Reasonable Complexity Research Articles

A Highly Resolved Speleothem δ13C Record from Central China and Its Manifestation on Multiple Time Scales during the Last Glacial

Speleothem δ13C in monsoonal China differs from speleothem δ18O, which is widely used as a climatic proxy for several complex control reasons. Nevertheless, δ13C records have the potential to reveal the implications of hydroclimatic changes. This study reports a speleothem δ13C record from Didonghe (DDH) Cave in central China spanning 34 to 13 kyr BP. After we investigated the factors that influence speleothem δ13C, we found that the δ13C record showed that DDH Cave can prompt directional shifts via local hydroclimatic changes, such as in vegetation types, biomass, and rock–water interaction processes, suggesting that δ13C is mainly controlled by the local hydroclimate. Ensemble empirical mode decomposition (EEMD) results revealed a coupling relationship between δ18O and δ13C on multiple timescales, which suggested that changes in precipitation caused by large-scale monsoonal circulation are controlled by regional hydrological conditions to a great extent. However, the hydrological conditions of the cave were relatively mild and humid during the last glacial maximum (LGM), which revealed the impact of evaporation on changes in the region’s hydrological conditions. We also found that the δ18O and δ13C profiles decoupled when δ13C changed with a shift in the location of the westerly during HS1. The δ13C record correlates well with other paleoclimate records, suggesting that regional hydrological conditions are also modulated by the Earth’s internal and external driving factors.

A reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph

AbstractThe lack of multidimensional knowledge means that current reasoning methods for rice fertilization cannot make decisions accurate when faced with complex spatiotemporal conditions in general. Therefore, we propose a reasoning method for rice fertilization strategy based on spatiotemporal knowledge graph. First, we systematically organize multisource expert knowledge about rice fertilization, and construct an ontology for rice fertilization consisting of five core elements: rice variety, planting environment, nutrition diagnosis, fertilization schemes, and time and place. Spatiotemporal differences in rice fertilization knowledge are expressed by assessing spatiotemporal concepts, relations, and state instances. Second, we propose a reasoning method for rice fertilization strategy based on the constructed knowledge graph. This method leverages a certainty factor model for nutrition diagnosis and integrates case‐based and rule‐based reasoning to determine fertilization schemes for different stages. Finally, taking Pucheng County, China, as an example, knowledge from crowd‐sensing data is obtained to construct a knowledge graph using the proposed method. The results demonstrate the method can support the expression and complex reasoning of rice fertilization decisions under different spatiotemporal conditions.

A Qualitative Appraisal of Job Exits Pervasiveness among Small and Medium Businesses in South West Zone of Nigeria

This paper primarily examines the degree of Employee Turnover occurrence in the manufacturing and service SMEs in Southwestern Nigeria. The study adopted qualitative methodology, using interview technique to collect primary data from employees, owners and managers of the businesses. Forty-five in-depth interviews were conducted in the businesses in four of six southwestern states. The collected data was analysed using NVIVO Qualitative Data Analysis Software (QDAS). Research results revealed multiple exits of employees within a short period; exits also appeared common among professionals (e.g. accountants) and casual workers. Generally, high and frequent exits are rife amongst employees. Some of the complex reasons for leaving include inadequate remuneration, job casualisation, inability to provide for family members, poor condition of service, stress, victimisation and fear of the unknown. In conclusion, some owners and managers are still indifferent to the high level of employee turnover, creating the potential for further crises, including business collapse.

Analysing students' concept mapping style and its association with task performance in computer‐based inquiry learning

AbstractBackgroundIn scientific inquiry learning, students often have difficulties conducting hypothetical reasoning with multiple intertwined variables. Concept maps have a potential to facilitate complex thinking and reasoning. However, there is little investigation into the content of student‐constructed concept maps and its association with inquiry task performance.ObjectivesThis study explored students' concept mapping style and its association with task performance in computer‐based inquiry learning.MethodsAn exploratory study was conducted with 80 Grade 11 students, who collaboratively constructed concept maps in a free style to support inquiry learning with a virtual ecosystem. Student‐constructed concept maps was analysed by firstly identifying different types of propositions formed in the maps and then determining the style of each concept map based on the dominant type of propositions in the map. Finally, the association between the concept map style and inquiry task performance was explored.Results and ConclusionsTwo major concept map styles were identified: (1) knowledge‐oriented concept maps (KCMs) mainly representing problem‐related subject knowledge as a set of concepts and their relationships, and (2) problem‐oriented concept maps (PCMs) mainly representing problem situation as a sequence of changes and their causal relationships. Compared with those constructing KCMs, the students constructing PCMs formed higher‐quality propositions in their maps and performed better in hypothesising, reasoning, and drawing conclusions in the inquiry task.ImplicationsBesides KCMs, students in inquiry learning can be encouraged to construct PCMs to foster effective thinking and reasoning; that is, constructing a concept map to represent the problem situation as a sequence of changes and the causal relationships between the changes.

Overview of knowledge reasoning for knowledge graph

Knowledge graphs are large-scale semantic networks that considerably impact knowledge representation. Mining hidden knowledge from existing data, including triplet knowledge reasoning, is a primary objective of knowledge graphs. With the development of Neural Network (NN) and Deep Learning (DL), the interpretability of triplet knowledge reasoning gradually decreases; furthermore, what machines learn is not actual reasoning but digital reasoning shortcuts. To solve this problem, more background knowledge needs to be introduced into knowledge graphs: causal graphs can offer valuable causal logic knowledge for reasoning; temporal quadruples can provide essential temporal distribution details; and commonsense graphs can furnish pertinent commonsense understanding to support reasoning. In recent years, many scholars have incorporated additional background knowledge into knowledge graphs to construct more complex reasoning mechanisms. This paper reviews the basic concepts and definitions of knowledge reasoning and the reasoning methods used for knowledge graphs. Specifically, we dissect the reasoning methods into four categories: triplet reasoning, causal inference, temporal inference, and commonsense reasoning. Finally, we discuss the remaining challenges and research opportunities related to knowledge graph reasoning.

Dada Bhagwan’s Insight on Intellect

In this paper the attempt has been made to clarify Dada Bhagwan’s concept of Intellect. Further, its difference and relation with the concept of faith, Knowledge, Prajna are also seen critically. The whole approach of Dada Bhagwan is analytical, critical as well as practical. Further, it should be noted that like Swaminarayana or Ramakrishna Paramahamsa, Dada Bhagwan also narrated the metaphysical, epistemological or moral truths in very lucid and colloquial language and expressions. The highest noble truths are expressed by him with simple examples of day-to-day like. Thus, it can be said regarding the writings of Dada Bhagwan that an illiterate will find it easy to understand and a scholar will find complex reasoning in his writing. The paper comprises of the narration and clarifications of Dada Bhagwan’s theory of Akrama Vijnana. Here, fate and freedom of soul, emancipation of soul is discussed with reference to the use of intellect. Dada Bhagwan elaborately gives the specific definition of Faith, Fate, Freedom, Intellect, Knowledge, Decisive knowledge, Prajna etc. Further it is expressively seen in Dada Bhagwan’s writings that the whole effort is done not only for intellectual pleasure, but for the purpose of Sadhana or spiritual practices for the attainment of salvation. Firstly, we will see his basic brief concept of Akrama Vijnana according to Dada Bhagwan and then his detailed definitions, concepts and practices will be discussed, with his views on the necessity and limitations of intellect.

Comparison of two different integration methods for the (1+1)-dimensional Schrödinger-Poisson equation

We compare two different numerical methods to integrate in time spatially delocalized initial densities using the Schrödinger-Poisson equation system as the evolution law. The basic equation is a nonlinear Schrödinger equation with an auto-gravitating potential created by the wave function density itself. The latter is determined as a solution of Poisson's equation modelling, e.g., non-relativistic gravity. For reasons of complexity, we treat a one-dimensional version of the problem whose numerical integration is still challenging because of the extreme long-range forces (being constant in the asymptotic limit). Both of our methods, a Strang splitting scheme and a basis function approach using B-splines, are compared in numerical convergence and effectivity. Overall, our Strang-splitting evolution compares favourably with the B-spline method. In particular, by using an adaptive time-stepper rather large one-dimensional boxes can be treated. These results give hope for extensions to two spatial dimensions for not too small boxes and large evolution times necessary for describing, for instance, dark matter formation over cosmologically relevant scales.

OVERGROWING REFUGEE PROBLEM IN LEBANON

The growing issue of Syrian refugees in Lebanon weaves tightly with Lebanon's past. It's a country with a complex history surrounding refugees, especially Palestinian refugees, and a long past with Syria. This rising refugee concern started after the Syrian Civil War. It's also tied to political, social, and economic elements that shaped Lebanon's reaction to this human crisis. Lebanon serving as a sanctuary for refugees isn't a new thing. It started before the Syrian refugee wave that came after the 2011 Civil War. The long-standing Palestinian refugee community, who've lived in Lebanon's camps for about seven decades, remarkably impacted Lebanon's view on welcoming refugees. Lebanese-Palestinian history carries weight due to the Arab-Israeli conflicts and PLO's role in the Lebanese Civil War. This past creates a hesitant, suspicious attitude in Lebanon towards refugees. It impacts how they handle the crisis of Syrian refugees. Also, the lasting stay of Syrian soldiers in Lebanon following its Civil War added tension. This, combined with Syria's large political sway, has intensified the rift between the countries. The long-term effects of this situation have stirred negativity towards Syrians and refugees in Le Banon. It's impacted both societal views and politics. It's also determined how Lebanon's government handles the necessities of Syrian refugees. Lebanon has a special governance system. It gives roles to people based on their religion. It has really influenced how they treat the refugee situation. Why? Because they're scared. They're scared about their population changing. Scared about tension between religious groups. That worry makes them hesitant in giving legal status to the refugees. They're worried that this might make the refugees want to stay longer. The past vents highlight the complex reasons for Lebanon's approach to the increasing refugee situation. The Syrian Civil War started, and Lebanon became home to roughly 1.5 million Syrian refugees. That's a ton for a place with around only 6.8 million people. Lebanon faces a massive dilemma now. It tests their shaky economy and society greatly. Lebanon's challenge is dealing with a large number of refugees. Their old residency rules make it tough. Many Syrians don't have official status. They can't work, go to school, or get healthcare. They might be taken advantage of and can't do much legally about it. Additionally, tough management hurdles, like the twice-yearly complex registration for refugees over 15, carry on their unstable situation. Various refugees, scared off by the difficult renewal steps, choose not to renew their legal status. This worsens their risk and blocks their way to vital services. The refugee crisis has had a profound and far-reaching impact on the fundamental rights and well-being of those affected, particularly in the areas of education, healthcare, and basic living conditions. These dire circumstances permeate all aspects of their lives, potentially perpetuating long-term vulnerabilities and significantly affecting their daily existence. In this context, international aid has played a crucial role in addressing the immense humanitarian needs created by Lebanon's refugee crisis. However, the necessary funds to adequately support these individuals have fallen short, resulting in approximately 54% of the required 2014 funding remaining unmet. This financial strain has only added to the already daunting challenges of providing essential support and services to the refugees.

Complexity of Credulous and Skeptical Acceptance in Epistemic Argumentation Framework

Dung’s Argumentation Framework (AF) has been extended in several directions. Among the numerous proposed extensions, three of them seem to be of particular interest and have correlations between them. These extensions are: constrained AF (CAF), where AF is augmented with (strong) constraints; epistemic AF (EAF), where AF is augmented with epistemic constraints; and incomplete AF (iAF), where arguments and attacks can be uncertain. While the complexity and expressiveness of CAF and iAF have been studied, that of EAF has not been explored so far. In this paper we investigate the complexity and expressivity of EAF. To this end, we first introduce the Labeled CAF (LCAF), a variation of CAF where constraints are defined over the alphabet of labeled arguments. Then, we investigate the complexity of credulous and skeptical reasoning and show that: i) EAF is more expressive than iAF (under preferred semantics), ii) although LCAF is a restriction of EAF where modal operators are not allowed, these frameworks have the same complexity, iii) the results for LCAF close a gap in the characterization of the complexity of CAF. Interestingly, even though EAF has the same complexity as LCAF, it allows modeling domain knowledge in a more natural and easy-to-understand way.

Making Natural Language Reasoning Explainable and Faithful

Neural models, including large language models (LLMs), achieve superior performance on logical reasoning tasks such as question answering. To elicit reasoning capabilities from LLMs, recent works propose using the chain-of-thought (CoT) mechanism to generate both the reasoning chain and the answer, which enhances the model’s capabilities in conducting reasoning. However, due to LLM’s uninterpretable nature and the extreme flexibility of free-form explanations, several challenges remain: such as struggling with inaccurate reasoning, hallucinations, and not aligning with human preferences. In this talk, we will focus on (1) our design of leveraging structured information (that is grounded to the context), for the explainable complex question answering and reasoning; (2) our multi-module interpretable framework for inductive reasoning, which conducts step-wise faithful reasoning with iterative feedback.

Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative Data

Large Language Models (LLMs) have performed well on various reasoning tasks, but their inaccessibility and numerous parameters hinder wide application in practice. One promising way is distilling the reasoning ability from LLMs to small models by the generated chain-of-thought reasoning paths. In some cases, however, LLMs may produce incorrect reasoning chains, especially when facing complex mathematical problems. Previous studies only transfer knowledge from positive samples and drop the synthesized data with wrong answers. In this work, we illustrate the merit of negative data and propose a model specialization framework to distill LLMs with negative samples besides positive ones. The framework consists of three progressive steps, covering from training to inference stages, to absorb knowledge from negative data. We conduct extensive experiments across arithmetic reasoning tasks to demonstrate the role of negative data in distillation from LLM.

PHFormer: Multi-Fragment Assembly Using Proxy-Level Hybrid Transformer

Fragment assembly involves restoring broken objects to their original geometries, and has many applications, such as archaeological restoration. Existing learning based frameworks have shown potential for solving part assembly problems with semantic decomposition, but cannot handle such geometrical decomposition problems. In this work, we propose a novel assembly framework, proxy level hybrid Transformer, with the core idea of using a hybrid graph to model and reason complex structural relationships between patches of fragments, dubbed as proxies. To this end, we propose a hybrid attention module, composed of intra and inter attention layers, enabling capturing of crucial contextual information within fragments and relative structural knowledge across fragments. Furthermore, we propose an adjacency aware hierarchical pose estimator, exploiting a decompose and integrate strategy. It progressively predicts adjacent probability and relative poses between fragments, and then implicitly infers their absolute poses by dynamic information integration. Extensive experimental results demonstrate that our method effectively reduces assembly errors while maintaining fast inference speed. The code is available at https://github.com/521piglet/PHFormer.

On the Structural Hardness of Answer Set Programming: Can Structure Efficiently Confine the Power of Disjunctions?

Answer Set Programming (ASP) is a generic problem modeling and solving framework with a strong focus on knowledge representation and a rapid growth of industrial applications. So far, the study of complexity resulted in characterizing hardness and determining their sources, fine-grained insights in the form of dichotomy-style results, as well as detailed parameterized complexity landscapes. Unfortunately, for the well-known parameter treewidth disjunctive programs require double-exponential runtime under reasonable complexity assumptions. This quickly becomes out of reach. We deal with the classification of structural parameters for disjunctive ASP on the program's rule structure (incidence graph). First, we provide a polynomial kernel to obtain single-exponential runtime in terms of vertex cover size, despite subset-minimization being not represented in the program’s structure. Then we turn our attention to strictly better structural parameters between vertex cover size and treewidth. Here, we provide double-exponential lower bounds for the most prominent parameters in that range: treedepth, feedback vertex size, and cliquewidth. Based on this, we argue that unfortunately our options beyond vertex cover size are limited. Our results provide an in-depth hardness study, relying on a novel reduction from normal to disjunctive programs, trading the increase of complexity for an exponential parameter compression.

Cervical Cancer Screening Barriers Among HIV Positive Women Attending ART Clinic at Yekatit 12 Hospital Medical College, Addis Ababa, Ethiopia: A Qualitative Study

<i>Background</i>: Cervical cancer is the most common cause of morbidity and death among female cancer patients globally, particularly in poor nations like Ethiopia. It is a preventable, non-communicable disease of public health relevance. In Ethiopia, women's acceptance of the services for cervical cancer screening and treatment is low and poorly recorded. The goal of the current study is to investigate the obstacles that HIV-positive women face while trying to use cervical cancer screening. <i>Objective</i>: To investigate cervical cancer screening barriers among HIV positive women at Yekatit 12 Hospital Medical College, Ethiopia, 2021. <i>Methods</i>: Between April and June of 2021, a qualitative study was carried out with women who tested positive for HIV and were enrolled in the ART clinic at Yekatit 12 Hospital Medical College. At the time of the study, HIV-positive women and medical professionals were purposefully chosen from an ART clinic. In all, 14 patients and 9 healthcare professionals participated in the study. A schedule for in-depth interviews were used to gather data. Analysis was done by using atlas ti computer software. <i>Result</i>: The risk factors and symptoms of cervical cancer were not well known to the respondents. Women have identified several factors that impact their use of cervical screening: inadequate knowledge of the significance of screenings, perceptions of the seriousness of cervical cancer, the separation of the screening location from ART, having conflicting concerns, and emotional barriers like anxiety about a positive result, embarrassment, and shame anticipation. These same problems were recognized by healthcare professionals as obstacles to cervical screening. <i>Conclusion</i>: This study offers extensive data on the various complex reasons why women do not participate in cervical cancer screening programs. Consequently, it is crucial to develop interventions that can address and reduce these barriers.

Perceived Causes of Vulnerable Employment among Rural Youth in Agricultural Endeavours: Insights and Recommendations

In India, where over 60% of the youth reside in rural areas, agriculture remains the primary source of livelihood. However, the sector faces a critical challenge: its young workforce is increasingly migrating towards urban areas in search of better opportunities. This research, conducted across eight villages in Karnataka (India), sheds light on the complex reasons behind this exodus. Through surveys with 120 rural youths, the study uncovers a multifaceted cocktail of challenges hindering their agricultural aspirations. Precarious employment emerges as a key theme, fueled by low remuneration for their produce, restrictive credit access, inadequate storage facilities, and the overall perception of agriculture as an unprofitable endeavor. Beyond economic constraints, the research delves into social and environmental factors like limited market access, lack of technical expertise, and the unpredictability of monsoons, further compounding the vulnerabilities faced by young farmers. Recognizing these intricate challenges, the study proposes actionable recommendations. It advocates for improving access to institutional credit, ensuring remunerative minimum support prices, investing in local infrastructure like storage facilities, and facilitating timely input supply. By implementing these suggestions and fostering a more enabling environment, policymakers and stakeholders can reverse the tide of rural youth migration, revitalize the agricultural sector, and pave the way for a more sustainable and prosperous future for India's rural communities.

History of the pacific capelin Mallotus catervarius (osmeriformes) fishery near the sakhalin coast and reasons of its catch records in present period

Far East capelin is characterized by long-term cycles of its biomass dynamics. During XX and early XXІ century fishery of Far East capelin near Sakhalin Island was more intensive in the years of high abundance. In 1930s annual catches of this fish was not more than 0,8– 0,9 thousand tons. In 1970s catches varied from 0,93 to 2,50 thousand tons. In 2016–2022 capelin catches attained to record level, 3,5–13,7 thousand tons. Grate catches connected by complex reasons such as large spawning biomass, intensive fishery and its season near Sakhalin coast and some others. It is already clear that the northwestern coast of Sakhalin is the most ideal for reproduction, growth, and survival of capelin in the waters around Sakhalin Island. Reproduction productivity of this fish species in the Sakhalin area of Okhotsk Sea is much lower as an annual catches.

Идея «творящей формы» в эстетике русского авангарда 1920-х годов

The Russian avant-garde of the 1920s was a time of a utopian thinking crisis in theoretical aesthetics and in art. The utopianism of the avant-garde project consisted in the impracticability of the mission of art to totally transform reality and man through aesthetic means. The key idea of the avant-garde aesthetic concepts was the effectiveness of the creative form building the integrity of the life creative matter. The concept of the “creative form” was developed in different directions: from the concept of a single style in all spheres of life and the theory of synthesis of arts to the aesthetics of functionally appropriate forms of the objective environment. The symbolic language of style was a universal aesthetic translation of metaphysical ideas into sensual ontological image of the wholeness of being; synthesis of arts was seen as a means of expressing the initial wholeness of cosmic being; and a functionally appropriate form of the objective environment was understood as a means of direct involvement of man, spontaneously causing his active creative response. The utopianism of the idea of the “creative form” determined its rapid demise, which had a complex of philosophical, social, political and human reasons. The major of them included the totality of the wholeness project, the undervaluation of the individual artistic subject’s creative freedom, the rejection of a substantial spiritual and value-based interpretation of culture, the hope that the aesthetic influence might transform the masses into creative subjects, the narrowing of the potentialities of the utopian project by the attempt to turn it into a methodology of action, the pursuit of realization that limited the growth of its inner potential, and the undervaluation of the real conditions for its implementation.

Exploring clinical reasoning in child language assessment through decoloniality

Purpose Clinical reasoning has been taught, practised, and researched under Western epistemologies, which have been fallible in addressing the complexity of clinical reasoning within Indigenous cultures and societies. We explored how speech-language pathologists in Sri Lanka negotiate and value Indigenous and Western perspectives in clinical reasoning within a decolonial framework. Method This study used participatory research methodology within the decolonised qualitative research paradigm to produce data collaboratively with eight Sri Lankan speech-language pathologists. Oral history narratives and object-based textual reflections generated the necessary data for the study. Systematic visual-textual analysis and reflexive thematic analysis were carried out iteratively, and the data analysis and interpretation were undertaken collaboratively with the participants. Result We generated four key themes about professional education, individuality in practice, holistic thinking, and balancing interests and priorities. The results demonstrate that social, political, and economic forces impact practitioners’ clinical reasoning. Conclusion Practising science in its original form within Indigenous contexts is challenging. Colonial roots and imperialism impact the delivery of appropriate services in socially and politically marginalised communities. Practitioners’ self-awareness about authentic identities and practical wisdom can develop culturally relevant knowledge for equitable practice.

Neuro-Symbolic Reasoning for Multimodal Referring Expression Comprehension in HMI Systems

AbstractConventional Human–Machine Interaction (HMI) interfaces have predominantly relied on GUI and voice commands. However, natural human communication also consists of non-verbal communication, including hand gestures like pointing. Thus, recent works in HMI systems have tried to incorporate pointing gestures as an input, making significant progress in recognizing and integrating them with voice commands. However, existing approaches often treat these input modalities independently, limiting their capacity to handle complex multimodal instructions requiring intricate reasoning of language and gestures. On the other hand, multimodal tasks requiring complex reasoning are being challenged in the language and vision domain, but these typically do not include gestures like pointing. To bridge this gap, we explore one of the challenging multimodal tasks, called Referring Expression Comprehension (REC), within multimodal HMI systems incorporating pointing gestures. We present a virtual setup in which a robot shares an environment with a user and is tasked with identifying objects based on the user’s language and gestural instructions. Furthermore, to address this challenge, we propose a hybrid neuro-symbolic model combining deep learning’s versatility with symbolic reasoning’s interpretability. Our contributions include a challenging multimodal REC dataset for HMI systems, an interpretable neuro-symbolic model, and an assessment of its ability to generalize the reasoning to unseen environments, complemented by an in-depth qualitative analysis of the model’s inner workings.

Connection between single-layer quantum approximate optimization algorithm interferometry and thermal distribution sampling

The quantum approximate optimization algorithm (QAOA) was originally proposed to find approximate solutions to combinatorial optimization problems on quantum computers. However, the algorithm has also attracted interest for sampling purposes since it was theoretically demonstrated under reasonable complexity assumptions that one layer of the algorithm already engineers a probability distribution beyond what can be simulated by classical computers. In this regard, a recent study has also shown that, in universal Ising models, this global probability distribution resembles pure but thermal-like distributions at a temperature that depends on the internal correlations of the spin model. In this work, through an interferometric interpretation of the algorithm, we extend the theoretical derivation of the amplitudes of the eigenstates and the Boltzmann distributions generated by a single-layer QAOA. We also review the implications of this behavior from practical and fundamental perspectives.