View Of System Research Articles

The connection between growth imperative of monetary production economies, the realization problem and Kornai's surplus economy

AbstractKornai challenged not only the dominant economic views of the socialist system, but also those of market economies. The former brought him fame, and the latter remained, so to speak, his scientific testament. He studied the systemic properties of different economic systems through the analytical grid of the sign of aggregate excess supply, which defined three categories: shortage economies, equilibrium economies and surplus economies. In this paper, we show that business plans postulated with the aim of realizing strictly positive net retained profits in nominal terms exclude equilibrium economies; these business plans imply a surplus economy. This definition of the business plan makes it possible to combine seemingly disparate results from different parts of the economic literature. An economy in which business plans are the rule and no economic agent can run a permanent negative budget is a surplus economy, which manifests itself in the phenomena of both growth imperative and realization problem. In short, all these phenomena are the manifestations of the same essence: the working of the business plans.

Construction of an Exudative Age-Related Macular Degeneration Diagnostic and Therapeutic Molecular Network Using Multi-Layer Network Analysis, a Fuzzy Logic Model, and Deep Learning Techniques: Are Retinal and Brain Neurodegenerative Disorders Related?

Neovascular age-related macular degeneration (nAMD) is a leading cause of irreversible visual impairment in the elderly. The current management of nAMD is limited and involves regular intravitreal administration of anti-vascular endothelial growth factor (anti-VEGF). However, the effectiveness of these treatments is limited by overlapping and compensatory pathways leading to unresponsiveness to anti-VEGF treatments in a significant portion of nAMD patients. Therefore, a system view of pathways involved in pathophysiology of nAMD will have significant clinical value. The aim of this study was to identify proteins, miRNAs, long non-coding RNAs (lncRNAs), various metabolites, and single-nucleotide polymorphisms (SNPs) with a significant role in the pathogenesis of nAMD. To accomplish this goal, we conducted a multi-layer network analysis, which identified 30 key genes, six miRNAs, and four lncRNAs. We also found three key metabolites that are common with AMD, Alzheimer's disease (AD) and schizophrenia. Moreover, we identified nine key SNPs and their related genes that are common among AMD, AD, schizophrenia, multiple sclerosis (MS), and Parkinson's disease (PD). Thus, our findings suggest that there exists a connection between nAMD and the aforementioned neurodegenerative disorders. In addition, our study also demonstrates the effectiveness of using artificial intelligence, specifically the LSTM network, a fuzzy logic model, and genetic algorithms, to identify important metabolites in complex metabolic pathways to open new avenues for the design and/or repurposing of drugs for nAMD treatment.

From Guwen to Chinese Literature

This article examines the Sinologists’ conceptually mediated approach in their studies and translations of Chinese literature in the nineteenth century. Gems of Chinese Literature (1884), compiled and translated by Herbert Allen Giles (1845–1935), contains the English translation of 110 Chinese prose extracts and eight poems from fifty-nine Chinese authors. This article historicizes the genesis and construction of this translation anthology and argues that, though most likely derived from a Chinese guwen (classical prose) collection, it was designed to provide a more systematic view of Chinese literature informed by the concept of national literature. By analysing its organizational strategies, discursive paratexts, and how it deviated from its possible Chinese source, the author demonstrates that Gems of Chinese Literature reveals more complex questions concerning the (re-)conceptualization and representation of Chinese literature at the encounter of Chinese and Western literary paradigms.

Government finance, loans, and guarantees for small and medium enterprises (SMEs) (2000–2021): A systematic review

ABSTRACT Governments across jurisdictional boundaries leverage financial incentives as a policy strategy to support and develop the business of small and medium enterprises (SMEs). This study is a systematic rety view of the literature on direct governmental finance to SMEs through loans, guarantees, and credit lines between 2000–2021. Among the 89 studies identified for inclusion, four themes emerged: provision of government loans, other government finance provision, external reasons for government finance provision, and the purpose and outcomes of government financing. The key managerial and finance findings in this study are that a greater awareness among SMEs is needed for accessing existing financial incentives from the government. Likewise, regarding government policy, this study highlights a need to clarify the purpose of loan provision to SMEs. Finally, despite calls by researchers for more qualitative assessments of SMEs and targeted government loan provision, there remains a lack of evidence to characterize this interelationship in practice.

Evaluation of circular skills and circular mind-set of consumers with the use of it - case study in a sample of consumers in northeast Brazil compared to a sample of internal stakeholders of an industry in transition to the circular economy

The circular economy concept has spread around the world, including Europe and Latin America. It is defined as a concept that led to a rethinking of economic and sustainable practices today and is inspired by the functioning of ecosystems and nature. It is innovation and design that are inseparable from products and systems, in the context of sustainable development. It is based on the principle of “closing the life cycle” of products, allowing a reduction in the consumption of raw materials, energy, and water. It promotes the development of new relationships between companies, which become consumers and suppliers of materials and are reincorporated into the production cycle. Several Circular Economy goals have already been achieved in the field of research, science, and technology. Numerous studies and efforts have been performed in the scientific and technological area for searching solutions to overcome legal, regulatory, political and technological barriers posed by several institutions; among them, the pioneering Ellen Mac Arthur Foundation has been joining efforts over the years in improving the conception and operation of the circular economy, applied to industrial processes and production chains, as well as in the structuring of new technological ecosystems. For every achievement, new challenges arise for the Circular Economy, which now needs to gain the trust of managers, politicians, investors, and entrepreneurs to initiate, plan and manage the circular economy in industry and companies. Consumers present challenges that need to be overcome by offering differentiated products and services. The objective of the work reported here was to identify mental and cultural barriers, which can generate various obstacles to the development of Circular Economy and Environmental Social Governance (ESG, such as climate change, pollution, and human resource management) issues and find ways and guidelines to resolve the problem. When investigating mentality, culture and skills for the Circular Economy, there are several possibilities to contribute to the construction of knowledge applied to the reality of companies and consumers, carrying out pilot studies in Industries with the method expressly created and oriented towards the “integrated assessment of competence", with the objective of planning and implementing the circular economy. It is based on the identification of mental models, on psychological aspects that are in line with the transition to the Circular Economy.” This method is reported here and has been used to collect data for the author's doctoral thesis. As a tool, the information platform was used, with FlashPlayHR® software (www.flashplayhr.com.br/#). bilingual, in Portuguese and English, and was developed with the aim of helping leaders, employees and stakeholders to better understand the complex systems developed through innovation in the Circular Economy. It is based on the assessment of mental models from linear to circular, as well as in identifying skills to operate with circular models. The case studies presented here included an electronics recovery and recycling industry located in São Paulo – Brazil in 2022 and a group of internet users. The study defines circular guidelines based on mindset, generating data for systemic, tactical, and operational planning, with interaction between technology and humans. The method provided the mapping/diagnosis of each employee and the organization's human system, defining the stages of the process “from linear to circular,” generating content for conducting systemic planning. One of the fundamental aspects of the method is to support the strategic human resources area of organizations, providing conditions for creating constructive interaction and integration with other areas of the industry to build a Systemic Corporate Governance Model., in addition to data and content for the development of circular programs and actions. The systems view becomes preponderant and fundamental for planning. The method/software was applied to two groups of people: one more focused on circular economy in the context of an electronic recovery industry, and another more distant from circular economy concepts, formed by Internet users. The methodology applied to the electronic retrieval industry and a random group of Internet users is reported here in detail. It was possible to identify the “linear to circular” stage of the industry to achieve the circular model.

An Assessment Model for Sustainable Cities Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

In the quest to understand urban ecosystems, traditional evaluation techniques often fall short due to incompatible data sources and the absence of comprehensive, real-time data. However, with the recent surge in the availability of crowdsourced data, a dynamic view of urban systems has emerged. Recognizing the value of these data, this study illustrates how these data can bridge gaps in understanding urban interactions. Furthermore, the role of urban planners is crucial in harnessing these data effectively, ensuring that derived insights align with the practical needs of urban development. Employing the Design Science Methodology, the research study presents an assessment model grounded in the principles of the city ecosystem, drawing from the General System Theory for Smart Cities. The model is structured across three dimensions and incorporates twelve indicators. By leveraging crowdsourced data, the study offers invaluable insights for urban planners, researchers, and other professionals. This comprehensive approach holds the potential to revolutionize city sustainability assessments, deepening the grasp of intricate urban ecosystems and paving the way for more resilient future cities.

Integrated care for older persons who live with complex health and social care requirements: a core set of indicators

PurposePerformance measures are an important mediating mechanism that influences the design and delivery of care. Unfortunately, it is still commonly the case that acute care indicators are employed to assess the efficacy of integrated care. This hinders the ability to accurately assess and continuously improve integrated care efforts for priority populations, including older persons who live with complex health and social care requirements. A core set of indicators is needed from which to assess the quality and impact of integrated care on these older persons and care partners.Design/methodology/approachA modified Delphi process was employed that comprised of the following steps: (1) selection of an indicator inventory (2) defining criteria for ranking and achieving consensus, (3) recruiting participants, (4) iterative voting rounds and analysis and (5) selection of a core indicator set.FindingsThe study produced a core set of 16 indicators of integrated care that pertain to older persons who live with health and social care requirements. The set can be applied by health and social care organizations and systems to assess the quality and impact of integrated care for this population across the continuum of care.Research limitations/implicationsAlthough the gap in the availability of relevant indicators was the impetus for the study, this also meant there was a dearth of validated indicators to draw from. There are significant gaps in commonly used data sets with respect to indicators of integrated care as it relates to older persons and care partner.Practical implicationsThe indicator set is intended to follow the older person and care partner throughout their health journey, enabling a whole systems view of their care. The set can be used in full or in part by health and social care systems and organizations across various primary, acute, rehabilitative and community settings for program development and evaluation purposes.Social implicationsThe core set of indicators that emerged out of this study is a first step toward ensuring that older persons who live with complex health and social care requirements and their care partners receive quality integrated care across the continuum of care.Originality/valueThe findings are informed by the perspectives of older persons, care partners and healthcare professionals. Future research is needed to test, validate and potentially expand the indicator set.

Book review: all through the town: the school bus as educational technology

Book review: all through the town: the school bus as educational technology

Supervised learning models for social bot detection: Literature review and benchmark

Over the past decades, online social networks such as Twitter and Facebook have become a significant part of people’s daily lives, particularly amid the ongoing global calamity — the COVID-19 pandemic. This gives room for social bot attacks that are designed to automatically replicate the behavior of real accounts. Most of these bots are employed for nefarious purposes such as disseminating false information, artificially amplifying the popularity of a person or movement, or spreading spam. Many studies have been conducted in an attempt to discover new strategies for identifying social bot accounts. To deal with large-scale attacks from social bots, Machine Learning has emerged as a noticeable path of bot detection problem that can handle massive amounts of data. However, the heterogeneity between studies in terms of problem statements, proposed processes, datasets, and evaluation metrics makes it difficult to assess and compare the efficiency of proposed methods. In this paper, we propose a systematic view of supervised learning methodologies for tweet-based social bot detection, ranging from shallow learning to specific deep learning models. In addition, we introduce a framework that measures various performance aspects and summarizes the in-depth analysis of the results, which were obtained using two datasets comprising 26224 labeled Twitter accounts. The results of this framework, we believe, will be beneficial as a practical guideline for other bot detection research or applications that require the use of machine learning techniques.

Development of a multispectral spatial-frequency domain imaging system for property and quality assessment of fruits and vegetables

Thanks to the unique features of wide-field, label-free and depth-resolved imaging, spatial-frequency domain imaging (SFDI) technique has witnessed rapid and considerable progress in biomedical, agricultural and food engineering. This paper reports on the design, characterization and calibration of a multipurpose, multispectral SFDI system (550, 600, 630, 675, 710 and 730 nm) for property and quality assessment of fruits and vegetables. The system was mainly composed of illumination unit, imaging unit and sample stage. Customized software was developed to synchronously control pattern generation and shift, light illuminating, image acquisition and saving. Multiple parameters, including field of view, spatial resolution, uniformity, linearity, repeatability and stability, were used to characterize or calibrate the multispectral SFDI system from a systematic view, based on a set of experiments using optical phantoms. The results indicate that the constructed multispectral SFDI system can be used to collect optical property parameters of common fruits and vegetables after calibration. Then the multispectral SFDI system was applied to measure the optical properties of six types of fruits and vegetables (apple, pear, cucumber, tomato, white and green radish), and the measured optical property mappings were utilized for detecting early-stage bruise, which cannot be observed by naked eyes or even conventional uniform lighting imaging. The results demonstrated that the multispectral SFDI system was capable of measuring optical properties, and the reduced scattering coefficient mapping was superior to the absorption coefficient mapping in detecting early-stage bruise. Selection of effective characteristic wavelength could further enhance the bruise detection.

Material recycling in a circular economy—A systems view

AbstractA circular economy is expected to reduce the use of primary resources through the reuse of products, components, and materials. Material recycling, though advantageous in many cases for saving primary resources by diverting them away from the landfill, may have perverse effects when analyzed from a systems perspective considering the entire material life cycle as well as economy‐wide effects of recycling. Using the case of metals, glass, and plastics recycling, the advantages of a systems view including the entire material life cycle in analyzing material recycling are illustrated. The advantages of recycling as compared to virgin production may vary significantly depending of the energy and resource requirements during the recycling process, logistics, and alloying of materials. Expanding the systems view further to analyze the economy‐wide effects of material recycling reveal the possibility of rebound effects which may reduce or even negate its advantages. Sustainable consumption is absolutely essential along with any technological advances to counter the rebound effects that may lead to overshoot. The article demonstrates the importance of considering a systems view incorporating a life cycle perspective and economy‐wide effects in analyzing and trying to maintain the advantages of material recycling.This article is categorized under: Climate and Environment > Circular Economy Emerging Technologies > Materials Climate and Environment > Pollution Prevention

Multiplexed and Millimeter-Scale Fluorescence Nanoscopy of Cells and Tissue Sections via Prism-Illumination and Microfluidics-Enhanced DNA-PAINT.

Fluorescence nanoscopy has become increasingly powerful for biomedical research, but it has historically afforded a small field-of-view (FOV) of around 50 μm × 50 μm at once and more recently up to ∼200 μm × 200 μm. Efforts to further increase the FOV in fluorescence nanoscopy have thus far relied on the use of fabricated waveguide substrates, adding cost and sample constraints to the applications. Here we report PRism-Illumination and Microfluidics-Enhanced DNA-PAINT (PRIME-PAINT) for multiplexed fluorescence nanoscopy across millimeter-scale FOVs. Built upon the well-established prism-type total internal reflection microscopy, PRIME-PAINT achieves robust single-molecule localization with up to ∼520 μm × 520 μm single FOVs and 25-40 nm lateral resolutions. Through stitching, nanoscopic imaging over mm2 sample areas can be completed in as little as 40 min per target. An on-stage microfluidics chamber facilitates probe exchange for multiplexing and enhances image quality, particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections. We demonstrate the utility of PRIME-PAINT by analyzing ∼106 caveolae structures in ∼1,000 cells and imaging entire pancreatic cancer lesions from patient tissue biopsies. By imaging from nanometers to millimeters with multiplexity and broad sample compatibility, PRIME-PAINT will be useful for building multiscale, Google-Earth-like views of biological systems.

Vision-based detection and coordinate metrology of a spatially encoded multi-sphere artefact

New developments in vision algorithms prioritise identification and perception over accurate coordinate measurement due to the complex problem of resolving object form and pose from images. Consequently, many vision algorithms for coordinate measurements rely on known targets of primitive forms that are typically planar targets with coded patterns placed in the field of view of vision systems. Although planar targets are commonly used, they have some drawbacks, including calibration difficulties, limited viewing angles, and increased localisation uncertainties. While traditional tactile coordinate measurement systems (CMSs) adopt spherical targets as the de facto artefacts for calibration and 3D registration, the use of spheres in vision systems is limited to occasional performance verification tasks. Despite being simple to calibrate and not having orientation-dependant limitations, sphere targets are infrequently used for vision-based in-situ coordinate metrology due to the lack of efficient multi-view vision algorithms for accurate sphere measurements. Here, we propose an edge-based vision measurement system that uses a multi-sphere artefact and new measurement models to extract sphere information and derive 3D coordinate measurements. Using a spatially encoded sphere identities embedded in the artefact, a sphere matching algorithm is developed to support pose determination and tracking. The proposed algorithms are evaluated for robustness, measurement quality and computational speed to assess their performance. At the range of 500 mm to 750 mm, sphere size errors of less than 25 μm and sphere-to-sphere length errors of less than 100 μm are achievable. In addition, the proposed algorithms are shown to improve robustness by up to a factor of four and boost computational speed.

Mapping mesoscale connectivity within the human hippocampus

The connectivity of the hippocampus is essential to its functions. To gain a whole system view of intrahippocampal connectivity, ex vivo mesoscale (100 μm isotropic resolution) multi-shell diffusion MRI (11.7T) and tractography were performed on entire post-mortem human right hippocampi. Volumetric measurements indicated that the head region was largest followed by the body and tail regions. A unique anatomical organization in the head region reflected a complex organization of the granule cell layer (GCL) of the dentate gyrus. Tractography revealed the volumetric distribution of the perforant path, including both the tri-synaptic and temporoammonic pathways, as well as other well-established canonical connections, such as Schaffer collaterals. Visualization of the perforant path provided a means to verify the borders between the pro-subiculum and CA1, as well as between CA1/CA2. A specific angularity of different layers of fibers in the alveus was evident across the whole sample and allowed a separation of afferent and efferent connections based on their origin (i.e. entorhinal cortex) or destination (i.e. fimbria) using a cluster analysis of streamlines. Non-canonical translamellar connections running along the anterior-posterior axis were also discerned in the hilus. In line with “dentations” of the GCL, mossy fibers were bunching together in the sagittal plane revealing a unique lamellar organization and connections between these. In the head region, mossy fibers projected to the origin of the fimbria, which was distinct from the body and tail region. Mesoscale tractography provides an unprecedented systems view of intrahippocampal connections that underpin cognitive and emotional processing.

Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps

The energy transition is a complex development towards a climate-neutral, economic, safe, and fair energy system. Therefore, numerical energy system models, among others, can make a significant contribution by simulating, optimizing and thus demonstrating possible transition pathways. Representative models and forecasting tools are needed to illustrate the next necessary steps and measures for the various target groups. In the literature, such energy system models have been studied and evaluated many times. This paper presents the approaches of previous reviews and analyses of how technical, economic, and social aspects of energy system models have been investigated so far. It is shown that especially recent studies already address this topic, but still receive insufficient recognition. Besides the general structural features, the technical modeling details were evaluated in the previous literature. Thereby, a part of the examined general reviews assesses the representation of consumer behavior in the models as a representative for social system aspects. Only a minor amount of the energy system models analyzed there per se represent consumer behavior. Furthermore, this article identifies possible linking strategies of social science parameters and energy system models from the literature based on their opportunities and challenges. This analysis forms a basis on which the already established majority of techno-economic energy system models can be extended in order to provide a more holistic view of the energy system. To do so, further research and development to improve future interdisciplinary processes are required.

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

Gen-Z university students’ attitudes toward current global trends: environment, globalisation, immigration, feminism and capitalism

ABSTRACT Generation Z is characterised by being digitally native, socially conscious, and diverse. These values influence the way they learn, communicate and relate to the world. The present study aims to examine the attitudes of university students towards some emerging global trends, including environmental change, globalisation, immigration, feminism and capitalism. It involves a cross-sectional exploratory study to describe the attitudes of a group of 1,346 students belonging to Generation Z from a Spanish university. Most students are concerned about the environment and support policies to protect it. They also view globalisation and immigration positively. A specific critical view of the capitalist system, however, is reflected by more intermediate scores. There are also gender differences in perceptions of progress on feminism and criticism of the capitalist system. Men score higher on globalisation but less on immigration. There are two profiles among Gen-Z students: those with more positive attitudes towards immigration, feminism and a critical view of the capitalist system (Social Sciences, Health, Translation-RI, Philosophy-Theology students) and those with less positive attitudes (Business, Law and Engineering). These distinctions coincide with different fields of study. Overall, these results are important in enabling social psychologists and educators to understand better the values of their students.

Vertical connectivity of microbiome and metabolome reveals depth-dependent variations across a deep cold-seep water column

Deciphering the vertical connectivity of oceanic microbiome and metabolome is crucial for understanding the carbon sequestration and achieving the carbon neutrality. However, we lack a systematic view of the interplay among particle transport, microbial community, and metabolic trait across depths. Through integrating the biogeochemical, microbial, and metabolic characteristics of a deep cold-seep water column (∼1989 m), we find the altered connectivity of microbial community and dissolved organic matter (DOM) across depths. Both the microbial communities (bacteria and protists) and DOM show a clear compositional connectivity from surface to the depth of 1000 m, highlighting the controls of sinking particle over microbial connectivity from the epipelagic to mesopelagic zone. However, due to the biological migration and ocean mixing, the fecal-associated bacteria and protistan consumers unexpectedly emerge and the degradation index of DOM substantially alters around 1000–1200 m. Collectively, we unveil the significance of multi-faceted particle dispersion, which supports the connectivity and variability of deep ocean microbial communities.

SMARTS-Based Decision Support Model for CMMS Selection in Integrated Building Maintenance Management

An Integrated Maintenance System (IMS) represents a coordinated methodology including different maintenance policies, such as preventive and corrective. These systems rely on Computerized Maintenance Management Systems (CMMSs), specialized software available from multiple suppliers. Given the diverse features of commercial CMMS software, this work aims to develop a decision support model for CMMS evaluation emphasizing an integrated perspective within IMS. A Simple Multi-Attribute Rating Technique using Swings (SMARTS) method was used to build the decision model. Five existing market software were evaluated, and a minimum profile was defined for IMS requirements. Three of the assessed software types met these minimum IMS requirements, while the absence of certain features limited scores for others. The results obtained from the decision support model provide a simple and synthetic way to support decision-makers and promote a systemic view of the software features. The evaluation model has the advantage of adopting criteria that integrate software evaluation; its framing in a building maintenance management model; and new technological trends, such as Building information modeling (BIM), Virtual Reality (VR), Augmented Reality (AR), and Internet of Things (IoT). Considering these outcomes, future developments and alternatives can capitalize on these trends.

What’s love got to do with it? A systemic view of agape

In this article, we explore what love feels like in systemic therapy, for us, as practitioners. The idea for writing this article as a personal set of reflections was born in our walking to work relationship. We both have the same part time visiting position in a systemic training programme in a Norwegian University. We leave our hotel at 8a.m. to walk up the hill, talking about training, supervision and therapy as we go along. Increasingly our attention turned to the experience of love in therapy – to what it looked like, to what it felt like, to what it meant, and to the inevitable challenges, risks and benefits of naming love in the therapy process. We soon discovered there was a relative silence on this topic in the systemic literature, and we wondered why. We open this article with a series of further reflections and questions to each other, following our first publication on therapeutic love as agape (Sheehan and Vetere, 2023). We identify agape as the best characterisation of the kind of love emergent in therapeutic relationships and conclude this article with a brief look at the existing systemic literature on the topic. In turn, we invite you, the reader, if you will, to respond.