Notion Of Complexity Research Articles

Maintaining Agricultural Production Profitability—A Simulation Approach to Wheat Market Dynamics

Profitability is a complex notion, intertwined with theoretical, socio-economic, and modern economic considerations. While traditionally linked to monopoly advantages, contemporary views broaden this to include shareholder value creation. In agriculture, profitability faces impediments such as rising input costs, market volatility, and economic disparities, emphasizing technological innovation, market conditions, and policy as crucial determinants. This study presents an econometric simulation model to analyze and forecast wheat production profitability in Poland from 2023 to 2027, providing insights into production efficiencies, market dynamics, and policy impacts. Using a system of recursive equations, the model forecasts profitability, integrating econometric techniques with expert insights. It examines variables like resource use, production levels, and price changes, validated through FADN data. The findings reveal that price relations and production efficiencies are the key to profitability. The model highlights market volatility, particularly through “price scissors”, as the main factor influencing profitability. Favorable price conditions significantly boost profitability and incentivize production. The model is a critical tool for analyzing wheat profitability, highlighting the influence of market and policy changes. Future work could extend the model’s use to other regions or crops, incorporating advanced technologies to improve accuracy. This study offers valuable insights for agricultural economics, aiding stakeholders in strategic decision-making.

From Play to Understanding: Large Language Models in Logic and Spatial Reasoning Coloring Activities for Children

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box-and-ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context—Zero-Shot, Few-Shot, Chain of Thought, Visualization of Thought, Self-Consistency, logicLM, and emotional —to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self-Consistency techniques enabled GPT-4o to correctly evaluate 90% of the logical–spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.

Comparing the complexity of written and molecular symbolic systems

Symbolic systems (SSs) are uniquely products of living systems, such that symbolism and life may be inextricably intertwined phenomena. Within a given SS, there is a range of symbol complexity over which signaling is functionally optimized. This range exists relative to a complex and potentially infinitely large background of latent, unused symbol space. Understanding how symbol sets sample this latent space is relevant to diverse fields including biochemistry and linguistics.We quantitatively explored the graphic complexity of two biosemiotic systems: genetically encoded amino acids (GEAAs) and written language. Molecular and graphical notions of complexity are highly correlated for GEAAs and written language. Symbol sets are generally neither minimally nor maximally complex relative to their latent spaces, but exist across an objectively definable distribution, with the GEAAs having especially low complexity. The selection pressures guiding these disparate systems are explicable by symbol production and disambiguation efficiency. These selection pressures may be universal, offer a quantifiable metric for comparison, and suggest that all life in the Universe may discover optimal symbol set complexity distributions with respect to their latent spaces. If so, the “complexity” of individual components of SSs may not be as strong a biomarker as symbol set complexity distribution.

Evolving scientific discovery by unifying data and background knowledge with AI Hilbert

The discovery of scientific formulae that parsimoniously explain natural phenomena and align with existing background theory is a key goal in science. Historically, scientists have derived natural laws by manipulating equations based on existing knowledge, forming new equations, and verifying them experimentally. However, this does not include experimental data within the discovery process, which may be inefficient. We propose a solution to this problem when all axioms and scientific laws are expressible as polynomials and argue our approach is widely applicable. We model notions of minimal complexity using binary variables and logical constraints, solve polynomial optimization problems via mixed-integer linear or semidefinite optimization, and prove the validity of our scientific discoveries in a principled manner using Positivstellensatz certificates. We demonstrate that some famous scientific laws, including Kepler’s Law of Planetary Motion and the Radiated Gravitational Wave Power equation, can be derived in a principled manner from axioms and experimental data.

Improved Intrusion Detection in the Internet of Things: A Multi-Layered Neural Network Approach and Analysis

The (IoT) Internet of Things is a complex notion that refers to the interconnection of several individual devices over a network (IoT). The data gathered by these interconnected devices have the potential to have far-reaching consequences for human society, the economy, and the environment. The IoT is especially vulnerable to a variety of vulnerabilities in hostile environments like the internet. High-end security solutions are not adequate to safeguard an IoT system due to adequate storage and less processing capabilities. This emphasizes the need for ascendable, strewn, and robust smart security solutions. In this study, IoT networks are safeguarded depleting a multiple-layered security strategy centered on deep learning. The proposed architecture employs the use of three intrusion detection datasets CIC-IDS, BoT-IoT, and ToN-IoT to weigh the performance of the insinuated multiple-layered approach. Irrevocably, compared to 92% accuracy for the existing methodologies, the new layout obtained 98% accuracy.

Prolegomena to the study of Youxi Sanmei 遊戲三昧 Buddhist sacred play between agonism and mimicry

ABSTRACT This article outlines a genealogical profile of an elusive doctrinal concept that, after being discussed in several Mahāyāna sutras, had a significant impact on East Asian Buddhist traditions. This notion is known as ‘playful samādhi’, in Chinese youxi sanmei 遊戲三昧, which translates to Sanskrit vikrīḍita samādhi. The compound youxi 遊戲 (‘playful’ – ‘at play’) was cited in Chinese sutras and Buddhist documents, in renowned and widely diffused collections of gongans/kōans 公案, was expounded and commented on by Dōgen Zenji 道元禅師 (1200–1253) in its Japanese version yuge 遊戲 and was explored by modern scholars and interpreters as Ryōsuke Ōhashi 大橋良介 and Wu Rujun 吳汝均, who compares youxi 遊戲 with Schiller’s Spieltrieb . Given the significance of ‘playful samādhi’ across different epochs and cultures, I believe a clarification of the term is especially needed. Furthermore, explicit reference to contemporary scholarship on play studies can help uncover its philosophical implications, shedding new light on a complex notion that defies a univocal interpretation and reunites in its semantic field both the aesthetic and religious dimensions.

The essence of dance. A study of Chinese and Western dance philosophy: socio-cultural, historical and educational aspects

ABSTRACT The art of dance is an intangible cultural heritage that occupies a special place in the social and cultural policy of China. The purpose of this research is to identify the specifics of Chinese and Western dance philosophy. The dance philosophy is a complex notion, which is possible to study through various research methods, including the following: dialectical, semiotic, specific historical, socio-cultural and analytical as well as expert evaluation. This study concludes that the philosophical framework of Chinese and Western dance art plays an essential role. The authors developed a conceptual framework for understanding Chinese and Western dance philosophies. The research revealed that the unique traditions of Chinese national dance are an integral part of the country’s cultural heritage and reflect the philosophical aspects of dance within the multicultural environment. The research results can be used in dance pedagogy, choreography, and dance lessons to improve the techniques and skills of dancers. Further research is needed to compare the philosophies of Chinese folk dances and Western folk dances from different countries and historical periods.

Klass, kön och Shakespeare

Class, gender and Shakespeare. Elise Karlsson's Smuts This essay suggests that the use of Shakespeare in Elise Karlsson’s novel Smuts (2021) serves to accentuate and develop the novel’s thematic focus on work, precarity, class, and gender. Revolving around a production of A Midsummer Night’s Dream at a fictitious theatre in Stockholm, Smuts aligns itself with tendencies in Karlsson’s previous work as well as in contemporary Swedish literature: as an assistant script editor, its narrator is a freelance worker in an economy where work is precarious and perceived—despite the supposedly high status of her work in the cultural sector—as badly paid and, literally, meaningless. Shakespeare’s play becomes a focal point for these themes not just because of the extensive character parallels with Smuts, but also because the complex notions of class, work and female subjugation in Karlsson’s novel can be seen as developments of themes that are very much present in the play. In other words, Smuts is a good example of contemporary ‘working-class literature’ in Sweden, and as the essay suggests, it builds up its focus on precarity, class, and gender by means of intertextual parallelisms with Shakespeare.

Assessing the Adequacy of Contemporary Life and Earth Textbook in Morocco: A Case Study of Blood Glucose Regulation

Blood glucose homeostasis is a fundamental concept in biology. Yet, in the Moroccan education system, it is only covered in the 11th grade. This might explain why the majority of students struggle to understand this complex notion. Fingers of blame are also pointed to textbooks and how they didactically (mis)transposed this knowledge from its academic form to its teachable one. In fact, the significance of textbooks in education is indisputable. Hence, analyzing them may provide insights on students (mis)conceptions. In this study, we aim to critically analyze the sections on blood glucose regulation in two widely-used Life and Earth Sciences textbooks in Morocco, intended for students enrolled in the experimental sciences track. To do so, the present study follows the findings and recommendations of the intriguing systematic review of literature by Vojíř & Rusek (2019) which urges for the need for science textbooks research in different local contexts around the globe. In the same vein, the absence of such research in the Moroccan context makes this study an obligation. Methodologically, this study adopted Bernard et al’s.,(2007) contrastive approach. According to our findings, the juxtaposition of these two textbooks reveals several shortcomings, errors, and inconsistencies. By taking the didactic transposition of blood glucose homeostasis into the heart of its exploration, this study –though rooted in its Moroccan context- advocates for a wider applicability of its findings.

Photography at a Standstill

What has replaced the still photograph are dynamic and distributed image-assemblages that unsettle received notions of space-time — no longer limited to traditional representation and not necessarily even visual. When it comes to computer vision for example, the descriptor photography seems largely redundant (despite deep learning computer vision systems being trained on large datasets of photographic images), and so too the tired metaphor of the eye that once supported its theories and practices. What is at stake here, as ever, is a kind of ‘seeing’ (if we continue to call it that) that makes clear what is visible, sensible and knowable, and crucially also what is not. We might call this seeing algorithmically, or seeing like a dataset, or perhaps even seeing like an infrastructure, comprised of fake images that render fake history. The logic of this invokes the complex notion of ‘image is dialectics at a standstill’, encapsulating a constellation of possible outcomes. To what extent is the radical potential that Benjamin once foresaw in montage applicable to image-based AI given that it seems less an instrument to imagine a qualitatively different future but simply more of the same. What can be seen is not so much representational nor photographic but latent traces of material relations and infrastructures that render historical experience in compromised form.

Exploring Stylistic analysis of lexical layer: An In-depth Study of Abdul Qayum Qawim's Poetry

The 'multi-layered stylistics' approach is a contemporary method for examining and evaluating the lexical, phonetic, syntactic, rhetorical, and ideological aspects within a text. Through the application of multi-layer stylistics, it is possible to discern the distinctive characteristics of an individual's style, thoughts, and ideologies that shape a poet or writer's written compositions. The aim of this study is to analyze and assess the lexical characteristics of a poem compilation written by Abdul Qayum Qawim. The objective is to determine the degree to which a thorough analysis and study of complex notions, such as sensuous, abstract, wonderful, slangy, and others, has been conducted at the level of language. The research employed a descriptive-analytical strategy by utilizing the library technique. This work meticulously analyzes the lexical layer of Abdul Qayum Qawim's poetry using a comprehensive stylistic analysis approach. The research is structured into two primary sections: initially, a comprehensive analysis of the poem's lexical layer is undertaken, followed by a meticulous examination of the poem's theoretical aspects. This study explores the concepts of ideology and investigates several themes like moral evaluation, societal dissatisfaction, pessimism, the passage of time, lack of mutual comprehension, concern towards instability, and the avoidance of hypocrisy. Its aim is to enlighten the general public through the use of uncomplicated poetry that highlights the abundance and vitality of spring. The research indicates that the poet exhibited a profound comprehension and extensive knowledge of contemporary affairs by skillfully portraying diverse social realities through the significance of his verses. Furthermore, the poet's method demonstrated a keen focus on the underlying meanings inside the text, highlighting the convergence of time, conceptual ideas, and human experiences, alongside the utilization of descriptive language that appeals to the senses.

The power to transform structures: power complexes and the challenges for realising a wellbeing economy

This article draws on different strands of existing scholarship to provide an analytical framework for understanding the barriers to achieving a well-being economy. It explores the interplay between agential and structural power, where some actor-coalitions can reproduce or transform pre-existing structures. Conversely, these structures are strategically selective, favouring some actors, interests, and strategies over others. Making sense of this interplay between agential and structural power, the article introduces the notion of power complexes—time-space-specific actor-coalitions with common industry-related interests and the power to reproduce or transform structures in a given conjuncture. To understand the historical “becoming” of today’s political-economic terrain, the article provides a regulationist-inspired history of the rise, fall, and re-emergence of four power complexes: the financial, fossil, livestock-agribusiness, and digital. They pose significant threats to pillars of a wellbeing economy such as ecological sustainability, equ(al)ity, and democracy. Subsequently, today’s structural context is scrutinised in more detail to understand why certain actors dominate strategic calculations in contemporary power complexes. This reveals strategic selectivities that favour multi- and transnational corporate actors over civil society, labour movements, and public bureaucracies. The article then examines firm-to-state lobbying as a strategy employed by corporate actors within today’s structural context to assert their interests. It presents illustrative cases of Blackstone, BP, Bayer, and Alphabet. Finally, it explores implications and challenges for realising a wellbeing economy based on post-/degrowth visions. It emphasises the double challenge faced by such a wellbeing-economy actor-coalition. On one hand, it has to navigate within contemporary modes of regulation that favour corporate strategies of capital accumulation while, on the other, it must confront the self-expanding and extractive logic of capital. In this context, three key challenges are outlined: the need to form unconventional strategic alliances, operate on various spatial dimensions simultaneously, and institutionalise alternatives to firm-to-state lobbying to influence policymaking.

Complexity in tame quantum theories

Inspired by the notion that physical systems can contain only a finite amount of information or complexity, we introduce a framework that allows for quantifying the amount of logical information needed to specify a function or set. We then apply this methodology to a variety of physical systems and derive the complexity of parameter-dependent physical observables and coupling functions appearing in effective Lagrangians. In order to implement these ideas, it is essential to consider physical theories that can be defined in an o-minimal structure. O-minimality, a concept from mathematical logic, encapsulates a tameness principle. It was recently argued that this property is inherent to many known quantum field theories and is linked to the UV completion of the theory. To assign a complexity to each statement in these theories one has to further constrain the allowed o-minimal structures. To exemplify this, we show that many physical systems can be formulated using Pfaffian o-minimal structures, which have a well-established notion of complexity. More generally, we propose adopting sharply o-minimal structures, recently introduced by Binyamini and Novikov, as an overarching framework to measure complexity in quantum theories.

Towards Improved Auditory-Perceptual Assessment of Timbres: Comparing Accuracy and Reliability of Four Deconstructed Timbre Assessment Models

Timbre is a central quality of singing, yet remains a complex notion poorly understood in psychoacoustic studies. Previous studies note how no single acoustic variable or combinations of variables consistently predict timbre dimensions. Timbre varies on a continuum from darkest to lightest. These extremes are associated with laryngeal and vocal tract adjustments related to smaller and larger vocal tract area and variations in vocal fold vibratory characteristics. Perceptually, timbre assessment is influenced by spectral characteristics and formant frequency adjustments, though these dimensions are not independently perceived. Perceptual studies repeatedly demonstrate difficulties in correlating variations in timbre stimuli to specific measures. A recent study demonstrated how acoustic predictive salience of voice category and voice weight across pitches contribute to timbre assessments and concludes that timbre may be related to as-of-yet unknown factor(s). The purpose of this study was to test four different models for assessing timbre; one model focused on specific anatomy, one on listener intuition, one utilising auditory anchors, and one using expert raters in a deconstructed timbre model with 5 specific dimensions. MethodsFour independent panels were conducted with separate cohorts of professional singing teachers. 41 assessors took part in the anatomically focused panel, 54 in the intuition-based panel, 30 in the anchored panel, and 12 in the expert listener panel. Stimuli taken from live performances of well-known singers were used for all panels, representing all genders, genres, and styles across a large pitch range. All stimuli are available as supplementary materials. Fleiss’ kappa values, descriptive statistics, and significance tests are reported for all panel assessments. ResultsPanel 1 through 4 varied in overall accuracy and agreement. The intuitionbased model showed overall 45% average accuracy (SD ±4%), k=0.289 (<0.001) compared to overall 71% average accuracy (SD ±3%), k=0.368 (<0,001) of the anatomical focused panel. The auditory-anchored model showed overall 75% average accuracy (SD ±8%), k=0.54 (<0.001) compared with overall 83% average accuracy and agreement of k=0.63 (<0.001) for panel 4. Results revealed that highest accuracy and reliability was achieved in a deconstructed timbre model and that providing anchoring improved reliability but with no further increase in accuracy. ConclusionDeconstructing timbre into specific parameters improved auditory perceptual accuracy and overall agreement. Assessing timbre along with other perceptual dimensions improves accruacy and reliability. Panel assessors’ expert level of listening skills remain an important factor in obtaining reliable and accurate assessments of auditory stimuli for timbre dimensions. Anchoring improved reliability but with no further increase in accuracy. The study suggests that timbre assessment can be improved by approaching the percept through a prism of 5 specific dimensions each related to specific physiology and auditory-perceptual subcategories. Further tests are needed with framework-naïve listeners, non-musically educated listeners, artificial intelligence comparisons, and synthetic stimuli to further test the reliability.

Binary sequence family with both small cross-correlation and large family complexity

Ahlswede, Khachatrian, Mauduit and Sárközy introduced the notion of family complexity, Gyarmati, Mauduit and Sárközy introduced the cross-correlation measure for families of binary sequences. It is a challenging problem to find families of binary sequences with both small cross-correlation measure and large family complexity. In this paper we present a family of binary sequences with both small cross-correlation measure and large family complexity by using the properties of character sums and primitive normal elements in finite fields.

Statistical Complexity of Quantum Learning

AbstractLearning problems involve settings in which an algorithm has to make decisions based on data, and possibly side information such as expert knowledge. This study has two main goals. First, it reviews and generalizes different results on the data and model complexity of quantum learning, where the data and/or the algorithm can be quantum, focusing on information‐theoretic techniques. Second, it introduces the notion of copy complexity, which quantifies the number of copies of a quantum state required to achieve a target accuracy level. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. As a result, empirical risk minimization is generally inapplicable. The paper presents novel results on the copy complexity for both training and testing. To make the paper self‐contained and approachable by different research communities, an extensive background material is provided on classical results from statistical learning theory, as well as on the distinguishability of quantum states. Throughout, the differences between quantum and classical learning are highlighted by addressing both supervised and unsupervised learning, and extensive pointers are provided to the literature.

By another's death?

In South Africa, the rhetoric of reconciliation is complex and contested. Indeed, reconciliation itself is viewed as “a controversial symbol”. In part, this may have to do with the different ways in which theological and social, political understandings drive the conceptualisation of reconciliation in South Africa. Within the theological tradition, salvation has long been portrayed by way of the metaphor of reconciliation, and many theologians have engaged the fruitful but potentially confusing difference in assumptions regarding what reconciliation is and requires of us. For a thicker, more robust theological concept of reconciliation, it may be important to consider what the intended use is of this complex notion when employed as a soteriological concept. This article explores David Kelsey’s portrayal of reconciliation by another’s death with some suggestions for contours of a soteriological grammar of reconciliation that could shape more lifegiving ways of speaking about reconciliation in South Africa today.

Characterization and Quantitative Assessment of Shale Fracture Characteristics and Fracability Based on a Three-Dimensional Digital Core

At present, assessment techniques for the fracability of shale reservoirs, which rely on the formation of an effective fracture network, are scarce. Hence, in order to assess the fracability, it is critical to establish a quantitative correlation between the pattern of fracture distribution after fracture and fracability. The present investigation utilizes three-dimensional digital core technology and triaxial compression experiments to simulate the fracturing process in typical domestic shale reservoir cores. In addition to utilizing the maximum ball algorithm to extract fracture images, a number of other techniques are employed to compute the spatial quantitative parameters of the fractures, including least squares fitting, image tracking algorithms, and three-dimensional image topology algorithms. The introduction of the notion of three-dimensional fracture complexity serves to delineate the degree of successful fracture network formation subsequent to fracturing. A quantitative fracability characterization model is developed by integrating the constraints of fracture network formation potential and fragmentation potential. The results of this study show that the quantitative characterization of the characteristic parameters of cracks can be achieved by establishing a method for extracting crack information as well as parameters after core compression and completing the construction of a three-dimensional complexity characterization model. Meanwhile, the three-dimensional post-compression fracture image validation shows that the core fracturability index can better reflect the actual fracturing situation, which is in line with the microseismic monitoring results, and significantly improves the accuracy of fracturability characterization, which is an important guideline for the fracturing design of shale gas reservoirs.

Structure discovery in PAC-learning by random projections

High dimensional learning is data-hungry in general; however, many natural data sources and real-world learning problems posses some hidden low-complexity structure that permit effective learning from relatively small sample sizes. We are interested in the general question of how to discover and exploit such hidden benign traits when problem-specific prior knowledge is insufficient. In this work, we address this question through random projection’s ability to expose structure. We study both compressive learning and high dimensional learning from this angle by introducing the notions of compressive distortion and compressive complexity. We give user-friendly PAC bounds in the agnostic setting that are formulated in terms of these quantities, and we show that our bounds can be tight when these quantities are small. We then instantiate these quantities in several examples of particular learning problems, demonstrating their ability to discover interpretable structural characteristics that make high dimensional instances of these problems solvable to good approximation in a random linear subspace. In the examples considered, these turn out to resemble some familiar benign traits such as the margin, the margin distribution, the intrinsic dimension, the spectral decay of the data covariance, or the norms of parameters—while our general notions of compressive distortion and compressive complexity serve to unify these, and may be used to discover benign structural traits for other PAC-learnable problems.

High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm

Overparameterization often leads to benign overfitting, where deep neural networks can be trained to overfit the training data but still generalize well on unseen data. However, it lacks a generalized asymptotic framework for nonlinear regressions and connections to conventional complexity notions. In this paper, we propose a generalized high-dimensional analysis for nonlinear regression models, including various nonlinear feature mapping methods and subsampling. Specifically, we first provide an implicit regularization parameter and asymptotic equivalents related to a classical complexity notion, i.e., effective dimension. We then present a high-dimensional analysis for nonlinear ridge regression and extend it to ridgeless regression in the under-parameterized and over-parameterized regimes, respectively. We find that the limiting risks decrease with the effective dimension. Motivated by these theoretical findings, we propose an algorithm, namely RFRed, to improve generalization ability. Finally, we validate our theoretical findings and the proposed algorithm through several experiments.