Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect Guided Discovery-Based Thermochemistry Module on Critical Thinking Skills of High School and Vocational Students

Critical thinking is a vital skill for success in higher education and the workforce. However, it is often inadequately emphasized in high school curricula, resulting in students lacking proficiency. Guided discovery-based modules provide a promising approach to enhancing critical thinking by fostering independent exploration and concept discovery. This study aimed to assess the effectiveness of a developed module in improving thermodynamics-related critical thinking skills among 10th-grade students in Boyolali Regency, Indonesia. Five schools were randomly selected, with two classes from each forming control and experimental groups. The experimental group utilized the developed module, while the control group used traditional textbooks. Validated by experts, a test was administered to evaluate students' critical thinking skills, and statistical analysis revealed a significant difference between the experimental and control groups. The developed module demonstrated superior efficacy in enhancing critical thinking skills compared to traditional textbooks. Variations in mean scores among the schools suggest the need for further investigation across diverse educational contexts. The study's outcomes have implications for teaching and learning in Indonesia and other countries where critical thinking is insufficiently emphasized in high school curricula. Ethical considerations were upheld, ensuring participant rights and confidentiality. Future research can explore the module's effectiveness in improving critical thinking across different subjects and educational settings
Assessing mathematics within advanced school science qualifications

Abstract Following sustained discussion regarding the relationship between advanced mathematics and science learning in England, the government has pursued a reform agenda in which mathematics is embedded in national, high stakes A-level science qualifications and their assessments for 18-year-olds. For example, A-level Chemistry must incorporate the assessment of relevant mathematics for at least 20% of the qualification. Other sciences have different mandated percentages. This embedding policy is running in parallel with an adding policy that is encouraging all young people to include the study of mathematics to 18. In this paper, we present a detailed scrutiny of the published sample assessment materials in the new A-level Physics, Chemistry and Biology qualifications in order to consider what the impact of this policy move might be for the teaching and learning of mathematics, its applications in upper secondary school advanced science studies and the implications in the transition to mathematically-demanding undergraduate studies.
Secondary School Teachers’ Perception of Occupational Stress Causes in Mwanza Region, Tanzania

This paper presents findings of the study that had examined the teachers' perception of the causes of occupational stress in Tanzania’s secondary schools. Grounded in the job-demand control model, the study employed a mixed methods research approach and specifically a descriptive design. The study collected data from a sample of 460 participants drawn from secondary schools in Mwanza city and Ilemela municipality, Mwanza region of Tanzania. The data were collected between December 2021 and June 2023 using a questionnaire with both open-ended and closed-ended questions to generate both qualitative and quantitative data. Interviews were also held with some of the purposively selected teachers to provide complementary in-depth explanation. The results show an increase in teachers’ heavy workload, low salaries, mounting debts, family problem, and a low rate of job promotion emerged to be major causes of occupational stress. These causes were mainly classified as environment, management, and interpersonal stressors. The secondary school teacher respondents identified other stressors as lack of support from administration and limited autonomy and control (work environment stressors), managing rights and needs, lack of professional development opportunities, insufficient on-the-job training and a lack of collaborative decision-making, and lack of support and resources (management); emotions, participants reported experiencing frustration, disappointment, depression and exhaustion (intrapersonal); and. poor relations, a lack of flexibility and adaptability, and a lack of patience and tolerance (interpersonal stressors). On the other hand, they suggested counter-strategies that included promoting a healthy work-life balance, providing emotional support and ensuring effective communication channels are in place. The study, therefore, recommends advocating for increased support and resources, strengthening professional development opportunities and developing a performance recognition system to address; fostering open communication, promote a positive and inclusive school culture, and providing conflict resolution and interpersonal skills training; enhancing the work conditions among teachers and promoting collaboration and collective action. Overall, addressing these stressors could allow educational institutions to create a conducive and supportive work environment capable of enhancing teacher satisfaction and effectiveness.
Process management in organizations - a discussion on terminology

In the literature on the subject, one can notice quite a lot of freedom in the approach to formulating and understanding of terms relating to process orientation, process approach and managing processes and process management. In recent years, there has been a noticeable increase in interest in the study of process management not only of organizations, but also of individual activities such as projects. Managers are looking for indicators and metrics to measure the effectiveness and efficiency of processes in their activities. The purpose of the article is to try to identify differences and similarities and to systematize terminology related to process management in organizations. The study uses literature research based on an exploration of the Web of Science and Scopus databases, with the analysis limited to scientific publications only, and the selection of available materials excluded other materials, such as communications, reviews or other documents, from the analysis. The article is of a review and conceptual nature. The collected research results were subjected to comparative analysis, logical analysis and critical analysis. The research and analysis results presented in the article are an attempt to organize terminology that can be used in further scientific research.
Forecasting and management of innovation and investment development of iron ore enterprises based on stochastic risk modelling

The article considers theoretical and methodological applied aspects of modeling and quantification of financial and economic risks in forecasting and managing innovation and investment development of industrial entities under conditions of uncertainty on the example of iron ore enterprises. It is established that the need to take into account stochasticity in forecasting and managing innovation and investment development of iron ore enterprises is due to random factors of the parameters of the development of iron ore deposits and increasing the impact of associated risks. At the same time, force majeure risks are important, in particular, due to the spread of coronavirus disease and others. It is concluded that the uncertainty in forecasting and managing the innovation and investment development of iron ore enterprises is reflected in the effective financial and economic performance of the enterprise. The aim of the study is to develop applied theoretical approaches to risk management of iron ore enterprises to forecast the prospects of innovation and investment development, taking into account the impact of stochastic uncertainty inherent in the development of iron ore deposits and unforeseen associated risks. In this case, taking into account stochasticity in forecasting methods requires modeling quantitative risk estimates based on the use of boundary theorems of the theory of probabilities of the law of large numbers. As a result of the conducted researches the approach to economic and mathematical modeling of risk in forecasting and management of innovation and investment development of iron ore enterprises taking into account the set limit values of the interval of reliability of the forecast is developed.
Korean Urologic Oncology Society Guidelines: Does Angioembolization Improve the Quality of Life for Renal Cell Carcinoma Patients With Intractable Symptoms Who Are Unfit for Surgery?

Purpose: There is a lack of guidelines for using angioembolization to manage renal cell carcinoma (RCC) patients with intractable symptoms. Therefore, the Korean Urologic Oncology Society (KUOS) developed a set of recommendations for angioembolization for RCC patients with intractable symptoms who are unfit for surgery.Materials and Methods: A rigorous systematic review was performed and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) methodology was used to rate the certainty of the evidence for the patient outcomes and to develop the evidence into recommendations. The steering group, guidelines development group, systematic review team, and external review group consisted of KUOS members involved in the guideline development process.Results: The guidelines address the benefits, harms, patients’ values and preferences, costs, and resources related to angioembolization by using a single clinical question: Does angioembolization improve the quality of life for RCC patients with intractable symptoms who are unfit for surgery? Conclusions: The guideline development panel suggests angioembolization for RCC patients with intractable symptoms compared with supportive therapies, including systemic treatment (very low certainty of evidence, weak recommendation).
An Improved Fuzzy Rule Based Edge Detection Technique

Edge detection is imperative part of image processing. In this paper the development of fuzzy rule based edge detection technique is presented. The proposed technique makes use of three linear spatial filters i.e. high-pass, low-pass and first order edge detector filters to produce three edge values at each pixel location of the digital image through spatial convolution process. These three edge values are cogitated as fuzzy inputs and edge values along with Gaussian membership functions helps to decide that whether pixel in focus is an edge or not. The comparison operators are applied and the experimental results show that the proposed technique shows better results than Sobel, Prewitt and traditional fuzzy logic technique.
DarkDialogs: Automated detection of 10 dark patterns on cookie dialogs

In theory, consent dialogs allow users to express privacy preferences regarding how a website and its partners process the user’s personal data. In reality, dialogs often employ subtle design techniques known as dark patterns that nudge users towards accepting more data processing than the user would otherwise accept. Dark patterns undermine user autonomy and can violate privacy laws. We build a system, DarkDialogs, that automatically extracts arbitrary consent dialogs from a website and detects the presence of 10 dark patterns. Evaluating DarkDialogs against a hand-labelled dataset reveals it extracts dialogs with an accuracy of 98.7% and correctly classifies 99% of the studied dark patterns. We deployed DarkDialogs on a sample of 10,992 websites, where it successfully collected 2,417 consent dialogs and found 3,744 different dark patterns automatically present on the consent dialogs. We then test whether dark pattern prevalence is associated with each of: the website’s popularity, the presence of a third-party consent management provider, and the number of ID-like cookies.
The attitudes and practices of United Arab Emirates consumers towards food waste: A nationwide cross-sectional study

Background Reducing global food waste is an international environmental, health, and sus-tainability priority. Although significant reductions have been achieved across the food chain, progress by UAE households and consumers remain inadequate. This study seeks to understand the association between consumer attitudes, knowledge, and awareness relating to food waste practice of residents living in the UAE. to help inform policy and action for addressing this national priority. Methods A cross-sectional study was conducted using a validated semi-structured online questionnaire through stratified sampling (n =1052). The Spearman correlation coefficient was performed to determine the correlations. Two independent regression analysis were used to determine the association between food waste practice with: 1) knowledge and awareness and attitude subdomains, and 2) sociodemographic characteristics. Respondents (n=1072) largely reflect the socio-demographic characteristics and population distribution across the seven Emirates. Results As expected, a significant and negative correlation was found between food waste practice knowledge and awareness and overall attitude. The regression models showed reduced food waste practice was associated with better knowledge, personal attitude, financial attitude (first model), older age and fewer adults in the household (second model). We found a significant and negative association of personal attitude (a commitment, intention), financial attitude (cost-saving motivation), and (existing) knowledge of Food waste (FW) with practice of food waste, indicating that better knowledge about FW, personal attitude or financial attitude was associated with reduction in undesirable food waste practice. While awareness and emotional attitude (moral concerns) were positively and significantly associated with food waste practice (undesirable behaviour). Conclusions Food waste poses significant challenges in the UAE, and addressing it requires a comprehensive understanding of the multifaceted factors influencing consumer behavior. By promoting knowledge, fostering positive attitudes, and considering socio-cultural factors, policymakers can develop effective strategies to reduce food waste in households and contribute to sustainable development goals.
Image classification using machine learning

The objective of this paper is to implement different tools available in machine learning/artificial intelligence to classify faces and identify different features, highlights, and correlations or similarities between different celebrity faces which can apply in everyday security purposes to identity virtually if the authorized personnel is using certain access or not. The material present in this paper is a literature review of a machine learning model developed by the students. This is a classical problem of machine learning executed using a support vector machine. Images are separated based on sub-images. Each sub-image has been classified into a responsive class by an artificial neural network. The website then fetches the data from the back end and classifies the image into the corresponding personal.
An extended mtDNA phylogeography for the alpine newt illuminates the provenance of introduced populations

Many herpetofauna species have been introduced outside of their native range. MtDNA barcoding is regularly used to determine the provenance of such populations. The alpine newt has been introduced across the Netherlands, the United Kingdom and Ireland. However, geographical mtDNA structure across the natural range of the alpine newt is still incompletely understood and certain regions are severely undersampled. We collect mtDNA sequence data of over seven hundred individuals, from both the native and the introduced range. The main new insights from our extended mtDNA phylogeography are that 1) haplotypes from Spain do not form a reciprocally monophyletic clade, but are nested inside the mtDNA clade that covers western and eastern Europe; and 2) haplotypes from the northwest Balkans form a monophyletic clade together with those from the Southern Carpathians and Apuseni Mountains. We also home in on the regions where the distinct mtDNA clades meet in nature. We show that four out of the seven distinct mtDNA clades that comprise the alpine newt are implicated in the introductions in the Netherlands, United Kingdom and Ireland. In several introduced localities, two distinct mtDNA clades co-occur. As these mtDNA clades presumably represent cryptic species, we urge that the extent of genetic admixture between them is assessed from genome-wide nuclear DNA markers. We mobilized a large number of citizen scientists in this project to support the collection of DNA samples by skin swabbing and underscore the effectiveness of this sampling technique for mtDNA barcoding.
An RDL Modeling and Thermo-Mechanical Simulation Method of 2.5D/3D Advanced Package Considering the Layout Impact Based on Machine Learning

The decreasing-width, increasing-aspect-ratio RDL presents significant challenges to the design for reliability (DFR) of an advanced package. Therefore, this paper proposes an ML-based RDL modeling and simulation method. In the method, RDL was divided into blocks and subdivided into pixels of metal percentage, and the RDL was digitalized as tensors. Then, an ANN-based surrogate model was built and trained using a subset of tensors to predict the equivalent material properties of each block. Lastly, all blocks were transformed into elements for simulations. For validation, line bending simulations were conducted on an RDL, with the reaction force as an accuracy indicator. The results show that neglecting layout impact caused critical errors as the substrate thinned. According to the method, the reaction force error was 2.81% and the layout impact could be accurately considered with 200 × 200 elements. For application, the TCT maximum temperature state simulation was conducted on a CPU chip. The simulation indicated that for an advanced package, the maximum stress was more likely to occur in RDL rather than in bumps; both RDL and bumps were critically impacted by layouts, and RDL stress was also impacted by vias/bumps. The proposed method precisely concerned layout impacts with few resources, presenting an opportunity for efficient improvement.
TwitterSentiDetector: a domain-independent Twitter sentiment analyser

ABSTRACT Sentiment analysis has become more crucial after the rise of social media, especially the Twitter since it provides structured and publicly available data. TwitterSentiDetector is a domain-dependent and unsupervised Twitter sentiment analyser that focuses on the differences occurred by the informal language used in Twitter. TwitterSentiDetector uses natural language processing techniques alongside the proposed linguistic methods to classify sentiments of tweets into positive, negative, and neutral through the polarity scores obtained from sentiment lexicons. According to tests on widely used Twitter data-sets that contain manually detected sentiments labels alongside tweets, TwitterSentiDetector’s sentiment detection ratio is calculated as up to 69%. When the target sentiment classes are decreased to positive and negative, the detection ratio is increased up to 87%. The results are calculated very similarly when the same data-set is evaluated by the proposed tweet-level context aware sentiment analysis module which confirms the validity of each approach.
Impact of Real Manipulation and Tax Compliance on Strategy Model: A Simulative Prediction of The Future Certainty

High awareness of obedience and compliance is a fundamental requirement in monitoring going concerned, reflecting a critical role of meaningful accounting information. This research tested earnings quality to measure belief and faith in achieving a sustainable business as optimism and confidence in the better one. The collecting data concerned the listed manufacturing company during 2010-2021, where purposive sampling and moderated regression with dummy variables were to capture the strategy topologies. The causal research observed amounted to 214 companies, illustrating that the number of valid observations has been 1.278 samples. The finding depicts the mapping of the investor reaction to quality accounting information related to this rational decision model in predicting the high future certainty as a positive signal. Bayes Teorema and Decision Tree Model are used to distinguish the prospective company as a highly guaranteed information; the social responsibility of the regulator is to minimize the distortion by implementing the going-private procedure for the low-prospected one; pragmatically, one platform of financial reporting service is to deduct a minimum chance for opportunity accruals. As a new insight into the literature in accounting, this simplex-linear programming has been modified into an innovative portfolio as an artificial intelligence model to maximize each utility.
Blind radial distortion compensation from video using fast Hough transform

This paper presents a method of radial distortion automatic compensation on video from an unknown camera. The proposed algorithm estimates the distortion parameters by analyzing a sequence of video frames. It does not require any calibration objects, but is based on the assumption that the original scene contained straight lines. The method tries to perform such radial distortion correction that makes lines look generally straighter. To estimate the overall curvature of the lines we propose to use the fast Hough transform; without actually detecting them in the image. The proposed algorithm has been tested on real data.
Complexes of polyvinylpyrrolidone and polyethylene glycol with palladium(II) ions: characterization and catalytic activity

In this work, we obtained complexes by mixing aqueous solution of palladium(II) chloride with polyvinylpyrrolidone and polyethylene glycol. The composition of the complex compounds was determined by potentiometric and conductometric titration. IR spectroscopy and scanning electron microscopy (SEM) confirmed the coordination of polymeric ligand to palladium and allowed evaluating the morphology and features of the complex surface. The catalytic activity of the synthesized compounds in the oxidation of octene-1 by inorganic oxidizers (NaBrO3, K2S2O8) in aqueous-organic media in dimethyl sulfoxide (DMSO) under mild conditions was calculated. The reaction product was octanone-2, obtained in good yield (62–98%). Quantitative analysis of octanone-2 was made by the gas-chromatographic method. Mass spectrometry confirms the formation of octanone-2. The complexes are able to participate in five consecutive catalytic cycles without significant loss of catalytic efficiency. Oxidation of octene-1 proceeds by the oxidation-reduction mechanism and consists of two key stages.
Forecasting deflation probability in the EA : a combinatoric approach

This paper assesses and forecasts the probability of deflation in the EA at different horizons using a binomial probit model. The best predictors are selected among more than one-hundred variables adopting a two-step combinatoric approach and exploiting parallel computation in Julia language. The best-selected variables coincide to those standardly included in a small New Keynesian model. Also, the goodness of the models is assessed using three different loss functions: the Mean Absolute Error (MAE), the Root Mean Squared Error (RMSE) and the Area Under the Receiver Operating Characteristics (AUROC). The results are reasonably consistent among the three criteria. Finally, an index averaging the forecasts is computed to assess the probability of being in a deflation state in the next two years. The index shows that having inflation above the 2% level before March 2019 is extremely unlikely.