Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Surface Tension for Multicomponent Silicate Melts

Synopsis : In order to estimate surface tension for multicomponent silicate melts, expanded approximation rules was proposed in view of practical use, on the basis of the regular solution approximation rules of excess molar quantities for binary system melts. Necessary parameters for the above rules have been derived using the previous data in binaries and ternaries, etc. Using these parameters, it was found that near the melting point, surface tensions of pure oxides and halides 0 ƒÐi were related to ( Ti)mp/0 Vi2/3, where ( Ti)mp and 0 Vi are the melting point and molar volume of pure oxides and halides, respectively. From the collation with the data of multicomponent silicate melts, it was confirmed that the above expanded approximation rules were applicable to predict the surface tension of melts over the wide range of composition and temperature discussed.
Fatty acid composition and antioxidant activity of Angelica glauca and Chenopodium album seed extracts from Kashmir

Angelica glauca Edgew. and Chenopodium album Linn. are medicinally important plants with aromatic, nutritious and flavor-enhancing properties. In this study the fatty acid composition of petroleum ether seed extracts (PE) of processed plants were analyzed by gas chromatography-mass spectrometry (GC-MS). The PE consisted mainly of unsaturated fatty acids, such as petroselinic acid 74.26% and oleic acid 7.37% for A. glauca and linoleic acid 53.05% and oleic acid 20.74% for C. album. The de-fatted seed extracts were screened for their antioxidant activities using 2,2-di-phenyl-1-picrylhydrazyl (DPPH), nitroblue tetrazolium (NBT), hydrogen peroxide (H2O2) and 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assay. Almost all the assays resulted in defatted seed extracts showing powerful radical scavenging activity. These findings suggest that the processed plants could be used as ingredients (as a source of natural antioxidants and unsaturated fatty acids) for the formulation of functional foods.
A simulation-based study to calculate all the possible trajectories of differential drive mobile robot

Deferential Drive Mobile Robot (DDMR) is being used in many applications as it is easy to be modeled and controlled. This research presents the idea of using DDMR turning motion behavior to develop an algorithm that calculate all the circular trajectories. This can be used to navigate DDMR in a curvature paths instead of linear ones. In this research we design and simulate Differential Drive Mobile Robot (DDMR) model. Then we use the simulated model to calculate all the possible trajectories that DDMR can follow with each left and right wheel velocity configurations. Results are saved in a navigation look-up table that can be implemented in DDMR navigation's approach.
Building capacity through open approaches: Lessons from developing undergraduate electrophysiology practicals

Background: Electrophysiology has a wide range of biomedical research and clinical applications. As such, education in the theoretical basis and hands-on practice of electrophysiological techniques is essential for biomedical students, including at the undergraduate level. However, offering hands-on learning experiences is particularly difficult in environments with limited resources and infrastructure. Methods: In 2017, we began a project to design and incorporate electrophysiology laboratory practicals into our Biomedical Physics undergraduate curriculum at the Universidad Nacional Autónoma de México. We describe some of the challenges we faced, how we maximized resources to overcome some of these challenges, and in particular, how we used open scholarship approaches to build both educational and research capacity. Results: We succeeded in developing a number of experimental and data analysis practicals in electrophysiology, including electrocardiogram, electromyogram, and electrooculogram techniques. The use of open tools, open platforms, and open licenses was key to the success and broader impact of our project. We share examples of our practicals and explain how we use these activities to strengthen interdisciplinary learning, namely the application of concepts in physics to understanding functions of the human body. Conclusions: Open scholarship provides multiple opportunities for universities to build capacity. Our goal is to provide ideas, materials, and strategies for educators working in similar resource-limited environments.
The Impact of External Environment on Competitive Advantage through SME Differentiation Strategy in Central Java

The competitiveness of Small and Medium Enterprises (SMEs) in Indonesia is still very low and vulnerable compared to increasingly uncertain business environment dynamics. Changing conditions require SMEs carry out continuous and systematic analysis of the external environment, so that owners who carry out strategic planning get information through various sources in the external environment. This is done to maintain a competitive advantage and as an effort to realize unexpected opportunities and progress. This study aims to: (1) measure the impact of external environment on differentiation strategy in SMEs in Central Java; (2) measure the impact of external environment on competitive advantage in SMEs in Central Java; (3) measure the impact of differentiation strategy on competitive advantage in SMEs in Central Java. The type of research used in this study is causal research. The method used in this research is quantitative. The population that will be used and examined in this study is all SMEs in Central Java, while the samples in this study were 180 SMEs in Central Java with a multivariate type sample size. Data collection technique was conducted using a questionnaire. This study uses Partial Least Square (PLS) for its analysis technique. The results in this study indicate that: (1) External Environmental has a significant effect on Differentiation Strategy; (2) External Environmental has a significant impact on Competitive Advantage. And (3) Differentiation Strategy has a significant effect on Competitive Advantage.
Moderating Role of User Experience and IT Reliability in Controlling Influence on Job Performance and Organizational Performance

Controlling is a method, which is most often used in contemporary organizations. The expectation of improvement of the organization’s results is the most important reason of controlling implementation. The relation between controlling use and organizational performance is often taken for granted, however there are no comprehensive research explaining in detail how it affects results of organization functioning. The article attempted to fill in the existing research gap and explain how controlling affects results of organization functioning. The analysis concerned the impact of controlling use on both job performance and organizational performance. Since the job performance in case of controlling is increasingly dependent on the IT solutions, the analysis concerned the impact of IT reliability and User Experience (UX) on the developed model of the controlling influence on organizational performance. In that context the aim of the article was to clarify the mechanism of controlling use influence on organizational performance – considering the mediating role of job performance of employees and moderating role of IT solutions (the impact of UX and IT reliability on the relations between controlling, job performance and organizational performance). Formulated hypotheses were verified empirically on the sample of 637 organizations (349 operating in Poland and 288 operating in Switzerland). The presented results of empirical research allowed for the construction of a mediating model demonstrating the impact of controlling use on both job performance and organizational performance and shown that UX and IT reliability are moderators of the relation between the controlling use and job performance, and the relation between job performance and organizational performance.
Do “decent work” dimensions lead to work engagement? Empirical evidence from higher education institutions in India

Purpose The study aims to investigate the impact of “decent work” dimensions on faculty members’ work engagement levels in the higher education institutions in India. Design/methodology/approach Data were obtained from 293 faculty members working in higher education institutes in India. The proposed study hypotheses were tested by deploying the statistical technique of multiple regression analysis using statistical package for social sciences Version-24. Findings Results demonstrated that of the five dimensions of “decent work,” only “access to health care” and “complementary values” were significant predictors of work engagement. “Adequate compensation,” “free time and rest” and “safe interpersonal working conditions” as dimensions of “decent work” were not found to be significantly related to work engagement. Research limitations/implications Findings encourage education policymakers to implement a “decent work” policy for faculty members with greater emphasis on ensuring workplace-fit and provision of adequate health-care facilities to keep the workforce engaged. Originality/value It is one of the few studies conducted in the South-Asian context that highlight “decent work” as a crucial job resource, useful in enhancing the work engagement of faculty members in higher education institutions.
Toward high energy density cathode materials for sodium-ion batteries: investigating the beneficial effect of aluminum doping on the P2-type structure

Aluminum doping of the P2-type layered structure results in a Na-ion cathode material (Na0.6Ni0.22Al0.11Mn0.66O2) with excellent performance. The material, in fact, exhibits outstanding specific capacities, 250 mA h g−1 and 150 mA h g−1 at 0.1 and 5C rate, respectively, which have never been reported before. Herein, a deep investigation of both the electrochemical behavior and the structural and morphological properties upon cycling reveals the beneficial effect of aluminum and the importance of a suitable metal intermixing selection for the obtainment of high performance cathode materials.
The Interdependency of the Diction and MBTI Personality Type of Online Users

This paper offers insight into the 16 Myers-Briggs Type Indicator (MBTI) personality types and how they may affect the diction used by online users on social media platforms such as Twitter and YouTube. The Myers-Briggs Type Indicator categorizes individuals who take the indicator test into one of 16 different personality types, and each of these types have distinct characteristics, from the simple Introverted versus Extraverted to Intuitive or Sensing, Feeling or Thinking, and Judging or Perceiving. These 4 sets of binary characteristics produce 16 different personalities that are often used to create general pictures or summaries about the individual who was assigned a certain personality type. The characteristics can, on occasion, even predict the potential actions of the individual based on their assigned personality type. This is what allows for the objective of this paper to be achieved - to use data analysis and machine learning to identify the number of times certain words were used by those of different personalities on online platforms, find patterns, and observe if the mechanic prediction of MBTI type based on words used in online posts is possible. The three machine-learning algorithms used to predict the personality types were the Naive Bayes, Gradient, and Random Forest algorithms, with a randomly-selected 80% of the data being used to train the algorithms and the remaining 20% being used to test the machine-learning for accuracy and specificity. This paper will analyze 433,750 total individual posts made online, along with the programming-processed data and the final results of the predictions, identifying which algorithm was most effective in predicting MBTI type and what future steps could be taken to increase accuracy and capacity.
Learning media development based on CNC simulator as the digital tool to support the CNC practice learning during COVID-19 new normal

Covid-19 pandemic changed human’s lifestyle in various areas. Indonesia Government enacted many rules to avoid Covid-19 transmission. The Ministry of Education and Culture issued a policy through a circular regarding the arrangement of learning activities from home during the Covid-19 emergency. Due to the policy, classical in-class learning method changed into virtual through online classes. The CNC simulation makes it possible for students to visualize model and concept into realization. The CNC Simulator is a computer program that could simulate the setting and operation of the CNC machine. The CNC simulator can be used as a digital tool to support the CNC practice learning activity, which was hindered by social activities restrictions during the COVID-19 pandemic. This research used the ADDIE development model, according to Lee and Owens. The stages were: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. Based on the evaluation, it could be concluded that all five indicators fell into the category of proper to use without revision because on average, they had above 80% score. The final score was 84.25%; thus, learning media based on CNC simulator was proper to sue in the learning activity.
Classification of fake news using multi-layer perceptron

"Fake News (FNs) is defined as a made-up story to deceive or to mislead. " The problem of FNs spread widely in recent years, especially on social media such as Facebook, Twitter, and other sources like webs and blogs. It has become a significant problem in society as a result of changing people's ideas and opinions about the direction of this news. In this paper, FNs detection can be proposed by using the Term Frequency-Inverse Document Frequency (TF-IDF) as features extraction, and Multi-Layer perceptron (MLP) algorithm as a classifier. Two phases (feed-forward and back-propagation) are used with a three-layers, which are (input layer, one hidden layer, and output layer). After running our proposed algorithm on a FNs dataset, the classification accuracy achieved equals 95.47%.
The impact of morphodynamics and storm floods on pore water flow and transport in the subterranean estuary

high-energy beaches change this classical picture of a subterranean estuary. The model results suggest that the variable beach morphology and seasonal storm floods lead to strong spatio-temporal variability of hydro-dynamic and transport patterns reaching several 10th of meters into the subsurface, thereby distorting the classical salinity stratification. We believe that these findings are particularly relevant for sandy high-energy beaches which are commonly present at global coastlines.
Mechanistic Modeling Of Anaerobic Thps Degradation In Seawater Under Various Conditions

Microbially influenced corrosion (MIC) is increasingly becoming a major problem in the oil and gas industry as well as in the water treatment industry. Currently, MIC mitigation mostly depends on biocides. THPS (Tetrakis Hydroxymethyl Phosphonium Sulfate) is one of the commonly used biocides because it is degradable and non-bioaccumulative in the environment. Usually a minimum of 50 or 100 ppm THPS is needed to prevent planktonic bacterial growth and biofilm establishment. A much higher concentration is needed to remove established biofilms. THPS degradability, however, shortens its effectiveness in time. Prediction of THPS degradation is essential in proper dosing for operations such as hydrotesting. THPS degradation may be affected by many factors such as temperature, pH, O2, light, presence of microbes and presence of mild steel. This work presents a mechanistic model,based on experimental data, to predict THPS degradation as a function of time, temperature and pH.
Environmentally Friendly Lithium-Terephthalate/Polylactic Acid Composite Filament Formulation for Lithium-Ion Battery 3D-Printing via Fused Deposition Modeling

In this paper, the development of an environmentally-friendly lithium-terephtalate/polylactic acid (Li2TP/PLA) composite filament, for its use, once 3D-printed via Fused Deposition Modeling (FDM), as negative electrode of a lithium-ion battery is reported. Solvent-free formulation of the 3D-printable filament is achieved through the direct introduction of synthesized Li2TP particles and PLA polymer powder within an extruder. Printability is improved through the incorporation of poly(ethylene glycol) dimethyl ether average Mn~500 (PEGDME500) as plasticizer, while electrical performances are enhanced through the introduction of carbon black (CB). Thermal, electrical, morphological, electrochemical and printability characteristics are discussed thoroughly. By taking advantage of the 3D-printing slicer software capabilities, an innovative route is proposed to improve the liquid electrolyte impregnation within the 3D-printed electrodes.
How digital knowledge sharing affects innovation work behavior and organizational innovation capability in term of sustainability development goals

This study seeks to analyze the antecedent factors of digital knowledge sharing that affect innovation work behavior and organizational innovation capability of employees working in government organizations. This study identifies four antecedents of digital knowledge sharing, namely demographics, environment, individuals, and organizations that have an influence on innovation work behavior and organizational innovation capability through indicators of knowledge donating and knowledge collecting from digital knowledge sharing. The online survey method was used to collect data from respondents, a number of 1000 employees of the Secretariat General, Ministry of Finance of the Republic of Indonesia. The data analysis of this study used Partial Least Square-Structural Equation Modeling (PLS-SEM) with the SmartPLS 3.2. 9 application. The results showed that the four antecedents of digital knowledge sharing had a significant effect on innovation work behavior and organizational innovation capability through indicators of knowledge donating and knowledge collecting from digital knowledge sharing. In addition, it was also found that the knowledge donating indicator was a better contributor in facilitating innovation work behavior and organizational innovation capability of government employees compared to knowledge collecting indicators. This study also lead the digital knowledge sharing, innovation works behavior, and organizational innovation capacity into a part of sustainability development goals.
The Challenges of Mitigating Climate Change Hidden in End-User Beliefs and Expectations

This research explores the potential challenges of reducing climate change hidden in the personal and collective energy use-related beliefs and expectations of end users. The study proposes a new typology of social environments, using the concept of personal and collective efficacy, which is suitable for exploring the level and nature of the challenges of solving social problems that require engaging whole societies. We use empirical data from round eight of the European Social Survey, which covers more than 20 European countries, and we employ the basic statistical methods of descriptive statistics, linear correlation and population proportion. The findings suggest that the challenges to climate-change mitigation by changing energy-use behaviour could be hidden in contradictions between beliefs in personal and collective abilities to contribute and positive outcome expectations. This opportunity could be addressed by relevant policy measures, providing more evidence of positive outcomes, even from personal contributions, and developing suitable means for collective contributions to increase awareness and belief in collective engagement.
Identification of Fruits and Vegetables using Embedded Sensor

In precision agriculture, computational techniques play a critical role. It is a vital job to detect and classify fruits and vegetables from crops and gardens. In fruit detection and yield estimation, an intelligent detection system is used as a key technology where embedded sensor techniques are being implemented. Many researchers developed a different classification system for classifying the fruits or vegetables using image processing techniques and machine learning algorithm. Big computers with fast CPUs and GPUs, massive RAM sizes or cloud algorithms have often been associated with them even simple applications. In this article Tensorflow and Arduino BLE sense are used to identify the fruits and vegetable with less resource.
Urban educated group's perceptions of the COVID-19 pandemic management in Bangladesh: a qualitative exploration

Background: Since the emergence of the COVID-19 outbreak, Government of Bangladesh (GoB) has taken various measures to restrict virus transmission and inform the people of the situation. However, the success of such measures largely depends on a positive public perception of the government’s ability to act decisively and the transparency of its communication. We explored public perceptions of pandemic management efforts by the Bangladeshi health sector decision-makers in this study. Methods: As this qualitative research was conducted during the COVID-19 pandemic, data was gathered through seven online mixed-gender focus group discussions involving 50 purposively selected clinicians and non-clinicians. Results: The study participants concurred that, from the outset, decision-makers failed to engage the right kind of experts, which resulted in poor pandemic management that included imposing lockdown in periphery areas without arranging patient transport to the center, declaring certain hospitals as COVID-19 dedicated without preparing the facilities or the staff, and engaging private hospitals in care without allowing them to test the patients for COVID-19 infection. Several participants also commented on ineffective actions on behalf of the GoB, such as imposing home quarantine instead of institutional, corruption, miscommunication, and inadequate private sector regulation. The perception of the people regarding service providers is that they lacked responsiveness in providing treatment, with some doctors misleading the public by sharing misinformation. Service providers, on the other hand, observed that decision-makers failed to provide them with proper training, personal protective equipment, and workplace security, which has resulted in a high number of deaths among medical staff. Conclusions: The Bangladeshi health sector decision-makers should learn from their mistakes to prevent further unnecessary loss of life and long-term economic downturn. They should adopt a science-based response to the COVID-19 pandemic in the short term while striving to develop a more resilient health system in the long run.