. After hyper-parameter tuning and feature selection, the RF machine learning algorithms identify three significant parameters from the dataset's original 10 parameters to use as the model parameter. The highest accuracy obtained was 92% on the test dataset and 96% on the training dataset for the RF classifier using three features, while the accuracy of 83% was obtained on the test dataset and 87% on the training dataset for the RF classifier using ten features.
 
Received: 30 May 2023 | Revised: 1 August 2023 | Accepted: 25 September 2023
 
Conflicts of Interest
The author declares that he has no conflicts of interest to this work.
 
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
 
Author Contribution Statement
Samuel Iorhemen Ayua: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.