Degree Of Complexity Research Articles

Elevating optical networks: Machine learning approach for optimal resource scheduling and performance boost

SummaryThe increasing demand for massaging networks that are stable and quick needs reevaluations of standard optical networking administration strategies. To improve the efficacy of optical networks by integrating machine learning (ML) approach for the best resource scheduling, this research presents an innovative dynamic block widow optimized random forest (DBWO‐RF) strategy. To implement the DBWO‐driven resource allocation method in accordance with the categorization and clustering findings, the RF method is incorporated with the software defined optical to achieve channel quality assessment after successfully clustering employs the RF approach to achieve channel quality assessment after successfully clustering traffic patterns using the fuzzy C‐means (FCM) algorithm. To lessen the likelihood of blocking, the fragmentation‐function‐fit (FFF) algorithm was provided and the findings indicate that this approach possesses a reduced blocking risk. Using multiple approaches to modulation for various channel quality, the suggested resource allocation system leverages the DBWO approach to distribute the necessary resources based on various “traffic flow (TF)” clustering findings. The examination's outcomes demonstrate that, compared to other techniques under various given load levels, the present study has a reduced blocking risk, a sufficient complexity degree and greater effectiveness in the utilization of spectrum resources.

Identification of DDX5 as a Potential Therapeutic Target of Osteosarcoma Using Thiazolone Probes.

Osteosarcoma (OS) is a rare malignant tumor that has predominantly affected children and adolescents in the past 50 years. The genomes of OS tumors exhibit a high degree of complexity, which leads to the great challenge of target identification for anti-OS. To date, no efficient therapeutic target for the treatment of OS has been validated in clinical practice. In our previous drug hunting for the treatment of OS by phenotypic screening, we found that thiazolone derivate (R)-8i was an effective and selective inhibitor against OS in MNNG/HOS cells and in vivo. However, the mechanism of action and specific molecular targets of (R)-8i remain unclear. In this study, we design and synthesize the photo-cross-linking probes based on the lead compound (R)-8i and identify DDX5 as a potential target protein using an activity-based protein profiling strategy. Further experiments including Western blot, shRNA knockdown experiments, cell colony formation, wound healing assays, and cellular thermal shift assays support that (R)-8i binds to DDX5 and induces its degradation, which affect cell proliferation and migration through the PI3K-AKT-mTOR signaling pathway. The research shows that DDX5 is a potential therapeutic target for the treatment of OS.

Developing Organizational Requirements to Standardize Delivery and Improve Quality of Acute Leukemia Care in Ontario.

Acute leukemia is a rapidly progressive cancer of the blood and bone marrow that requires a high degree of complex, specialized, resource-intensive clinical and supportive care. The aging Canadian population has introduced an unprecedented demand on the health care system for a variety of illnesses, including acute leukemia. The purpose of this work was to develop organizational requirements for service providers delivering care for patients aged 18 years and older with acute leukemia within a single-payer health care system in Ontario. This initiative was intended to support streamlining high-quality health care across Ontario. We worked collaboratively with an expert panel to conduct a review of the literature to synthesize the organizational requirements for delivering acute leukemia care. A total of 229 requirements were developed. The requirements were categorized into themes including (1) facility requirements, including infrastructure, data management, safety, policies and procedures; (2) availability of clinical services and service complexity; (3) personnel, including roles, responsibilities, and ongoing education; (4) patient care; (5) quality management; (6) clinical research; and (7) laboratory services. These requirements will act as a framework for the provision of service, complexity of care, safety, accessibility, and quality care across all levels from the patient, organization, and system perspectives. This framework will help support person-centred care, emphasizing providing care close to home, while optimizing the use of specialized resources. Moving forward, Ontario Health (Cancer Care Ontario) will continue to work with acute leukemia service providers in the province to determine compliance and focus improvement efforts in priority areas.

Bouncing forward better – micro-foundations of combinatorial innovation

This article theoretically investigates the conditions that empower actors (entrepreneurs and intrapreneurs) to pursue combinatorial innovation processes, and thereby contribute to transformative activities with a high degree of novelty and complexity. We argue that the possibility for combinatorial innovation depends on agents’ time perspective and combinatorial capabilities. We elaborate why institutional incentive structures and knowledge bases condition actors’ time perspective and why network structures and firm routines condition actors’ combinatorial capabilities. We illustrate our arguments with examples and show their practical relevance for policy and innovative actors.

The importance of spatial scale and vegetation complexity in woody species diversity and its relationship with remotely sensed variables

Plant species diversity is key to ecosystem functioning, but in recent decades anthropogenic activities have prompted an alarming decline in this community trait. Thus, developing strategies to understand diversity dynamics based on affordable and efficient remote sensing monitoring is essential, as well as examining the relevance of spatial scale and vegetation structural complexity to these dynamics. Here, we used two mathematical approaches to assess the relationship between tropical woody species diversity and spectral diversity in a human-modified landscape in two vegetation types differing in their degree of complexity. Vegetation complexity was measured through the fraction of species that concentrate different proportions of the cumulative importance value index. Species diversity was assessed using Hill numbers at three spatial scales, and metrics of spectral heterogeneity, vegetation indices, as well as raw data from Landsat 9 and Sentinel-2 sensors were calculated and analysed through general linear models (GLM) and Random Forest. Vegetation complexity emerged as an important variable in modelling species from remote sensing metrics, indicating the need to model species diversity by vegetation type rather than region. Hill numbers showed different relationships with remotely sensed metrics, in consistency with the scale-dependency of ecological processes on species diversity. Contrary to multiple previous reports, in our study, GLMs produced the best fits between Hill numbers of all orders and remotely sensed metrics. If we are to meet the need of conducting efficient and speedy woody species diversity monitoring globally, we propose modelling this diversity from remotely-sensed variables as an attractive strategy, so long as the intrinsic properties of each vegetation type are acknowledged to avoid under- or overestimation biases.

Problem of Animal Rights in Selected Works by Dorota Probucka

This article presents the idea of animal rights as perceived by a Polish philosopher and ethicist, Dorota Probucka. It is divided into three sections that delve into the development and significance of animal rights from the perspectives of both proponents and critics of the idea. The first section provides an overview of the turning points in the history and evolution of animal rights, referring to the main thinkers who had the fundamental impact on their development. The second part defines the concept of animal rights and explains why extending fundamental rights to at least some non-human beings is important from both moral and legal perspectives. The third part compares the arguments of the proponents and opponents of the idea of granting basic rights to animals. The philosophers’ positions presented by Probucka prove that beings capable of suffering, regardless of their intellectual abilities, deserve moral consideration. This stance is supported by numerous arguments from various fields of science, demonstrating the degree of awareness and emotional complexity of animals. These arguments should contribute to the recognition of animal rights within a moral and legal context. The article also emphasizes the need for legal reforms, including the need to introduce formal legal structures, such as the appointment of the so-called Animal Rights Ombudsman, who could represent animals at an institutional level. Considering the growing bioethical and biocentric awareness, the article emphasizes the need to redefine our attitude towards animals. It also postulates the necessity of implementing legal reforms that will make animals full participants of the moral community, which is of key importance for the future of both people and animals on our planet.

High-complexity of DNA double-strand breaks is key for alternative end-joining choice

The repair of DNA double-strand breaks (DSBs) through alternative non-homologous end-joining (alt-NHEJ) pathway significantly contributes to genetic instability. However, the mechanism governing alt-NHEJ pathway choice, particularly its association with DSB complexity, remains elusive due to the absence of a suitable reporter system. In this study, we established a unique Escherichia coli reporter system for detecting complex DSB-initiated alternative end-joining (A-EJ), an alt-NHEJ-like pathway. By utilizing various types of ionizing radiation to generate DSBs with varying degrees of complexity, we discovered that high complexity of DSBs might be a determinant for A-EJ choice. To facilitate efficient repair of high-complexity DSBs, A-EJ employs distinct molecular patterns such as longer micro-homologous junctions and non-templated nucleotide addition. Furthermore, the A-EJ choice is modulated by the degree of homology near DSB loci, competing with homologous recombination machinery. These findings further enhance the understanding of A-EJ/alt-NHEJ pathway choice.

On the suitability of dispersion models of varying degree of complexity for air quality assessment and urban planning

The development of integrated urban services requires the implementation of informative tools that provide a balance between quality, time and costs for air quality assessment. Within this framework, three modeling techniques with different levels of complexity were compared during a winter inversion episode against PM10 concentrations measured in a built-up area in Prague (Czech Republic) characterized by heavy traffic. Although the Gaussian model ATEM satisfied the common statistical-performance criteria, the predictions poorly represented the spatial variability of concentrations in the study domain. The Lagrangian model GRAL provided a better simulation of the effects of terrain and vortice formation inside street canyons, but tended to overpredict the influence of these phenomena. Finally, the most sophisticated of the three models, the Large-Eddy Simulation model PALM, demonstrated the best performance based on an exhaustive analysis of the model outputs in the temporal and spatial dimensions. After model comparison, a sensitivity test of the selected models to the driving meteorology and emissions inputs was carried out. While advanced models can simulate complex urban environments, their suitability for use in urban planning is subject to further considerations, such as computational cost, user expertise, and the usefulness of the output. Thanks to increasing computation power and intensive work on the entire modeling chain, sophisticated models could become routine tools for use in regulatory applications, contributing to future integrated urban service provision.

Assessment of the diagnostic utility of the electroencephalogram in pediatric emergencies

IntroductionWe analyze the diagnostic utility of urgent EEG (electroencephalogram) performed in children under 16 years of age in our center. Material and methodsDescriptive, retrospective, observational study of consecutive patients from 0 to 16 years of age, who underwent an urgent EEG for any reason, from January to December 2022. ResultsOf the 388 patients, 70 were children: 37 (52.85%) women, and 33 (47.14%) men. Average age: 6.27 ± 4.809. Of the 70 patients, 6 (8.57%) had previous epilepsy. Reasons for consultation: 17 febrile seizures, 10 first focal seizures, 10 first TCG seizures, 6 paroxysmal episodes, 6 absences, 3 myoclonus of extremities, 3 syncope, 2 SE, 2 visual alterations, 2 low level of consciousness, 2 cyanosis, 2 suspected meningitis or encephalitis, 1 choking, 1 atypical headache, 1 chorea, 1 presyncope, 1 language delay. Of the 70 patients, 47 had a normal EEG (67.14%). Of the 47 patients with a normal EEG, 10 were diagnosed with epilepsy, and 3 of them began receiving antiepileptic treatment upon discharge. None of the patients with suspected syncope or paroxysmal disorder (17 patients, 24.28%) had EEG abnormalities. Of the 17 patients with atypical febrile seizures, 3 had EEG abnormalities. ConclusionsA third of the EEG records performed in the Emergency Department showed alterations, probably due to the time taken. Almost half of the patients with suspected epilepsy or EE showed EEG abnormalities, which confirmed the diagnosis in these cases and encouraged the clinician to start drug treatment. No case with a high suspicion of epilepsy was dismissed due to the normality of the EEG recording in our series. No patient diagnosed with syncope or paroxysmal disorder had EEG abnormalities. Nearly a quarter of patients with atypical febrile seizures showed EEG abnormalities. We barely register cases of status epilepticus, probably due to the degree of complexity of our center.

Performance management systems and digital technologies: an exploratory analysis of practitioners and academics’ perspectives

PurposePerformance management systems (PMSs) must remain dynamic and maintain the ability to withstand the high degrees of complexity brought about by digital technologies (DTs). Academics and practitioners have explored DTs and PMSs separately. This study aims to bridge the academic and practitioner discourse surrounding PMSs and DTs to promote knowledge diffusion and collaboration.Design/methodology/approachThe authors adopted a mixed method approach, combining quantitative and qualitative content analysis, which were validated through semi-structured interviews with academics and practitioners. The authors first conducted a content analysis of the academic literature contained in the Scopus database and the practitioners' literature featured in the Nexis Uni database.FindingsThe combined academic-practitioners’ body of knowledge underscores the risk and environmental dimension, as well as the theoretical frameworks employed to explore digitally empowered PMSs. These findings were corroborated by 17 confirmatory interviews conducted with scholars and practitioners.Research limitations/implicationsDue to its scope, the research is limited to publications listed on Scopus and Nexis Uni. Additionally, its qualitative and interpretative nature presents some generalizability issues.Originality/valueThis study connects the intentions of scholars and practitioners concerning PMSs and DTs to promote collaborative efforts and knowledge diffusion. Moreover, considering the broader spectrum of insights, this manuscript postulates new avenues of research that address the key issues and concerns of both academics and practitioners. Finally, this article showcases PMs- and DT-appropriate theoretical frameworks that can inform practitioners’ discourse and work.

Entrepreneurial and international? The role of entrepreneurial orientation in the Brazilian franchises’ internationalization process

PurposeWe investigate the relationship between Entrepreneurial Orientation (EO) and the internationalization pathways of Brazilian franchises. Our aim is to unravel the patterns of firm-level entrepreneurial characteristics vis-à-vis their corresponding processes of internationalization.Design/methodology/approachWe extracted and curated data from the directories of the Brazilian Franchising Association (ABF). Additionally, we scrutinized the International Intensity, International Complexity and EO degree of 27 Brazilian franchises engaged in international activities. Associations between these dimensions were assessed through fuzzy-set qualitative comparative analysis (fsQCA).FindingsOur findings suggest that franchisees can enhance their international activities by adopting various configurations of EO attributes. This discovery illuminates the intricacies of EO and its association with firms’ operations and performance. Accordingly, we empirically demonstrate that EO is not a monolithic element. Instead, it should be perceived as a multifaceted and dynamic construct.Originality/valueThis study aimed to examine the internationalization process of franchises through the EO lens, a perspective that has not been explored in the existing literature. This unique approach offers novel insights about the internationalization processes of this particular business model. Furthermore, our research delves into the intricate relationship between firm-level EO and the trajectories of firm-level internationalization.

Emerging Networks

This paper discusses findings from an investigation of students’ experiences from and participation in different learning networks during the Covid19-lockdown. The investigation is based on empirical data in the form of 32 interviews with students from a variety of University College Programmes (business-, administration-, construction-, technology-, health-, pedagogy- and teacher education). The interviews were collected as part of a larger study, where data also consisted of responses to surveys from, potentially, 84000 students. In the interviews, the students shared their experiences regarding learning and teaching online, respectively. Three cases were singled out aiming to maintain a high degree of complexity and maximum variation. Through the contemporary theories within the field of Networked Learning, we aim to show examples of how the students were networked during the Covid-19 shutdown and the implications that emerging networks had on their participation in online educational activities. Furthermore, we wish to make a suggestion for the use of the applied categorisation of networks for analyzing how students are networked. These categories, presented in this paper, are proposed by researchers within the field. The main findings suggest that online teaching during the lockdown required students to establish new patterns of participation, thus, establishing new structures and ways to collaborate. This led to emerging networks supporting different aspects of their life setting as students and creating opportunities for engaging in new social configurations and learning.

Firm-level climate risk and accounting conservatism: International evidence

We examine the impact of climate-risk exposure on accounting conservatism, and document a significant positive association. Utilizing a firm-level climate-exposure measure (CRI) for a large international sample covering 46 countries from 2002 to 2021, we find that firms facing climate risk tend to adopt more conservative reporting practices. This effect is notably stronger during pivotal periods of climate awareness, such as that around the Paris Climate Agreement, and in jurisdictions governed by common law. Our results remain valid under a series of robustness tests and after addressing endogeneity concerns. Further analyses indicate that this positive association is more pronounced in well-governed firms and in firms with high levels of environmental and social performance, but less pronounced in firms with high degrees of complexity and information asymmetry. Additional tests reveal that firms in environmentally sensitive industries and those operating in developed countries adopt more conservative reporting than counterparts in non-environmentally sensitive industries or in developing countries. Our final analysis suggests that regulatory risks have a greater effect on accounting conservatism than physical risks. Our paper contributes to the ongoing discourse on climate change, documenting the ‘bright side’ of firms' exposure to climate risk.

Decision-focused neural adaptive search and diving for optimizing mining complexes

Optimizing industrial mining complexes, from extraction to end-product delivery, presents a significant challenge due to non-linear aspects and uncertainties inherent in mining operations. The two-stage stochastic integer program for optimizing mining complexes under joint supply and demand uncertainties leads to a formulation with tens of millions of variables and non-linear constraints, thereby challenging the computational limits of state-of-the-art solvers. To address this complexity, a novel solution methodology is proposed, integrating context-aware machine learning and optimization for decision-making under uncertainty. This methodology comprises three components: (i) a hyper-heuristic that optimizes the dynamics of mining complexes, modeled as a graph structure, (ii) a neural diving policy that efficiently performs dives into the primal heuristic selection tree, and (iii) a neural adaptive search policy that learns a block sampling function to guide low-level heuristics and restrict the search space. The proposed neural adaptive search policy introduces the first soft (heuristic) branching strategy in mining literature, adapting the learning-to-branch framework to an industrial context. Deployed in an online fashion, the proposed hybrid methodology is shown to optimize some of the most complex case studies, accounting for varying degrees of uncertainty modeling complexity. Theoretical analyses and computational experiments validate the components’ efficacy, adaptability, and robustness, showing substantial reductions in primal suboptimality and decreased execution times, with improved and more robust solutions that yield higher net present values of up to 40%. While primarily grounded in mining, the methodology shows potential for enabling smart, robust decision-making under uncertainty.

How clients choose procurement strategies and organizational control systems in the Swedish housing sector

Purpose This paper aims to examine how different contextual contingency factors and organizational goals influence construction clients’ decision-making when procuring contractors in the housing sector. More specifically, it investigates how clients’ choice of procurement strategies and organizational control systems is contingent upon various contextual factors and organizational goals. Design/methodology/approach It is based on an explorative interview study of clients and contractors in the Swedish housing sector underpinned by a review of organizational control literature. Findings The client's knowledge and resources, as well as project complexity and uncertainty, are the most important contextual contingency factors, while property management and sustainable development are the most important organizational goals that housing clients consider when designing procurement strategies. Research limitations/implications The paper contributes to the understanding of how construction clients choose procurement strategies, by providing new insights into effects of the mentioned contextual contingency factors and organizational goals on clients’ choice of control systems through their procurement strategies. Practical implications Property owners who continuously procure housing projects with sustainability requirements and high degrees of complexity and uncertainty should develop knowledge and resources related to their client role, to enable the design and implementation of appropriate procurement strategies. Originality/value Novel aspects of the paper are the demonstration of the value of a holistic approach, considering both contextual contingency factors and organizational goals, when selecting control systems and explicit discussion of how the client's knowledge and resources influence possibilities to implement different control systems.

Identification of microalgal particles using pixel feature analysis of Mueller matrix images

Fine sorting of aquatic particles is of great significance for water environment monitoring. Natural water contains aquatic particles that exhibit a high degree of diversity and complexity, and the identification of aquatic particles remains a persistent challenge in the field. In this article, we propose a new technique for identifying the target species of microalgal particles by using the pixel feature analysis of Mueller matrix images. This technique is independent of any prior knowledge or data about the existing particles in the environment, which is advantageous when applied to real-world situations. The pixel-level polarimetric features are fully leveraged to construct polarization feature templates, which can be used to characterize and filter specific microalgal particles in complex environments. This method could enable the accurate detection of harmful algal blooms species in natural water, which can facilitate early warning of algal blooms. The preliminary results show that the recall rate reached 97.2%, and the average accuracy is 98.9%, which demonstrate the effectiveness of this approach for identifying the target species of aquatic particles in natural water.

Effective removal of chromium, copper, and nickel heavy metal ions from industrial electroplating wastewater by in situ oxidative adsorption using sodium hypochlorite as oxidant and sodium trititanate nanorod as adsorbent

Sodium hypochlorite and synthesized sodium trititanate nanorods (Na2Ti3O7, 186 × 1270 nm) were used as the oxidant and adsorbents for in situ oxidative adsorption treatment of actual electroplating wastewaters containing Cr(VI) (2.6‒5.2 mg∙L‒1), Cu2+ (2.7‒5.4 mg∙L‒1), and Ni2+ (0.2705‒0.541 mg∙L‒1) ions at pH of 8.8‒9.1 and 20‒60 °C. The as-synthesized sodium trititanate nanorods were characterized by XRD, HRTEM, N2 adsorption/desorption, SEM, EDX, and Zeta potential techniques. The concentrations of heavy metal ions in wastewaters were analyzed by ICP technique. After in situ oxidative adsorption treatment under the concentrations of 25 g∙L‒1 for sodium hypochlorite and 125 mg∙L‒1 for sodium trititanate nanorods at 60 °C for 5 h, the heavy metal ion concentrations could be reduced from initial value of 2.6 to final value of 1.92 mg∙L‒1 for Cr(VI), 3.6 to 0.17 mg∙L‒1 for Cu2+, and from 0.2705 to 0.097 mg∙L‒1 for Ni2+, respectively. Cr(VI), Cu2+, and Ni2+ ions could be effectively removed by the in situ oxidative adsorption method. The in situ oxidative adsorption processes of Cr(VI), Cu2+, and Ni2+ ions are satisfactorily simulated by the pseudo-second order adsorption kinetics and Langmuir adsorption isotherm, respectively. Adsorption thermodynamics analyses reveal that the oxidative adsorption processes of Cr(VI), Cu2+, and Ni2+ ions are spontaneous and endothermic. The oxidation degree of metal-contained complexes influences the values of thermodynamics functions.

Achieving Occam's razor: Deep learning for optimal model reduction.

All fields of science depend on mathematical models. Occam's razor refers to the principle that good models should exclude parameters beyond those minimally required to describe the systems they represent. This is because redundancy can lead to incorrect estimates of model parameters from data, and thus inaccurate or ambiguous conclusions. Here, we show how deep learning can be powerfully leveraged to apply Occam's razor to model parameters. Our method, FixFit, uses a feedforward deep neural network with a bottleneck layer to characterize and predict the behavior of a given model from its input parameters. FixFit has three major benefits. First, it provides a metric to quantify the original model's degree of complexity. Second, it allows for the unique fitting of data. Third, it provides an unbiased way to discriminate between experimental hypotheses that add value versus those that do not. In three use cases, we demonstrate the broad applicability of this method across scientific domains. To validate the method using a known system, we apply FixFit to recover known composite parameters for the Kepler orbit model and a dynamic model of blood glucose regulation. In the latter, we demonstrate the ability to fit the latent parameters to real data. To illustrate how the method can be applied to less well-established fields, we use it to identify parameters for a multi-scale brain model and reduce the search space for viable candidate mechanisms.

Design and Analysis of a Novel Fractional-Order System with Hidden Dynamics, Hyperchaotic Behavior and Multi-Scroll Attractors

The design of chaotic systems with complex dynamic behaviors has always been a key aspect of chaos theory in engineering applications. This study introduces a novel fractional-order system characterized by hidden dynamics, hyperchaotic behavior, and multi-scroll attractors. By employing fractional calculus, the system’s order is extended beyond integer values, providing a richer dynamic behavior. The system’s hidden dynamics are revealed through detailed numerical simulations and theoretical analysis, demonstrating complex attractors and bifurcations. The hyperchaotic nature of the system is verified through Lyapunov exponents and phase portraits, showing multiple positive exponents that indicate a higher degree of unpredictability and complexity. Additionally, the system’s multi-scroll attractors are analyzed, showcasing their potential for secure communication and encryption applications. The fractional-order approach enhances the system’s flexibility and adaptability, making it suitable for a wide range of practical uses, including secure data transmission, image encryption, and complex signal processing. Finally, based on the proposed fractional-order system, we designed a simple and efficient medical image encryption scheme and analyzed its security performance. Experimental results validate the theoretical findings, confirming the system’s robustness and effectiveness in generating complex chaotic behaviors.

예비 초등교사들의 비구조화된 수학 문제 만들기 활동 분석

Objectives The purposes of this study were to analyze degree of structure and complexity of ill-structured mathematical problems made by prospective elementary teachers. Methods In order to do this, 109 prospective elementary teachers participated in ill-structured mathematical problem posing activities, as a result 24 group work papers were collected. The data was analyzed using framework which determines ill-structured problems and problem complexity. Results The results of this study showed that the degree of structure of the problems posed by prospective teachers varied. The prospective teachers posed problems with relatively high ill-structuredness in terms of authenticity, but with low ill-structuredness in terms of complexity and openness. The prospective teachers posed problems that were low of linguistic complexity but high of mathematical complexity. when prospective teachers asked students to solve problems they posed, most of them expected that difficulties would arise during the phase of carrying out the plan. Conclusions The results indicate that prospective elementary teachers need to develop their competence of posing ill-structured mathematical problems, in particular, there is a need to explore the meaning of openness of ill-structured problems. It also suggests that there is also a need to provide prospective teachers opportunities to anticipate and discuss students’ difficulties in ill-structured problem solving.