bluuebunny/crossref_metadata_2025 huggingface dataset:
Blockchain Based Decentralized Healthcare Network to Share Electronic Medical Records
Authors: Iyer Anoushka
Published: February 2024

Over 172 ransomware attacks on US healthcare organizations since 2016 have cost over $157 million total and disrupted care for over 70% of patients impacted, prompting healthcare CIOs to declare cyberattacks as one of the most devastating healthcare issues today. Furthermore, lack of interoperability of patient data between healthcare providers prevents patients from exploring care outside their provider’s network. Though hospitals utilize electronic health records (EHR), data formats remain fragmented and non-interoperable, leaving patients to be responsible for transporting their own data between providers or insurance plans. Permissioned blockchain technology can solve both these issues due to its inherent transparency, immutability and data sharing capabilities. Therefore, I developed a decentralized application called HyperEHRbase that would allow patients to control their own health records and share them with different healthcare providers. My application extends an open-source OpenEHR implementation called ehrbase. Unlike ehrbase, my application writes health records into a Hyperledger blockchain, not a centralized database. The blockchain network is designed to work as a decentralized healthcare network, allowing patients and healthcare providers to mutually exchange data. Patients can register to the healthcare network using their personal devices and voluntarily grant multiple healthcare providers access to their medical records. Doctors and other care providers can also register to the network and access information shared by patients. This system secures electronic healthcare records in an immutable blockchain and makes them interoperable using the OpenEHR standard. Patients will also have control over their data, which is a significant improvement over the current healthcare system.
Exploring the Influence of East Asian Culture Tendencies to Judge Others Based on Familial Factors
Authors: Kim Hidan , Song EunHye
Published: February 2024

This study aimed to explore the influence of familial factors on prejudice among East Asians, considering the ambiguous impact of Confucian collectivism. To achieve this, a literature review was conducted to examine previous research on prejudice and its association with familial factors. The study employed the Implicit Bias Test and collected data from a voluntary sample of 33 East Asian individuals. The results of a logistical regression test (p=4.31 e -0.5) demonstrated that the participants placed considerable importance on familial factors: parental income, parental occupational prestige, and parental education.  These findings indicate a significant influence of familial qualities in the judgments made by East Asians. However, further investigation is necessary to understand the specific role of Confucian culture in shaping these dynamics (Rsq =0.532). Overall, this study contributes to the existing literature and highlights the need for additional research to fully comprehend the complex interplay between familial factors, prejudice, and cultural influences among East Asians.
An Examination of the Representation of the Autistic Community in Film
Authors: Diaz Raquel , Olivo Daniel , Ciliento Kayla
Published: February 2024

Autism spectrum disorder (ASD) is a life-long neurodevelopmental  disorder where individuals with a diagnosis have communication challenges and many restrictions within their everyday life. Being a disadvantaged community, they tend to face discrimination and stigmatization on social media associated with social withdrawal and lower mental health. Their representation in film may have similar effects yet rarely studied. This study uses a directed content analysis with codes derived from the DSM-5 test and Baker’s Autistic Formula in order to calculate frequencies, duration, and percentages of movies devoted to each stereotype or criterion. The results from this research reveal that although the film industry is being representative they may be over-using certain symptoms and using stereotypes that the autistic community may find offensive.
Melodic Melodies: Is That All There is to Music?
Authors: Leung Jessica , Daffre Carolina
Published: February 2024

Music has great benefits; music can improve mood which in turn enhances cognitive performance in the brain. The objective of this literature review is to see how musical induction, the process of using mood induction through music, can change affect. Affect is the emotional reactive response to stimuli. With time, affect can influence mood, becoming an emotional state that stays stagnant for a prolonged period of time. Positive affect and mood benefit cognitive performance in 4 domains: attention and processing speed, working memory, declarative memory, and executive function. Results from scientific journals, blogs, and journal articles were reviewed to [paraphrased + shortened research question]. Studies suggest that musical induction can induce positive affect, enhancing cognitive performance in memory, processing speed, and attention. Since music is prevalent in daily lives, understanding how brain functions benefit positively from musical induction is extremely important; these tools and knowledge will be beneficial in solving mental health issues and other crises.
Historical Policies, Biological Principles, and Causes of Pandemic of Tuberculosis in the U. S.
Authors: Zhu Zixi , Bonday Chase
Published: February 2024

The late 19th and early 20th centuries in the United States saw a boom in immigration, which brought with it the unintended consequence of disease transmission. Tuberculosis was one of the most lethal diseases at the time which had significant impacts on both the economy and society. The spread of tuberculosis was exacerbated by the poor sanitary conditions and overcrowded living conditions in urban areas. This paper analyzes the underlying causes of tuberculosis and their relationship to immigration policies and rapid urbanization, critically analyzing the impact of immigration policies, urban public policy challenges, the tuberculosis prevalence connection between Europe and the United States, and the role of medical advancements, hygiene practices, and government regulations in reducing US tuberculosis cases. The history of the spread of tuberculosis in the US can inform future strategies for establishing better disease preparedness and response systems.
A Review of Pedagogical Approaches for Improved Engagement and Learning Outcomes in Mathematics
Authors: Lee Junho , Paul Nicholas
Published: February 2024

The traditional, lecture-based teaching approach in mathematics education has tended towards being a more standardized and passive learning environment, often failing to cater to diverse learning styles and needs. The consequence of this approach is the lack of engagement and understanding among students, a phenomenon prevalent in many classrooms worldwide. Indeed, student disengagement and a lack of critical thinking skills in mathematics are major concerns. Innovative pedagogical methodologies, such as Inquiry-Based Learning (IBL), Collaborative Learning, and the Flipped Classroom Model, have emerged as potential remedies to this issue. Still, their implementation faces challenges related to teacher preparation, technology dependence, and individual motivation. Despite these challenges, these methods have demonstrated significant potential to improve student outcomes. Evidence suggests IBL fosters critical thinking, collaborative learning enhances interpersonal skills, and the flipped classroom approach promotes personalized instruction and increased engagement. Improvements in student test scores ranging from 5% to 30% have been reported across different studies employing these innovative teaching methods. These methods have profound effects despite minimal funding. Combining these strategies, tailored to cater to diverse student needs, can create an effective and efficient learning environment. It can foster a deeper understanding and enjoyment of mathematics, thereby stimulating greater engagement and overall improved learning outcomes.
Is All Publicity Good Publicity? A Sentiment Analysis of Media Regarding Concussions in the NFL and its Effects on Viewership
Authors: Barrera Sebastian , Olivo Daniel
Published: February 2024

With the increase in the rate of concussions within the National Football League (NFL), as well as an increase in studies finding the long-term effects of these concussions, there has been growing interest garnered by the media on the NFL’s concussion protocol. Other studies would suggest that these portrayals by the media, if negative, would impact the league's viewership; however, with no research done on the topic, this claim was unsupported. To determine this relationship, this study conducts a sentiment analysis using MeaningCloud Software on statements made within the years 2017 through 2021 regarding NFL concussions/concussion protocol, which was then compared to the average viewership of its corresponding season. Throughout the entirety of the years analyzed, MeaningCloud analyzed that 49 of the 99 statements about NFL concussions/concussion protocol were deemed to have negative polarity (49.5%), while only 24 had positive polarity (24.24%), conveying a very large disparity in the media coverage. These results disagreed with the current ideals that negative portrayals can impact enjoyment (therefore viewership), and could speak to the strength of the NFL’s business model.
Using Artificial Intelligence-Based Approach for Detecting Insects-Induced Grain Damage
Authors: Sharma Saanvi , Singh Chandra Bhan
Published: February 2024

According to the Intergovernmental Panel on Climate Change, around 30% of global food production is wasted each year. Prevention strategies during post-harvest grain storage may reduce food waste and help distribute food surpluses more fairly globally, ultimately reducing global hunger. Insect damage is a major cause of post-harvest storage losses, resulting in both quality and nutritional loss to the grain. Recently, data-driven approaches have been used to enhance proper and efficient storage. The aim of this project is to investigate how artificial intelligence (AI) can be used to detect insect-induced grain damage during storage. This project used barley grain to test the experimental hypothesis that insect-related damage during grain storage can be detected by simultaneous imaging and AI-based analysis. An AI approach was developed using Python to build a prediction model. Data was collected by acquiring images of insect-induced damaged and undamaged grain. The AI-based model was highly (90%) accurate in identifying the damage caused by the insect based on the parameters defined in the algorithm. In summary, this innovative approach allowed us to identify grain damage, which, in the future, will help take necessary intervention(s) to prevent insect-induced grain damage and ultimately prevent loss during post-harvest storage.
Assisted Species Migration of Joshua Trees
Authors: Dunn Renee , Larson Melinda
Published: February 2024

The Joshua tree evolved in a complex way with its environment, pollinator, and seed dispersers over millions of years. Its survival as a species is now imminently threatened by climate change. Many factors prevent it from migrating to a cooler range quickly enough to keep up with the planet’s current rate of warming. This paper explores the viability of assisted migration for the Joshua tree, where humans help it move to escape extinction.  Several studies are examined.  One persuasively shows that the Joshua tree had a range contraction when the climate warmed at the end of the Ice Age and that present warming will cause a similar, drastic range reduction. Other studies look at factors such as soil, CO2, pollinator mutualism, and seed longevity to determine if assisted migration would be successful. The ethics of assisted migration is also explored. This paper concludes that humans must try to assist the Joshua tree to migrate but that it will be difficult given the complexities of its evolution, its relationship to its environment, and a migration lag that is not completely understood.
Jean Piaget and His Studies on Cognitive Development and Contributions to the Field of Psychology
Authors: Saravanan Aishwaryalakshmi , Murphy Bernadette
Published: February 2024

This paper explores the life, accomplishments, and psychological contributions of Jean Piaget and how his findings impacted the field of psychology. It also dives into the criticisms he faced for his findings. Piaget was born as the son of a historian but decided to study abnormal psychology after being introduced to the concept of psychoanalysis. Piaget went on to study children and cognitive growth at different stages of childhood. He developed four stages of mental growth and explored what children can do during each stage. Piaget studied other concepts, such as object permanence and conservation of quantity, and explored the level of understanding of these concepts during each stage. This paper dissects many of the topics Piaget studied and analyzes criticisms against his work, raising the question of how he could have studied these topics better. It also emphasizes how Jean Piaget revolutionized the field of psychology through his discoveries and contributions relating to children and how they learn, demonstrating how Piaget’s theories can even be used during the 21st century to understand cognitive growth among children.
The Intersections of Artificial Intelligence, Brain Imaging Tools and Diagnostics for Neurodegenerative Diseases
Authors: Jayaraj Anish
Published: February 2024

This paper explores the fascinating topics of artificial intelligence (AI), brain imaging tools, and diagnostics for neurodegenerative diseases. By examining the advancements in AI algorithms and their integration with cutting-edge brain imaging technologies, this publication displays the potential of these approaches to revolutionize the diagnoses and understanding of neurodegenerative disorders. Through an analysis of recent studies, this paper highlights the significant progress made by utilizing AI-powered tools, enhancing the accuracy, efficiency, and early detection of conditions such as Alzheimer's, Parkinson's, and Huntington's diseases. Ultimately, this research underscores the transformative role that AI and brain imaging can play in the field of neurodegenerative disease diagnostics, paving the way for improved patient care and better outcomes.

In addition to exploring the current state of AI and brain imaging tools in neurodegenerative disease diagnostics, my paper also dives into the potential future applications and challenges in this rapidly evolving field. It discusses the ethics of AI-driven diagnostic methods, emphasizing the importance of ensuring patient privacy, informed consent, and equitable access to these technologies.
The Ethical Concerns of CRISPR Editing in Embryos
Authors: Pydipati Bavana
Published: February 2024

CRISPR is a tool in molecular biology with many far-reaching uses in medicine and research. Along with its well-known benefits for diagnostics and treatments, recent research has focused on how CRISPR can be used in gene editing in germline cells. This paper explicitly discusses and comments on the ethics of such genetic modifications and explores future solutions to resolve the ethical concerns of this field of research.
A török fegyveres erők külföldi jelenléte
Authors: Egeresi Zoltán
Published: February 2024

Az utóbbi években nemcsak Törökország külpolitikai, de katonai jelenléte is jelentős mértékben növekedett a vele szomszédos régiókban. A Török Fegyveres Erők (Türk Silahlı Kuvvetleri, TSK), összhangban a külpolitikai célkitűzésekkel, aktívan részt vesz a török befolyás terjesztésében. Ugyanígy a török védelmi ipar is jelentős fejlődésen ment keresztül, termékei megjelentek a nemzetközi és újabban a magyar piacon is. A tanulmány célja, hogy ismertesse Törökország külhoni katonai jelenlétének fejlődését az utóbbi évtizedek, de főleg a 2010-es évek elejétől fogva. Ennek érdekében felvázolja a külpolitika változását, különös tekintettel az AKP alatti folyamatokra, majd pedig kategorizálva mutatja be a külföldi katonai jelenlét különböző megnyilvánulásait.
Pakisztán a destabilizáció útján? Politikai és gazdasági válságjelenségek a dél-ázsiai államban
Authors: Csicsmann László
Published: February 2024

Pakisztán az elmúlt hónapokban az országban uralkodó politikai és gazdasági válság, valamint a növekvő radikalizálódás következtében a nemzetközi közösség figyelmébe került. 2022-ben a fegyveres erők megvonták a támogatást Imrán Khán kormányától, amely egy újabb alkotmányos válságba sodorta a dél-ázsiai államot. Az ország történetének egyik legnépszerűbb politikusát, az egykori krikettjátékost különféle vádakkal börtönbe zárták, és eltiltották a 2024. februári választásokon való indulástól. A mögötte álló politikai erő azonban képes milliókat mobilizálni, ahogy azt az elmúlt két évben láthattuk. Pakisztán gazdasága az összeomlás szélére került a politikai krízissel egyidőben. 2023 nyarán sikerült egy újabb IMF megállapodást kötni, amelynek előfeltétele megszorító intézkedések meghozatala, amely könnyen ronthat az életkörülményeken a 240 milliós országban. Továbbá az elmúlt két esztendő – összefüggésben a 2021-es kabuli tálib hatalomátvétellel – a radikalizáció újabb hullámát hozta el a dél-ázsiai országban. A kabuli tálib kormányzattal szoros kapcsolatokat ápoló pakisztáni tálib mozgalom, a TTP tehető felelőssé a 2022-ben és 2023-ban jelentkező jelentősebb terrorhullámért, amelyre válaszként Pakisztán az illegálisan az országban tartózkodó afgán menekültek kiutasításában találta meg a megoldást. Az elemzés a politikai és gazdasági válságjelenségek mellett a fokozódó radikalizálódás hátterét járja körbe.
Evaluasi Kualitas Portal E-lerning Universitas Mahakarya Asia Menggunakan Metode MCCALL
Authors: Salamudin Salamudin , Hartati Sri , Saputro Haris , Meilantika Dian
Published: February 2024

This research focuses on evaluating the quality of the e-learning system at Universitas Mahakarya Asia using the McCall Method. The study aims to provide insights into the performance of the online learning platform e-learning.unmaha.ac.id. Involving criteria such as correctness, reliability, efficiency, integrity, usability, and maintainability, the research yields an overall score of 79.6%. The evaluation results indicate high reliability and integrity but highlight areas for improvement in the correctness of information and ease of maintenance. Improvement recommendations are provided to enhance content accuracy and improve the user interface for a smoother experience. Special emphasis is given to improving maintainability for the sustainability of the platform. These findings lay the foundation for developing a more user-responsive e-learning system, reinforcing the role of Mahakarya Asia University in providing quality online education
Coping Mechanisms for Food Insecurity among Rural Households in Bitereko Sub-County, Mitooma District: Convergent Parallel Mixed-Methods Design
Authors: Ngabirano Augustino , Nabitandikwa Catherine , Neeza Timothy , Igwe Mathew Chibunna
Published: February 2024

Background: Food insecurity is a multifaceted global health concern, causing poor health in low- and middle-income countries, especially in rural sub-Saharan Africa. This study was done to assess causes of food insecurity, explore coping strategies and the effect of environmental factors and locally accessible resources on the food situation in Bitereko Sub-County, Mitooma district, Uganda Method: This article’s empirical analysis is predicated on data collected on thirty-two households from Bitereko Sub-County between September and October 2018 which were selected using stratified sampling technique. Focus group discussions, key informant interviews and a semi-structured questionnaire were used for data collection. Descriptive analysis was done using IBM SPSS version 20 while qualitative (thematic and content) analysis was conducted manually. Result: The study findings show that population increase and land degradation is the main cause of food shortage in the area. Banana was reported (100%) by both genders to be the major food crop relied upon by the households. Reducing the number of meals (40.62%) was the main coping strategy to food insecurity. Diversification into non-farm activities and agricultural diversification are two main livelihood adjustment strategies that have emerged in the area in relation to environmental factors and locally available resources. Conclusion: The study findings indicate that gender, age group and education level significantly influenced the food situation in a given household. Households whose heads were male were more likely to experience food insecurity as compared to the females χ2 (1, N = 32) = .002, p = .041. Households with respondents aged between 20 – 29 years were less likely to experience food insecurity than those aged between 30 – 39 years χ2 (5, N = 32) = 16.09, p = .007. Whereas respondents who had attained up to primary level of education were more likely to experience food insecurity in their households as compared to those who had never been to school χ2 (4, N = 32) = 15.71, p = .003.
PENERAPAN PENDIDIKAN KARAKTER MELALUI METODE PEMODELAN PADA SISWA KELAS IV SD NEGERI 63 REJANG LEBONG
Authors: Setiadi Setiadi
Published: February 2024

Penelitian ini dilakukan dengan metode penelitian tindakan kelas yang berlangsung selama 3 siklus. Subjek penelitian adalah siswa kelas IV SD Negeri 63 Rejang Lebong Tahun Pelajaran 2022/2023 sebanyak 25 orang. Waktu pelaksanaan pada bulan Januari sampai dengan Maret 2023 selama 3 bulan. Tempat pelaksanaan di SD Negeri 63 Rejang Lebong kecamatan Padang Ulak Tanding kabupaten Rejang Lebong. Alat pengumpulan data berupa lembar observasi dan lembar dokumentasi. Teknik analisis data dengan menggunakan analisis data observasi dan data dokumentasi. Hasil penelitian Pelaksanaan pendidikan karakter tidak berdiri sendiri sebagai mata pelajaran, tetapi menyatu dan terintegrasi dengan mata pelajaran yang ada di sekolah. Penerapan pendidikan karakter melalui pemodelan di SDN 63 Rejang Lebong dapat meningkatkan pemahaman siswa, hal ini dapat dilihat dari skor Pengamatan terhadap pelaksanaan pendidikan karakter skor rata-rata pada siklus I sebesar 1,78 atau baru mencapai 46%, siklus II meningkat menjadi 2,7 atau sebesar 67,5% dan siklus III mencapai skor 3,5 atau sebesar 87,5%.
IMPLEMENTASI SISTEM PENILAIAN KURIKULUM 2013 MELALUI KEGIATAN IN HOUSE TRAINING UNTUK MENINGKATKAN PEMAHAMN GURU-GURU DI SD NEGERI 66 REJANG LEBONG
Authors: Winarto Eko
Published: February 2024

Desain penelitian ini adalah penelitian tindakan sekolah (action research). Subjek dalam penelitian ini adalah guru kelas dan guru bidang studi di SD Negeri 66 Rejang Lebong pada tahun pelajaran 2022/2023. Waktu pelaksanaan penelitian dimulai pada bulan Januari sampai dengan Maret 2023 selama 3 bulan. Tahap penelitian yang dilakukan dalam penelitian ini adalah melalui kegiatan perencanaan, pelaksanaan, observasi dan refleksi. Teknik pengumpulan data melalui data observasi dan data tes. Hasil penelitian Melalui pelaksanaan pelatihan model in house training dapat meningkatkan keaktifan peserta pelatihan penilaian kurikulum 2013 di SD Negeri 66 Rejang Lebong, hal ini terlihat pada siklus I keaktifan sebesar 60% meningkat pada siklus II sebesar 93%. Melalui pelaksanaan pelatihan model in house training dapat meningkatkan pemahaman guru dalam penilaian kurikulum 2013, dimana pada siklus I kemampuan guru sebesar 33% meningkat pada siklus II sebesar 97%.
PENINGKATAN KUALITAS PEMBELAJARAN MELALUI SUPERVISI KUNJUNGAN KELAS DAN PENDAMPINGAN DI SD NEGERI 42 REJANG LEBONG
Authors: Susilawati Susilawati
Published: February 2024

Penelititian ini adalah penelitian tindakan sekolah. Subjek dalam penelitian ini adalah guru baik guru kelas maupun guru bidang studi di SD Negeri 42 Rejang Lebong yang berjumlah 7 orang. Waktu pelaksanaan dimulai pada bulan Januari sampai dengan Juni 2022. Teknik pengumpulan data melalui data observasi dan data angket. Hasil penelitian supervisi kunjungan kelas dengan pendampingan dapat meningkatkan kualitas perencanaan pembelajaran, hal ini terlihat pada rata-rata pencapaian komponen persiapan pembelajaran siklus I meningkat pada siklus II secara signifikan bahwa dalam menentukan tujuan pembelajaran. Supervisi kunjungan kelas dengan pedampingan dapat meningkatkan kualitas pelaksanaan pembelajaran dimana terjadi peningkatan yang cukup baik terhadap pelaksanaan pembelajaran siklus II yaitu pada komponen pelaksanaan pembelajaran di siklus I dipeoleh rerata skor 7,4 atau sebesar 74% mengalami peningkatan pada siklus II dengan rerata 8,7 atau 87%. Kegiatan membuka pembelajaran rerata skor 7,3 atau 73% meningkat menjadi rerata 9,1 atau 91%. Penilaian pembelajaran inti memiliki skor 8,7 atau sebesar 72,5% mengalami peningkatan menjadi rerata 10,6 atau sebesar 88,3%. Sedangkan pada kegiatan penutup rerata skor 7,7 atau sebesar 77%. Meningkat menjadi rerata 8,9 atau sebesar 89%.
PENINGKATAN KOMPETENSI GURU MELALUI DISKUSI KELOMPOK PENYUSUNAN BAHAN AJAR DI SD NEGERI 32 REJANG LEBONG
Authors: Herawati Lili
Published: February 2024

Menyusun bahar ajar merupakan salah satu kompetensi penting yang harus dimiliki oleh semua guru, terlebih guru-guru yang telah mendapatkan sertifikasi. Namun realita di lapangan di SD negeri 32 Rejang Lebong, kemampuan guru dalam menyusun bahar ajar sangat rendah dan perlu ditingkatkan. Penelitan ini dilaksanakan dengan tujuan untuk meningkatkan kompetensi pedagogic guru, khususnya dalam menyusun bahan ajar melalui diskusi kelompok yang dilakukan oleh Kepala Sekolah. Penelitian ini dilakukan menggunakan maetode Penelitian Tindakan Sekolah atau PTS dengan total dua siklus. Berdasarkan penelitian yang dilakukan diperoleh hasil bahwa diskusi kelompok yang dilakukan oleh Kepala Sekolah selama dua siklus terbukti dapat meningkatkan kemampuan guru dalam menyusun bahan ajar di SD Negeri 32 Rejang Lebong. Adapun rincian hasilnnya ialah: 1) item kesesuaian tema dengan kompetensi dasar meningkat dari 72,85 menjadi 85; 2) item petunjuk penggunaan bahan ajar meningkat dari 75 menjadi 90; 3) item bahasa meningkat dari 60 menjadi 80; 4) itiem desain dan tampilan meningkat dai 69 menjadi 80; dan 5) item evaluasi meningkat dari 77 menjadi 90.
EFEITO DOS LÍQUIDOS MODELADORES NA SUPERFÍCIE DA RESINA COMPOSTA – UMA REVISÃO DE LITERATURA
Authors: Dias Samuel Silva , Lopes Matheus Fernando , Dias Jeffison Teles , Tanaka Caio Junji , Rodrigues Jose Augusto
Published: February 2024

O presente trabalho estudou os modeladores de resina composta e utilizados na odontologia contemporânea para facilitar o processo de escultura final nas restaurações de resina composta. Realizou-se uma revisão da literatura, consultando bases de dados, para compilar uma tabela comparativa que ilustra as diferenças e os estudos abordados. A seleção de artigos se restringiu a publicações em inglês, sem imposição de limite temporal. De um total de 228 títulos encontrados, 19 estavam relacionados à técnica, porém, somente 4 artigos foram considerados, pois tratavam exclusivamente de modeladores de resina composta. Esta revisão destacou possibilidades de alteração das propriedades mecânicas, ópticas e/ou superficiais das resinas compostas. No entanto, a aplicação de modeladores de resina composta tem demonstrado resultados variados a curto prazo, com impactos neutros ou positivos em alguns estudos e negativos em outros. Nota-se uma escassez evidências científicas na literatura que recomendem ou contraindiquem o uso dos modeladores. Dessa forma, não se contraindica o uso de modeladores, mas sugere-se que os clínicos que optem pela utilização de modeladores de resina composta também realizem um bom polimento da restauração e façam acompanhamento a longo prazo.
Espoir
Authors: Aguenier Lucas , Doyon Sabrina
Published: February 2024

Since the early 2000s, we have witnessed a new fascination with hope, both within the social sciences and anthropology, and in civil society and the political struggle. Associated with the idea of possibility, utopia and opening onto the future, hope has been proposed by a number of thinkers as a response to the growing uncertainty of our times. Under these conditions, hope becomes a call to aspire outside the ideological frameworks of the moment. In ethnographic works, this capacity to aspire to a different future is documented along axes of interrelated motivations, most notably a sense of impending crisis, commitment, activism or resistance, and a reflexive, historical and positioned subjectivity.
A Comparative Study of the Oxidation Behavior of Hot-Rolled Steel established from Medium and Thin Slabs oxidized in 20% H2O-N2 at 600-900°C
Authors: Singthanu Seksan , Nilsonthi Thanasak
Published: February 2024

This study focuses on the oxidation behavior of oxide scale on hot-rolled steel from a Thailand steel industry. Hot-rolled steel established from the medium and thin slabs was studied. The oxidation behavior was conducted in a horizontal furnace with 20%H2O-N2 to simulate steel oxidation during the hot rolling line. The scale was formed at a temperature range of 600-900°C for 30, 60, and 90 min. The scale morphology can be seen via Scanning Electron Microscope (SEM-EDS). The oxide phase was investigated via X-Ray Diffraction (XRD). The results show that iron oxides such as hematite (Fe2O3) and magnetite (Fe3O4) were produced on the studied steel. The oxidation behavior of the studied steel was followed by a parabolic law. The mass gain increased with increasing temperatures. The steel established from a medium slab exhibited a lower oxidation rate than the steel established from a thin slab. The reason for this could be the high amount of oxide containing silicon at the steel-scale interface, which promoted the oxidation resistance of the steel established from the medium slab. The influence of different slab types and its alloying elements was studied to comprehend the oxidation behavior. As a result, the alloying element in the hot-rolled steel was controlled in the design process.
Design and Implementation of an IoT-based automated EC and pH Control System in an NFT-based Hydroponic Farm
Authors: Jain Swati , Kaur Mandeep
Published: February 2024

In hydroponics, the growth of plants is primarily dependent on the precise configuration of the nutrient solution supplied to them. Continuous monitoring and control of the nutrients in the hydroponic tank is essential to maintain optimal growth requirements at all times. Manual monitoring and control of the system is inefficient, as it requires human intervention and can lead to errors and variations in the nutrients supplied. This study presents a system to automatically track pH, current nutrient, and water level in the tank and supply the exact amount of pH solution, nutrient solution, and water whenever needed. The proposed system, when integrated with IoT technology, can help achieve better control over the farm and higher productivity with a reduced amount of manual labor.
Analysis of a Compact Electrically Small Antenna with SRR for RFID Applications
Authors: Majji Naveen Kumar , Madhavareddy Venkata Narayana , Immadi Govardhani , Ambati Navya , Aovuthu Sree Madhuri
Published: February 2024

This paper contains the design and analysis of a compact, bidirectional Electrically Small Antenna (ESA) at 0.9 GHz for Radio Frequency Identification (RFID) and a global system for mobile communication applications. The proposed design consists of a microstrip patch antenna enclosed inside the split ring resonators, in which a split ring resonator was subtracted from the ground plane in order to obtain the results at lower frequencies by maintaining a compact size. This ESA was designed on FR4 substrate having a dimension of 30 mm × 30 mm × 1.6 mm. This antenna was created and simulated with the Ansys HFSS. The ESA was fabricated by chemical etching and it was measured with the MS2037C Anritsu Combinational Analyzer. The simulated results show that the ESA attains a bandwidth of 100 MHz (with S11 < -10 dB) at 0.9 GHz. The bidirectional radiation pattern in both H and E planes with a radiation efficiency of 80% at the resonant frequency was obtained. A close agreement of 90% between the simulated and the measured results was observed.
Solar Water Heating Systems: A Review on Contemporary Design and Emergent Technology using PCM for Increased Performance
Authors: Kchaou Mohamed
Published: February 2024

This study highlighted the specificity of solar water heating systems, investigating their financial benefits and discussing their economic advantages. Several studies have shown that solar water heaters' effective performance and the best cost savings were obtained during the hot seasons. New developments in solar water heaters have been discussed in detail. According to numerous researches, the highest quality performance of solar water heaters and the best cost savings were achieved when the system was integrated with innovative components such as Phase Change Materials (PCMs), heat pipes, and turbulators. Emergent technologies using PCMs have shown excellent results, increasing solar thermal efficiency. This technology presents great potential not only for domestic applications but also on an industrial scale.
An Experimental Study on the Performance Enhancement of a Heat Pump System using Nanofluids
Authors: Shewale Vinod , Kapse Arvind A. , Barahate Sanjay D. , Jadhav Santosh P. , Suryawanshi Satish J.
Published: February 2024

Heat pumps are frequently used for heating, cooling, and air conditioning. It is well known that nanoparticles can improve the coefficients of conduction and convection, increasing heat transfer along with other properties. The considered heat pump was loaded with R-134a. Titanium dioxide (TiO2) and aluminium oxide (Al2O3) were blended with clean water to create a nanoscale solution used to cool the heat pump condensers. A total of three TiO2 and Al2O3 proportions (0.1%, 0.2%, and 0.3%) were used. The study's findings showed that utilizing 0.3% Al2O3 instead of conventional clean water to cool the heat pump condenser boosted the coefficient of performance by 18% while reducing energy consumption by 26%.
The Potential of Landsat 8 OLI Images in Coastline Identification: The Case Study of Basra, Iraq
Authors: Tahir Hamzah , Din Ami Hassan Md.
Published: February 2024

Coastline extraction plays important functions in coastal resource management, natural resource preservation, and sustainable coastal development. Long-term records of Landsat data series are available for free downloading, being highly potential for coastline extraction. Furthermore, remote sensing imagery systems along with the application of digital image processing techniques can be utilized in coastline extraction. However, it is challenging to accurately extract coastlines with coarse spatial resolution due to the dynamic properties of various types of coastlines produced by sea-level changes from tides and storms. Moreover, the use of conventional surveys and the need for high-resolution images involve substantial costs and efforts, especially when coastlines of long distances are involved. The current study compared the accuracy of extracting coastlines from Landsat 8 OLI with the observed coastlines from GPS data. In particular, this study focused on distinguishing water areas from non-water areas on the coastline of a selected concrete port. The analysis involved the use of both MNDWI and NDWI indexes. The statistical results demonstrated the accuracy of MNDWI (RMSE of 2.363) and NDWI (RMSE of 2.491 m), which suggested the potential of using Landsat 8 OLI in coastline identification.
Voltage Control of a Three-Phase Distribution Grid using a DC Microgrid-Fed STATCOM
Authors: Khater Faeka M. , Elkady Zeinab , Amr Amany M. , Mansour Diaa-Eldin A. , El Gebaly Ahmed E.
Published: February 2024

With the increasing penetration of microgrids in distribution systems, the possibility for voltage variations increases. This paper proposes the use of a static synchronous compensator (STATCOM) fed by a DC microgrid to control the voltage of a 3-phase AC distribution grid and provide bidirectional active power transfer from the AC grid to the DC microgrid and vice versa. A simplified control is applied to this system to manage the magnitude and angle of the system voltage at the point of common coupling. With the use of a PI controller and pulse width modulation, the proposed control was able to modify the active and reactive power compensation. The control approach is characterized by its simplicity and rapid response to system changes, such as fault occurrences or load variations. The proposed control system is applied after converting the 3-phase system into a dq system to simplify the voltage regulation process. The PSCAD package is used to perform the simulation. Results demonstrate that it is possible to control STATCOM to offset reactive power and regulate grid voltage. The results validated the ability of active power transfer through the line by injecting negative and positive active power. The transfer of active and reactive power from the AC grid to the DC microgrid, and vice versa, is examined in this study following the STATCOM rating and the energy management demands.
Integral Backstepping Sliding Mode Control for Maximizing the Power Production of Wind Turbines
Authors: Abouri Habiba , El Guezar Fatima , Bouzahir Hassane , Chehaidia Seif Eddine , Vargas Alessandro N.
Published: February 2024

Wind turbine control has attracted increasing attention, driven in part by evolving challenges due to the growing size and complexity of wind turbines. Addressing these challenges and maximizing wind turbine power production requires the application of advanced nonlinear control methods. Sliding Mode Control (SMC) has emerged as a promising approach in this context. Recent studies have explored the integration of an integral term with SMC, called I-SMC. This technique has been shown to result in system responses that exhibit chattering phenomena with noticeable state errors. This study aimed to address these issues through the introduction of a novel controller known as Integral Backstepping SMC (IB-SMC). This study demonstrated that IBSMC not only ensured the stability of wind turbines but also outperformed other control strategies, even in the presence of disturbances of approximately 30% of the rated electromagnetic torque. To validate the effectiveness of the proposed controller, extensive simulation tests were carried out using MATLAB /Simulink software to evaluate the controller's responsiveness to rapid changes in conditions, as well as its robustness and overall performance. A comparison was carried out between the IBSMC and previous SMCs to evaluate their ability to reduce steady-state error and chattering.
An Improved Machine Learning Method by applying Cloud Forensic Meta-Model to Enhance the Data Collection Process in Cloud Environments
Authors: Al-mugern ٍRafef , Othman Siti Hajar , Al-Dhaqm Arafat
Published: February 2024

Cloud computing has revolutionized the way businesses operate by offering accuracy in Normalized Mutual Information (NMI). However, with the growing adoption of cloud services, ensuring the accuracy and validation of common processes through machine learning and clustering of these common concepts as well as of the processes generated by cloud forensics experts’ data in cloud environments has become a paramount concern. The current paper proposes an innovative approach to enhance the data collection procedure in cloud environments by applying a Cloud Forensic Meta-Model (CFMM) and integrating it with machine learning techniques to improve the cloud forensic data. Through this approach, consistency and compatibility across different cloud environments in terms of accuracy are ensured. This research contributes to the ongoing efforts to validate the clustering process for data collection in cloud computing environments and advance the field of cloud forensics for standardizing the representation of cloud forensic data, certifying NMI and accuracy across different cloud environments.
A Binary Object Detection Pattern Model to Assist the Visually Impaired in detecting Normal and Camouflaged Faces
Authors: Sajini S. , Pushpa B.
Published: February 2024

This study presents a novel Binary Object Detection Pattern Model (BODPM) to detect objects with face key points and recognize them using the KERAS dataset. The proximity and accuracy of the recognized items were evaluated using computer vision techniques. The object recognition time interval and duration were recorded and stored permanently in a database, and the information was communicated to the visually impaired user as voice output. The normal face, without wearing a mask, was identified using binary patterns with proximity detection. Camouflaged objects were detected in a maximum probability range of 100%. The proposed method was tested, calculating accuracy and score, and compared with existing models, showcasing remarkable performance. The proposed method of normal and camouflage detection is a novel prediction with proximity analysis of objects in a frame.
DPPNet: A Deformable-Perspective-Perception network for Safety Helmet Violation Detection
Authors: Alassaf Yahya , Said Yahia
Published: February 2024

The issue of worker safety at construction sites has become increasingly prominent within the construction industry. Safety helmet usage has been shown to reduce accidents among construction workers. However, there are instances when safety helmets are not consistently worn, which may be attributed to a variety of factors. Therefore, an automated system based on computer vision needs to be established to track protective gear appropriate usage. While there have been studies on helmet detection systems, there is a limited amount of research specifically addressing helmet detection. Also, various challenges need to be addressed such as small object miss-detection and occluded helmet detection. To fix these issues, a Deformable Perspective Perception Network (DPPNet) is proposed in this paper. Two modules make up the proposed DPPNet: Background/Image Spatial Fusion (BISF) and Grayscale Background Subtraction (GBS). While the BISF module utilizes channel attention to blend feature maps from a current frame and the background, the GBS submodule in particular incorporates background spatial information into a current frame. Additionally, the DPPNet facilitates occluded and small helmet detection. Excessive training and testing experiments have been performed using the Safety Helmet Wearing Detection (SHWD) Dataset. Experimental results demonstrate the effectiveness of the proposed DPPNet network. The obtained findings exhibit that the suggested module significantly enhances the detection capabilities of small objects. Effective mean average precision results have been obtained on the SHWD dataset coming up to 97.4% of mAP.
Machine Learning-assisted Prediction and Optimization of Exergy Efficiency and Destruction of Cumene Plant under Uncertainty
Authors: Ahmad Farooq , Ahmad Naveed , Al-Khazaal Abdul Aal Zuhayr
Published: February 2024

Machine Learning (ML)'s growing role in process industries during the digitalization era is notable. This study combines Artificial Neural Networks (ANNs) and Aspen Plus to predict exergy efficiency, exergy destruction, and potential improvements in a cumene plant under uncertain process conditions. An optimization framework, using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), was developed to enhance exergy efficiency amid uncertainty. Initially, a steady-state Aspen model evaluates exergy efficiency, irreversibility, and potential improvements. The proposed model is transitioned to a dynamic mode, introducing artificial uncertainties into key variables. An ANN model predicts exergy efficiency and exergy destruction under uncertainty. The PSO and GA-based optimization methods improve exergy efficiency and reduce exergy destruction. This work demonstrates the potential real-time application of intelligent methods in plant analysis.
The Innovative Role of Process Mining in building Face Re-identification Trajectory
Authors: Alharbi Amirah
Published: February 2024

Face recognition and tracking technology have witnessed significant advancements during the recent decades. These advancements include improved accuracy and speed in identifying and tracking individuals, as well as the ability to recognize faces in various scale and lighting conditions. Leveraging the potential of face recognition and tracking, this article explores the integration of process mining techniques to discover and visualize face’s appearing trajectories in crowd scenarios, aiming to enhance crowd security, surveillance, and personal identification. Notably, existing face recognition tools typically focus on bounding box localization, neglecting the utilization of face coordinates to construct trajectory models upon face re-identification. In this paper, full system architecture for building a trajectory model of re-identified faces in a crowd is proposed. This approach significantly helped in building a large database of visitor faces, and the proposed trajectory model resulted in a high rate of true positive face re-identification.
Empowering Learning through Intelligent Data-Driven Systems
Authors: Aldriwish Khalid Abdullah
Published: February 2024

The evolution of educational systems is closely tied to technological advancements, particularly the emergence of machine learning. This technology offers a sophisticated system capable of predicting, explaining, and influencing behavior. Many efforts have aimed to integrate machine learning into education, focusing on specific cases using ad-hoc models. This paper introduces an intelligent educational system that relies on data-driven student models, aiming to surpass the limitations of these ad-hoc systems. The approach outlined in this endeavor adopts a comprehensive and methodical modeling methodology centered on machine learning techniques. By employing Long Short-Term Memory (LSTM), the proposed approach enables predictive student models based on historical educational data. The effectiveness of this method was tested through experimentation on an intelligent tutoring system using 5-fold cross-validation, revealing that the smart educational system achieved a remarkable 96% accuracy rate. Furthermore, a comparison between the importance scores of features with and without the student models demonstrated the practicality and effectiveness of the proposed methodology.
Minden bremst Erwartungen
Authors: Mende Jan , Tewes Werner , Hofmann Janine , Stockburger Manfred
Published: February 2024

Edeka Minden-Hannover tritt bei der Umsatz- und Ertragsprognose auf die Bremse. Nachdem er die Planzahlen erstmals verfehlte, gibt sich Regionschef Mark Rosenkranz für 2024 nun vorsichtig.
Lidl baut Deluxe aus
Authors: Schulz Hans-Jürgen
Published: February 2024

Mit Premium-Handelsmarken werten die Discounter ihr Angebot auf. Der Blick auf die zwei wichtigsten Anbieter zeigt: Lidl baut aus, Aldi Süd ist vorsichtiger.
Alnatura stockt Geschäftsführung auf
Authors: Müller Annette
Published: February 2024

Alnatura-Chef Götz Rehn holt einen weiteren Geschäftsführer ins Haus, um die Dachmarke zu stärken. Der Unternehmer will erste Aufgaben abgeben.
PMI und BAT schließen Friedensabkommen
Authors: Brändlein Philip
Published: February 2024

Fünf Jahre lang haben sich Philip Morris und British American Tobacco rund um den Globus bekriegt. Nun lassen die beiden alle Patentstreitigkeiten fallen. Sie versprechen sich davon eine schnellere Expansion – PMI insbesondere in den USA.
Bell sieht noch Potenzial für Convenience-Salate
Authors: Lenders Dirk , Herberg Ruth
Published: February 2024

Mit dem Absatz von Abraham-Schinken ist die Bell Food Group sehr zufrieden. Für Convenience-Salate und -Früchte der Tochter Eisberg soll die Kundenbasis spürbar erweitert werden.
Tony’s greift Konkurrenz mit Produktnachahmungen an
Authors: Bender Hanno
Published: February 2024

Der Hersteller Tony‘s Chocolonely bringt Schokoladentafeln auf den Markt, die den großen Marken zum Verwechseln ähnlich sehen – und prangert deren Produktionsbedingungen scharf an.