Reviewerly/exHarmony huggingface dataset:
Main Minerals of the Araxá Alkali-Carbonatite Complex, Minas Gerais State, Brazil

The Araxá alkali-carbonatitic complex is a significant source of niobium and phosphate and accounts for approximately 75% of global niobium production. The complex contains magmatic niobium ore minerals, such as natrium-pyrochlore and calcium-pyrochlore, and hydrothermal niobium ore minerals in the form of kenopyrochlore and natrium-pyrochlore. The magmatic micas in the complex are tetraferriphlogopites that exhibit Mg-rich cores surrounded by one or two rims of tetraferriphlogopites formed by hydrothermal alteration. These rims have lower IVAl and Mg apfu (as per formula unit) values but higher IVFe3+ and Fe2+ contents than the original phlogopite. Microphlogopitite dikes that formed during several episodes of magmatism between 83.48 and 77.4 Ma contain tetraferriphlogopites, phlogopite, eastonite, biotite, and annite-siderophyllite. These micas exhibit variations in Mg2+ and Fe2+ concentrations owing to the magmatic differentiation and subsequent hydrothermal alteration, resulting in rims with higher Mg and lower Fe2+ concentrations than the mica core. The Araxá complex also contains magmatic magnetite that has been further altered by hydrothermal processes, resulting in the formation of ilmenite and the oxidation and crystallization of titaniferous hematite. Magnetite within the microphlogopitites displays variations in the concentrations of Fe3+ and Ti, likely owing to the timing of the intrusion of the microphlogopitites into the Araxá complex. The degree of oxidation of the oxidized ilmenite of the Araxá complex varies based on the intrusions, which occurred before or during hydrothermal activity. Apatite is concentrated in carbonatites, which form a ring around the core of the complex, and disseminated in phlogopite-rich rocks hosting norsethite carbonatite veins in the center of the complex. The apatite in the core rocks exhibits complex zonation with unexpected changes in Ca, P, and Sr concentrations. Apatite in the carbonatite ring was generated during the differentiation of the carbonatite magma, whereas that in the core rocks exsolved from the phosphorus-saturated carbonatite magma (Biondi and Braga Jr., 2023a). The carbonate minerals dolomite, norsethite, and calcite exhibit compositions grouped around their end-members, suggesting that they formed during different stages of magmatic source differentiation. Strontium differentiation occurs in the magmas corresponding to each endmember, and carbocernaite is exsolved from the Sr-saturated crystals, thus forming micro-inclusions in some carbonate crystals that have been displaced by late-magmatic hydrothermal fluids.
ANALISIS SENTIMEN REVIEW PENGGUNA APLIKASI DEPOK SINGLE WINDOW DI GOOGLE PLAY MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

Technology is developing rapidly, including in the world of government. The district government makes a web or mobile-based application with the aim of helping people in getting the services that the community deserves. The Depok Regency Government created a mobile-based public service application called Depok Single Window. Due to the importance of user reviews for the continuity of the DSW application, it is required to analyze the sentiment of reviews of the Depok Single Window application on Google Play Store. Sentiment analysis is carried out using the Support Vector Machine. The data used in this study were 733 reviews obtained from the scrapping. The scrapping is carried out by utilizing python library, namely google play scrapper as access to retrieve data. The results attained from this research are an accuracy value of 89.23% for the sentiment analysis of the Depok Single Window application, which means that the Support Vector Machine is good to be used to classify the Depok Single Window application review data into positive, negative and neutral.
Artificial intelligence and “Foreign language for specific purposes” classes in higher education institutions

The global influence of artificial intelligence implies a change in approaches from the restructuring of the social order in a broad sense to the processes of learning and management in education in a narrow sense. Therefore, there is no choice but to accept artificial intelligence as a necessity and effectiveness of improving educational processes both at the classroom and system levels. The purpose of the article is to determine the role and significance of the AI use in learning a foreign language in “Foreign language for specific purposes” classes (FLSP) in higher education institutions. Artificial intelligence (AI) is the ability of intelligent machines to perform tasks accurately and efficiently. AI is a complex mixture of computer science, mathematics and other sciences that helps machines reproduce human cognitive abilities. AI in education involves adaptive, personalized, interval learning and automated assessment. The main AI functions in FLSP classes are independent assessment of student achievements, learning assistance, global learning, and individual approach. Positive AI aspects in FLSP classes are adaptation to students’ strengths and weaknesses, appropriate support based on results, adaptive learning at the initial level, prevention of shyness, and continuous practice in a convenient mode. However, excessive use of AI can also cause negative consequences, such as a decrease in students’ cognitive abilities; complete dependence of mood on failures and successes in the AI operation; loss of real connections between participants of the educational process; reduction of the teacher’s role; deterioration of health; loss of personal data. The use of AI is an integral part of the educational process. AI, as an effective addition to FLSP classes, can enrich the process of learning a foreign language, and also provides adaptability, personalization and satisfies the desire for globalized learning.
A Review of Educational Adaptation During the COVID-19 Pandemic via Online Learning

Purpose -This study explains how the educational sector adapts to become more effective in the long run regarding the COVID-19 pandemic has caused significant hardship for families, children, educators, and teachers.Learning has been adapting to the digital economy. 1515Method -The researchers employed the documentary method in this review article.Random sampling from reliable and valid sources was utilised in the first step and was analysed using content analysis from the selected papers adopting purposive sampling in the second step.Results -The findings reveal that in most countries, the COVID-19 lockdowns have produced a blended learning model that combines face-to-face education with e-learning.This means that class sizes have been reduced, students and teachers must maintain social distance, and learning schedules are staggered.Moreover, students can continue their education using online resources such as language apps, video conferencing tools, and virtual tutoring.Conclusion -Teachers have had to adapt to the educational world in distance education.Most teachers in schools and universities face this challenge, even though teachers lack the skills and equipment to provide adequate distance education in many developing nations.As governments consider reopening schools following the easing of quarantine restrictions, the safety of students and teachers should take precedence, and social isolation of students, access to personal protective equipment, and routine virus testing will be crucial.Recommendations -The role of instructors must shift from knowledge educator to learning motivator and progress manager.Additionally, the investment in the Information and Communication Technology (ICT) infrastructure of the education service to improve educational outcomes should be considered.Research Implications -The internet and technology in the classroom should be given serious consideration to becoming more competent.The government must improve and alter teachers' perceptions of educational technology integration.As teachers play a crucial role in ensuring that any new policy is implemented effectively and efficiently, they are essential in implementing any new initiative.
Sensing the Future: A Design Framework for Context-Aware Predictive Systems

Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel &amp; Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems.
Partial Sum Quantization for Reducing ADC Size in ReRAM-Based Neural Network Accelerators

While resistive random-access memory (ReRAM) crossbar arrays have the potential to significantly accelerate deep neural network (DNN) training through fast and low-cost matrix–vector multiplication, peripheral circuits like analog-to-digital converters (ADCs) create a high overhead. These ADCs consume over half of the chip power and a considerable portion of the chip cost. To address this challenge, we propose advanced quantization techniques that can significantly reduce the ADC overhead of ReRAM crossbar arrays (RCAs). Our methodology interprets ADC as a quantization mechanism, allowing us to scale the range of ADC input optimally along with the weight parameters of a DNN, resulting in multiple-bit reduction in ADC precision. This approach reduces ADC size and power consumption by several times, and it is applicable to any DNN type (binarized or multibit) and any RCA size. Additionally, we propose ways to minimize the overhead of the digital scaler, which is an essential part of our scheme and sometimes required. Our experimental results using ResNet-18 on the ImageNet dataset demonstrate that our method can reduce the size of the ADC by 32 times compared to ISAAC with only a minimal accuracy loss degradation of 0.24%. We also present evaluation results in the presence of ReRAM nonideality (such as stuck-at fault).
PEMBELAJARAN ONLINE: ANALISIS KESIAPAN BELAJAR DAN MANAJEMEN WAKTU SISWA KELAS VI

This study aims to determine the learning readiness and time management of class VI students in online learning. The study was conducted at MI Raudlatul Mubtadiin Kediri with 18 students as participants consisting of 8 males and 10 females. The data collection technique was carried out by using a questionnaire distributed to all students and interviews with 2 representatives of class VI students. The stages of research are adjusted to case study research. Data analysis techniques using data analysis techniques by Miller include data reduction, data presentation, and concluding. The results showed that students' readiness for learning in terms of infrastructure was good and there was parental support during online learning. Student time management in online learning has been done through making a daily activity schedule, but it is still in the form of activities that are general in nature but not specific and detailed.
An Autonomous Mechanical Maxwell's Demon

Szilard proposes three engine models in 1929 to resolve several paradoxes arising from Maxwell's Demon [1,2].We analyze Szilard's second demon models [1,2].We show that the second one, apparently employs distinct molecular species and semipermeable membranes.On this basis, we propose a fourth model of Szilard's engines.The mechanism of this model is based on Raoult's law and Van't Hoff's law in colligative properties of aqueous solutions, coupling the evaporating process of water molecules with the reverse osmosis process of water molecules, forms a spontaneous thermodynamic cycle composed.Wefind:(i) The cycle can proceed spontaneously in a gravitational field, without the need for an external force to do its work;(ii) The continuous flow of water molecules in the cycle, like the continuous current in a superconducting ring, can continue for a long time, but it is not a perpetual motion machine and does not violate the second law of thermodynamics;(iii) The cycle is capable of doing what Maxwell's Demon does, it is capable of producing a temperature difference in a single hot bath heated at temperature equilibrium.(iv) Its transitory functioning as an engine that converts disorganized heat energy to work is governed by the Onsager reciprocal relations.Taken together, this Szilard's fourth model is a new self-consistent, non-equilibrium thermodynamic cycle that provides a new theoretical model for understanding that quasi-perpetual motion processes and autonomous mechanical Maxwell's Demon do exist in nature.
Keefektifan Model Pembelajaran Tipe CIRC (Cooperative Integrated Reading and Composition) terhadap Minat dan Hasil Belajar pada Materi Akar Pangkat Tiga Bagi Siswa Kelas VI Sekolah Dasar

One of the goals of learning mathematics is so that students can have skills in solving a problem. In order to increase the positive attitude of students, the material must be designed in such a way, so that it is suitable to achieve the teaching goals that have been determined to be achieved. Therefore, it is necessary to choose a learning model that is estimated to be appropriate to use. One of them is the cooperative learning model that can help students improve positive attitudes including building confidence in their ability to solve math problems. There are many cooperative learning models in mathematics learning that meet the characteristics of effective learning, including the CIRC type cooperative model (Cooperative Integrated Reading and Composition) which can help students hone problem solving skills in solving story problems. So that with this learning model students are able and skilled to solve problems in story problems with the right steps. The purpose of this study was to determine the effectiveness of the CIRC model in improving student learning outcomes and student interest in learning. This research was a research experiment carried out at SD Negeri Sendang and SD Negeri Gondo 01, in grade VI students.
THE ROLE OF RETAINER AS PREVENTIVE IN POST-ORTHODONTIC TREATMENT RELAPS

Orthodontic treatment is a very complex process because throughout human life the teeth will continue to change position due to their main function which plays an important role in the mastication process, so that when the periodontal tissue and teeth are under pressure after orthodontic treatment, it is very easy for the teeth after orthodontic treatment to relapse or return to the original position before orthodontic treatment until the maximum remodeling process is achieved, the remodeling process takes at least 6 months, therefore a tool or device is needed that can be used to maintain the position of the teeth after orthodontic treatment, namely a retainer, because the success of orthodontic treatment itself will not be achieved if the tooth returns to the original arch and position.
Pengembangan Media Digital Book Bergambar Seri Berbasis Examples Non Examples untuk Meningkatkan Keterampilan Menulis Karangan Narasi Siswa

This research is motivated by the low skills of writing narrative essays for fifth grade students of SDN Sidalang 01 based on observations and interviews with classroom teachers. This research aims to produce digital media illustrated book series based on examples non examples to improve the skills of writing narrative essays. The type of research used is Thiagarajan Semmel and Semmel 4-D (Four-D) development research. The data collection method used is the method of observation, questionnaires and tests. The results of the research at the definition and design stages produced a digital media design for a series of picture books which in its presentation used the examples non examples syntax. Then the development stage was carried out, namely by expert validation, practicality testing and effectiveness testing on digital media based on examples-non-examples-based picture books. The results of the media expert validity test got an average score of 89.37% with very good criteria and 89.5% according to material experts with very good criteria. The results of the practicality test based on student responses got an average score of 92% and 90.7% based on the teacher's response with very good criteria. The effectiveness of digital media illustrated book series based on examples non examples tested valid based on the t test got a sig (2-tailed) of 0.000 so that Ho was rejected, while the average N-Gain result was 0.57 in the moderate improvement category. It can be concluded that the digital media picture book series based on examples and non-examples is proven to be valid and feasible to use in learning.
Factors Influencing Employee Engagement and its Impact on Organizational Performance

Purpose: The purpose of this study is to identify the factors affecting the employee engagement as well as to examine the effect of employee engagement on organizational performance.&#x0D; Design/Methodology/Approach: Descriptive and Analytical research design was used for data analysis. A convenient sample of 200 employees of Nepal Telecom responded to a structured questionnaire. Correlation and Regression analysis were performed to examine the hypothesis.&#x0D; Findings: The result shows that identified factors like career development, compensation, work environment, team and co-worker relationship, organizational policies and workplace wellbeing have positive and significant impact on employee engagement whereas Leadership has negative and insignificant impact on employee engagement. Further, the result also shows employee engagement had significant impact on organizational performance.&#x0D; Practical Implication: Organization must focus and effort on the factors like organizational policies and team and co-worker relationship as they have shown significantly higher impact on employee engagement and organizational performance. Organization should develop favourable organizational policies and focus on developing a good environment and promote such programmes that enhances team and peer relationship.&#x0D; Originality/Value: Managers must apply various strategies to make their employee engaged which is less prioritized till today.
Strategi Pembelajaran Bahasa pada Kelas III di SD Negeri 02 Karangasem

This article aims to understand how language learning in lower grade elementary schools, especially in grade II SD Negeri 02 Karangasem, covers aspects of reading, writing, listening, and speaking. Aspects of reading and writing are very important to be taught in elementary school. By reading and writing, all knowledge will be absorbed by students and they can understand and define the meaning of words that are read, heard, and remember them well. However, the difficulty in teaching beginning reading and writing lies in the strategies used. As for low grade students, learning should be a fun and meaningful activity. That is, activities that are close to the daily lives of students. Therefore, the strategies that can be applied are reading game learning strategies and early writing learning strategies using the SAS method. This strategy is based on student experience which is then applied in teaching reading and writing beginning to students.
PENERAPAN METODE EVERYONE IS TEACHER HERE UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS V DI SDIT WANASABA

The purpose of this study is to increasing the students' motivation to learn by using the method everyone is teacher here for class V SDIT Wanasaba. The methode of the research is a classroom action research (Classroom management) which was carried out for two cycles, each cycle consisting of four stages of activity, namely, planning stage, taking action stage, observing stage and reflecting stage. The subjects in this study were fifth grade of students SDIT Wanasaba, totaling 26 people consisting of 11 boys and 15 girls. Students' learning motivation data was collected using a questionnaire, after the data was collected it was then analyzed descriptively. The data of student learning motivation has increased, in the first cycle the average student motivation is 20.42 and is in the sufficient category and the second cycle the average student learning motivation is 26.92 in the good category. Based on these data, it can be concluded that the everyone is teacher here method can increase students' learning motivation.
Sejarah Kebudayaan: Hasil Budaya Material Dan Non Material Akibat Adanya Pengaruh Islam Di Nusantara

Indonesia is currently a nation with a diversity of cultures, but in this diversity there is an influence given by foreigners even though not entirely.The influence given by foreigners can be learned from the cultural acculturation in Indonesia, like the acculturation of local culture with Hindu-Buddhist culture, and acculturation of local culture with Islamic culture.The focus of this writing is the result of culture due to the influence given by Islam in Nusantara culture, because nowadays Islamic culture affects many customs or all local traditions run by the wider community.This study was conducted using historical methods, namely heuristics to collect data, criticism for sorting data, interpretation to interpret the data that was received, and historiography to incorporate all the necessary data For historical writing, as well as conducting literature study methods, with a series of research methods, researchers found that the Islamic culture has had considerable influence both in the material and non material culture.
Improved Task Scheduling for Cloud Computing Using Combination of Genetic Algorithm and Tabu Search Algorithm

Abstract: Cloud computing has revolutionized the way computational resources are provisioned and utilized. However, effective task scheduling in cloud environments remains a critical challenge due to the complexity of managing resources and meeting quality of service (QoS) requirements. In this paper, we address the multi-objective task scheduling problem by proposing a novel scheme that combines a hybrid algorithm, HGTSA, to achieve improved convergence rates and overall efficiency. Our main contributions include the development of a fitness function that considers makespan, system capacity, and resource utilization, as well as the implementation of the HGTSA algorithm. Through extensive simulations, we demonstrate the superiority of our proposed scheme, outperforming conventional genetic algorithms and achieving better makespan times. Furthermore, we highlight the future scope of research in leveraging machine learning techniques to further enhance task scheduling processes and optimize decision-making based on workload predictions and historical data.