Deductive Reasoning Research Articles

Juridical Analysis of the Position of the Surakarta Kasunanan Palace as a Cultural Heritage Area Linked to the Basic Agrarian Law (UUPA)

With the provisions of the Fourth Dictum of the UUPA, regarding the position of the Surakarta Kasunanan Palace as a cultural heritage area, there are still differences of opinion regarding its ownership status. This research aims to examine the position of the Surakarta Kasunanan Palace after the enactment of the UUPA, as well as to analyze the ownership status of the Surakarta Kasunanan Palace as a cultural heritage area. The research method is normative juridical. The type of data used is secondary data. Data analysis techniques using deductive reasoning presented descriptively. The results of this research are: first, the position of the Surakarta Kasunanan Palace after Indonesian Independence, based on: Law Number 10 of 1950 was designated as part of Central Java Province; and based on Law Number 18 of 1965, de jure Swaraja Surakarta was abolished. Then, after the UUPA came into force, the position of the Surakarta Kasunanan Palace should have shifted to the State. However, in reality, currently the Surakarta Palace Sultanate still has and exercises authority over the lands it owns and owns based on Presidential Decree Number 23 of 1988. Second, the ownership status of the Surakarta Kasunanan Palace as a cultural heritage area is stipulated in the Regulation of the Minister of Culture and Tourism Number PM.03/PW.007/MKP/2010 belongs to the Surakarta Kasunanan Palace as an indigenous community in accordance with Article 13 of the Cultural Heritage Law. The Surakarta Kasunanan Palace is a traditional community, because the King is the traditional leader who still has the same territorial area and lineage and has authority within and outside his traditional area. If the Kasunanan Surakarta Palace is interpreted as a traditional institution, and ownership of the land of the Surakarta Kasunanan Palace becomes a customary right for the Surakarta Kasunanan Palace, then as a consequence the Government in taking over the land of the former Surakarta self-government must also pay attention to the principle of recognizing these customary rights.

Kazakh-European trade and economic relations

ABSTRACT This paper analyzes Kazakh-European trade and economic relations from 2012 to 2021, aiming to elucidate the dynamics, trends, and strategic implications of these bilateral interactions. The primary purpose of this research is to scrutinize the dynamics of Kazakhstan's trade and economic interactions with European countries, assessing the trends, challenges, and opportunities within this framework. Employing a methodology that combines analysis and synthesis, inductive and deductive reasoning, and statistical methods including ABC analysis in MS Excel, the study provides a comprehensive examination of Kazakhstan's trade volumes, exports, imports, and foreign direct investments with European countries. It was revealed that for the countries of Europe, the indicators of the volume of trade, exports, and imports, gross investments showed a greater drop than in the economy. Summarized information characterizing the institutional aspect of the formation of relations between Kazakhstan and European states highlights Kazakhstan's active participation in international organizations as a key driver in developing these relationships. The findings offer valuable insights for policymakers and business stakeholders, highlighting the need for strategic approaches in optimizing trade and investment relations between Kazakhstan and Europe.

Exploring the typology of reasoning influencing university teachers’ language teaching and learning strategies

Despite the critical role of reasoning in shaping language teaching and learning strategies in higher education, prior studies have either separately examined reasoning or focused on one specific type thereof and language teaching and learning strategies. To address this gap, this study took a comprehensive approach by examining various types of reasoning in language instruction and their alignment with language teaching strategies in higher education. It adopted a sequential mixed-methods design through two phases of data collection. The study instruments included a mixed-method questionnaire, interviews, classroom observations, and document analysis. The quantitative phase collected data from 357 university teachers of Arabic-language disciplines at the university level who completed a mixed-methods questionnaire using a 5-point Likert scale and brief written explanation. Exploratory factor analysis, descriptive and inferential analysis of variance and the Scheffé test were used to analyse the quantitative data. In the follow-up qualitative phase, 20 university teachers from the quantitative phase were observed in the classroom and interviewed, and their document tasks were analysed using thematic analysis. The results unveiled four distinct typologies of university teachers’ reasoning closely aligned with their language teaching and learning strategies: inductive, abductive, analogical, and deductive reasoning. Notably, these typologies were associated with cognitive, metacognitive, interactional, and Knowledge strategies. Furthermore, the findings highlighted the intricate interplay and mixture of these typologies, indicating that university teachers do not rely solely on one type or strategy. Finally, the conclusion section outlines critical areas for future research concerning reasoning and language teaching and learning strategies in higher education.

Balancing Bioethics and Legal Frontiers: А Case Study of Brazil’s Supreme Federal Court Decision on Embryonic Stem Cell Research

Background. The present work focuses on the need to protect prenatal life, which is intricately entwined with delineating the precise biological and legal juncture marking an embryo’s transition into personhood. Drawing upon bioethical insights from domestic frameworks and international jurisprudence, we compare diverse perspectives on the moral and legal standing of the embryo, including its right to life, and invoking legal principles in the context of cellular and regenerative medicine.Aim. The goal of this article is to investigate the various biosafety policy approaches governing embryonic stem cell research, ranging from outright prohibition to authorization solely for therapeutic or scientific ends. Through our analysis, we focus on the unique national context of Brazil to scrutinize the underlying rationale behind a specific legal challenge questioning the constitutionality of the BiosafetyLaw. This law, which permits the utilization of human embryonic cells for research and therapeutic purposes, raises concerns about potential infringement upon the inviolability of the right to life.Methodology. The research is based on deductive reasoning alongside formal-legal methodologies, including textual interpretation and comparative-legal analysis. The research process involved documentary, bibliographic, and virtual analytical inquiries utilizing a variety of resources such as legislative texts, monographs, academic articles, databases, and online libraries. Results. Through our examination in a distinct national context, we delineate the theoretical-philosophical and normative-ethical foundations underpinning the stances of Brazilian Supreme Court justices concerning the utilization of embryonic stem cells. Their arguments predominantly invoked significant constitutional liberties such as freedom of family planning, scientific research, and academic pursuits, intertwined with considerations of human dignity and the sanctity of life. Additionally, some justices cautioned against the potential hazards inherent in genetic manipulation.Implications. The legal and ethical ramifications of Brazil’s approach to biosafety legislation concerning embryo rights invoke the necessity for conducting neutral, unfettered scientific inquiry and regenerative therapies according to specific operational parameters. These include safeguarding the integrity of genetic inheritance, preemptive evaluation of potential risks and benefits (adherence to the precautionary principle), and ensuring informed consent for treatments. A significant hurdle consists in the need to establish robust mechanisms for overseeing research involving human embryos within the domains of biomedicine and regenerative cell therapy

Is the Serpin-Enzyme Complex Receptor an Orphan G-Protein Coupled Receptor?

Alpha-1 antitrypsin (α1-AT) is a member of serine proteinase inhibitors, collectively known as serpins, that inactivate their target enzymes by forming a stabilized serpin-enzyme complex. α1-AT molecules interact with elastase, forming biologically active complexes. It was suggested that the formation of α1-AT-elastase complex would expose a domain from α1-AT molecule that is recognized by a specific cell receptor. Thus, a synthetic peptide, called 105Y, was made based on the sequence of the exposed domain. The peptide binds specifically to human hepatoma HepG2 cells, human monocytes, human neutrophils, and rat pheochromocytoma cells (PC12). This binding is blocked by α1-AT-elastase complex and other serpin-enzyme complexes, suggesting an existence of a specific cell surface receptor, termed SEC receptor, that recognizes serpin enzyme complexes. However, the identity of SEC receptor is still unknown. Thus, we decided to use the Deductive Reasoning Strategy approach to investigate if the SEC receptor belongs to G-protein-coupled receptor (GPCR) family. We measured responsiveness of HepG2 cells as well as human neuroblastoma SHSY5Y cells to 105Y peptide by quantifying their expression of an early response gene c-Fos using real time quantitative polymerase chain reaction (qPCR) and measured their expression of orphan GPCRs using polymerase chain reaction (PCR) followed by gel electrophoresis. Our results indicate that the cells were responding to 105Y peptide and express certain orphan GPCRs. Our goal is to evaluate the necessity of these oGPCRs in 105Y peptide signaling in order to determine the best candidate(s) for the 105Y receptor. These results would shed light on the identity of the SEC receptor for better understanding of the molecular biology and physiology of the serpin-enzyme complexes and their receptors. National Institute of Health. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

The impact of discrete mathematics lectures on students' deductive reasoning: The case of graph theory learning

The impact of discrete mathematics lectures on students' deductive reasoning: The case of graph theory learning

How nurses can promote resilience among adolescents receiving active cancer treatment: A scoping review.

Explore knowledge on resilience-promoting interventions among adolescents receiving active cancer treatment. The question used to guide the research was: How can nurses promote resilience among adolescents receiving active cancer treatment? Adolescence is a very turbulent stage of development (Young, 2014). A cancer diagnosis at this age contributes to emotional distress and reduces quality of life (Sodergren et al., 2017). However, some youth develop positive coping mechanisms that lead to increased resilience (Bellizzi et al., 2012; Sodergren et al., 2017). Because nurses often care for these patients over an extended period of time, they can play an important role in fostering this resilience. Three databases (CINAHL, PubMed and PsycArticles) were consulted in February 2023, using research limiters "2013-2023" and "adolescents" (teenagers) both in French and in English. Potentially relevant sources were selected based on the guidelines identified by Pollock et al., (2021). Data were extracted, analyzed and presented using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist (Tricco et al., 2018). The results were categorized, using deductive reasoning, as either protective factors or risk factors, in line with the Resilience in Illness Model (RIM; (Haase et al., 2014, 2017). Finally, potential interventions were identified where nurses can foster resilience among adolescents actively undergoing cancer treatment. The method used returned 86 studies, 17 of which met the selection criteria. Of these, 10 were quantitative in nature, three were qualitative, three were theoretical (including literature reviews and meta-analyses) and one was an editorial. The majority (n = 15) were published in the United States. There have been no studies specifically examining the role of nurses in promoting resilience among adolescents undergoing active cancer treatment since 2013. Based on the findings of this paper, considering that information has been published on the role nurses serve in caring for adolescents who have a chronic illness other than cancer, the conclusion is that pediatric oncology nurses can be key players in promoting resilience among patients at this stage of development. Studies focusing specifically on this topic would be useful in determining how to facilitate adaptation and foster resilience effectively among adolescents receiving active cancer treatment.

Illusory inferences in conditional expressions.

A robber points a gun at a cashier and says: "Only one of these two options is true: If you conceal the combination to the safe, then I kill you; otherwise, if you don´t conceal the combination to the safe, then I kill you." Hearing this statement, most people conclude that, in either case, "I kill you." This is an illusory response, in fact; the valid conclusion states "I don´t kill you." The research reported here studied the roles that different expressions of conditionals ("if-then," "only if," and "if and only if") play in the illusory response. Three experiments show that participants inferred the conclusion "I kill you" from the conditional "if-then" and "I may or may not kill you" from the conditional "only if," while selecting both options with similar frequency for the biconditional "if and only if." These results shed light on the main theories of deductive reasoning.

Deductive Reasoning and Mathematical Resilience in Complex Analysis

The pre-research data of mathematics prospective teachers in one of the universities in Bandung showed that the deductive reasoning ability in complex analysis was still not at good level. Beside the cognitive aspect, the affective aspect could be considered too in doing learning process, such as mathematical resilience. This study aims to analyze and identify the correlation between deductive reasoning and mathematical resilience in complex analysis. The research was conducted in one of the mathematics education departments of a university in Bandung. Correlation was the method used in this study. Mathematics prospective teachers were the sample of this research. This study concluded that mathematical deductive reasoning of prospective teachers was on a moderate level, the mathematical resilience of prospective teachers was on the positive category, and there was a significant correlation between deductive reasoning and the mathematical resilience of prospective teachers on a moderate level. Keywords: deduktif reasoning, matchematical resilience, complex analysis

Impact of Social Media Sentiments on Stock Market Behavior: A Machine Learning Approach to Analyzing Market Dynamics

Social media has become a valuable tool for informed decision-making. This research delves into the influence of Twitter sentiments on the stock market’s movements and price fluctuations, specifically focusing on Tesla Inc and the tweets of Elon Musk. A combination of deductive and inductive reasoning approaches is used to explore the intricate relationship between the social media platform and the stock market. Methodologically, the Twitter data undergoes rigorous processing to derive features for the machine learning predictive model, and the sentiments are extracted using the Valence Aware Dictionary and Sentiment Reasoner (VADER) tool. This study emphasizes the usefulness of social media in predictive modeling while underscoring the importance of evaluating data reliability considering challenges such as spam tweets and geographical relevance. Multiple machine learning models are tested against four distinct datasets addressing the high stock price volatility. XG Boost and Random Forest Regressor emerge as the most effective performers, particularly when moving averages are included, showing enhanced performance. This research establishes an evident correlation between social media sentiments and stock market movements, however with limited predicting power. It is also noted that integrating traditional financial metrics enriches the understanding of stock market dynamics while enhancing the model’s predictability.

FGeo-DRL: Deductive Reasoning for Geometric Problems through Deep Reinforcement Learning

Human-like automatic deductive reasoning has always been one of the most challenging open problems in the interdisciplinary field of mathematics and artificial intelligence. This paper is the third in a series of our works. We built a neural-symbolic system, named FGeo-DRL, to automatically perform human-like geometric deductive reasoning. The neural part is an AI agent based on deep reinforcement learning, capable of autonomously learning problem-solving methods from the feedback of a formalized environment, without the need for human supervision. It leverages a pre-trained natural language model to establish a policy network for theorem selection and employ Monte Carlo Tree Search for heuristic exploration. The symbolic part is a reinforcement learning environment based on geometry formalization theory and FormalGeo, which models geometric problem solving (GPS) as a Markov Decision Process (MDP). In the formal symbolic system, the symmetry of plane geometric transformations ensures the uniqueness of geometric problems when converted into states. Finally, the known conditions and objectives of the problem form the state space, while the set of theorems forms the action space. Leveraging FGeo-DRL, we have achieved readable and verifiable automated solutions to geometric problems. Experiments conducted on the formalgeo7k dataset have achieved a problem-solving success rate of 86.40%.

FGeo-TP: A Language Model-Enhanced Solver for Euclidean Geometry Problems

The application of contemporary artificial intelligence techniques to address geometric problems and automated deductive proofs has always been a grand challenge to the interdisciplinary field of mathematics and artificial intelligence. This is the fourth article in a series of our works, in our previous work, we established a geometric formalized system known as FormalGeo. Moreover, we annotated approximately 7000 geometric problems, forming the FormalGeo7k dataset. Despite the fact that FGPS (Formal Geometry Problem Solver) can achieve interpretable algebraic equation solving and human-like deductive reasoning, it often experiences timeouts due to the complexity of the search strategy. In this paper, we introduced FGeo-TP (theorem predictor), which utilizes the language model to predict the theorem sequences for solving geometry problems. The encoder and decoder components in the transformer architecture naturally establish a mapping between the sequences and embedding vectors, exhibiting inherent symmetry. We compare the effectiveness of various transformer architectures, such as BART or T5, in theorem prediction, and implement pruning in the search process of FGPS, thereby improving its performance when solving geometry problems. Our results demonstrate a significant increase in the problem-solving rate of the language model-enhanced FGeo-TP on the FormalGeo7k dataset, rising from 39.7% to 80.86%. Furthermore, FGeo-TP exhibits notable reductions in solution times and search steps across problems of varying difficulty levels.

Teaching Fin Regeneration Using a Dominant Negative Receptor.

Rising in popularity as a model organism in the classroom, zebrafish have numerous characteristics that make them ideal for teaching. In this study, we describe an experiment that helps students better understand the concept of tissue regeneration and the genes that control it. This experiment utilizes a dominant negative transgene for fgfr1 and allows students to observe the consequences of its activation. The first part of the laboratory is hands-on, and includes details of the amputation of caudal fins, heat shocking, general fish care, and visual observations. Over the course of a week, students observed the differences between the activated and unactivated transgene in the zebrafish. The second part was literature based, in which students tried to determine which gene is responsible for inhibiting regeneration. This encouraged students to sharpen their skills of deductive reasoning and critical thinking as they conduct research based on the information they receive about dominant negative receptors and transgenes. Having both a hands-on and critical thinking component in the laboratory helped synthesize the learning goals and allowed students to actively participate.

Deductive Reasoning Based on the Valid Aristotelian Syllogism AEE-2

This paper firstly formalizes Aristotelian syllogisms based on the tripartite structure of categorical propositions, and then uses the truth definitions of categorical propositions to prove the validity of the Aristotelian syllogism AEE-2. Then, the remaining 23 valid syllogisms are derived from the syllogism AEE-2 with the help of relevant facts, inner and outer negation definitions of quantifiers, and deductive rules. In other words, this paper reveals the reducible relationship between/among these 24 syllogisms and establishes a succinct formal reason system for Aristotelian syllogistic. The deductive reasoning not only ensures consistency in its results, but also provides a concise mathematical paradigm for other types of syllogisms.

The Relationship Between Individual Social Capital and Life Satisfaction Among University Students in China: The Mediating Role of Resiliency

This present paper has aimed to investigate the university students’ life satisfaction in the city of Ji’nan in China. Due to the important role of university students, their life satisfaction has been valuable and necessary to be examined. The extent literature about students’ life satisfaction has left a blank for the three variables in the study. Therefore, this paper has tried to give an explanation for the relationship among university students’ life satisfaction and individual social capital by the mediating effect of resilience, which may be a new conceptual model seldom conducted in previous studies, especially in Ji’nan. As a non-experimental descriptive research design, a quantitative (deductive reasoning) technique has been employed to quantify the issue, in which survey questionnaire has been used to gather numerical data and then turned into practical statistics.

Antecedents of Staff Attrition

Addressing turnover has consistently remained a pivotal concern across industries. Mitigating turnover can empower organizations to retain their crucial personnel, consequently fostering heightened productivity and potentially bolstered profitability. This study delves into the correlation between employees' perception of organizational politics and the lure of alternative job offers featuring better compensation as drivers of turnover among Bank Alfalah (Karachi) personnel. Employing a cross-sectional approach with deductive reasoning, this study collected responses through survey questionnaires from Bank Alfalah employees. The outcomes unveiled a noteworthy positive association between turnover and both perceived organizational politics and the appeal of higher-paying alternative job opportunities. Additionally, the study unearthed that office politics plays a more robust role in translating turnover intentions into decisions. These findings bear significant implications not only for the banking sector but also for theoretical advancements in research centered around organizational politics and the allure of enhanced compensation through alternative employment avenues.

Exploring the role of palliative care occupational therapists in supporting compassionate communities in end-of-life care.

The compassionate communities' movement is a public health approach to end-of-life care that emphasises the integral role of communities in supporting and caring for dying persons and their informal carers. Although occupational therapists have well-established roles in palliative care teams, little is known about their potential in assisting in the formation and maintenance of compassionate communities. Data were gathered via semi-structured interviews with nine Australian occupational therapists with experience in specialist palliative care. Interview questions were based around the British Columbia Compassionate Community Ideal framework. Key themes were derived through qualitative descriptive analysis, blending deductive, and inductive reasoning. Interviewees indicated that occupational therapists have a role in supporting compassionate communities that centres on the facilitation of networks and connections between palliative care professionals and in the promotion of informal care networks. The importance of education and awareness raising were also discussed as valuable to the development of community capacity. It was also suggested that occupational therapists have important skills to support dying persons and their caregivers to remain engaged and safe in their homes and communities, in a meaningful and sustainable way. However, many interviewees maintained a profession-centric view on control within compassionate communities, as opposed to approaches that are community led. Findings offer early insights into the promise and potential of occupational therapists in supporting the compassionate communities' movement. However, education regarding the ethos of the compassionate communities' movement so as to facilitate a shift away from professionally oriented modes of practice may be needed to maximise success.

Eating alone or together: Exploring university students’ eating patterns before and during the COVID-19 pandemic

Commensality with close friends and acquaintances increases opportunities for social connectedness, creates a sense of belonging, and may reduce the risks of isolation among students. The outbreak of COVID-19 pandemic and the subsequent lockdown disrupted daily routines and relationships. This put an increased number of university students at risk of emotional and social loneliness. Little research has focused on commensal eating practices and loneliness among university students before or during the COVID-19 pandemic in the UK or elsewhere. This study explored these themes using one-to-one interviews with 13 undergraduate and postgraduate students at a university in England. A hybrid approach to thematic analysis of deductive and inductive reasoning was adopted which is data-driven but informed a priori by the research questions. Emergent findings include (1) pre-COVID-19 eating practices: meal-skipping, varying lunch-time rituals, and dinner as the most important meal regarding content and commensality; (2) Eating practices during COVID-19 lockdown: healthier eating patterns, limited opportunities for commensality, increased feelings of loneliness, and increased reliance on digital media. The COVID-19 lockdown was an opportunity for students to transform erratic eating into more regular eating practices and patterns and to cook more homemade meals. Many students were alone during dinner time and expressed increased feelings of loneliness leading to increased reliance on digital media and virtual commensality to socially interact with close family and friends whilst enjoying the meal.

Learning distributed representations of knowledge that preserve deductive reasoning

Deep neural networks have shown promise in various fields including image processing, natural language processing and speech processing. Despite their proven usefulness in both theory and empirical studies, significant difficulties in their application still persist. More specifically, enabling deep neural networks to reason over data for knowledge acquisition is arguably challenging. Neural networks have the ability to learn patterns and generalize over data but often lack model interpretability, i.e., it is not always clear how they reason over data. Enabling neural networks to symbolically reason is one way to bring explainability and improve knowledge acquisition. In this paper, we introduce a Deduction-Preserved Embedding (DPE) model designed to learn a distributed representation that integrates symbolic deductive reasoning. Our approach effectively incorporates symbolic rules, resulting in enhanced link prediction performance for knowledge graph completion. Our experimental results highlight that the proposed model consistently outperforms baseline methods, demonstrating superior overall performance despite having a relatively small number of parameters. Notably, the version of the model that incorporates symbolic rules surpasses the majority of compared models, particularly in scenarios characterized by data sparsity.

Applying Machine Learning to Construct a Printed Circuit Board Gold Finger Defect Detection System

Machine vision systems use industrial cameras’ digital sensors to collect images and use computers for image pre-processing, analysis, and the measurements of various features to make decisions. With increasing capacity and quality demands in the electronic industry, incoming quality control (IQC) standards are becoming more and more stringent. The industry’s incoming quality control is mainly based on manual sampling. Although it saves time and costs, the miss rate is still high. This study aimed to establish an automatic defect detection system that could quickly identify defects in the gold finger on printed circuit boards (PCBs) according to the manufacturer’s standard. In the general training iteration process of deep learning, parameters required for image processing and deductive reasoning operations are automatically updated. In this study, we discussed and compared the object detection networks of the YOLOv3 (You Only Look Once, Version 3) and Faster Region-Based Convolutional Neural Network (Faster R-CNN) algorithms. The results showed that the defect classification detection model, established based on the YOLOv3 network architecture, could identify defects with an accuracy of 95%. Therefore, the IQC sampling inspection was changed to a full inspection, and the surface mount technology (SMT) full inspection station was canceled to reduce the need for inspection personnel.