View Of System Research Articles

Value co-creation between coworking spaces and startups in different stages of development

Coworking spaces (CWS) are sustainable pillars for the development of entrepreneurial ecosystems, providing a variety of relevant services, which are co-created in exchanges experienced among different actors. During the pandemic, CWS experienced structural transformations. This study identified, characterised, and evaluated the relevance of the services provided by CWS considering the different stages in the evolution of a startup. For this, a narrative literature review was conducted and the second phase of the research included the development of netnographic initiatives and the conduction of multiple case studies. As a result, six categories of services were identified, comprehending 36 services, whose relevance varies considering the maturity level of the startup. This research contributes to the literature by providing a systemic view of the state of practice of these services in the context of CWS, as well as identifying the changes CWS environments are experiencing driven by digital transformations.
 Keywords: Coworking Spaces, startup, sharing economy, co-creation, digital transformation.

Phylogenomics analysis of velvet regulators in the fungal kingdom.

All life forms have evolved to respond appropriately to various environmental and internal cues. In the animal kingdom, the prototypical regulator class of such cellular responses is the Rel homology domain proteins including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). Fungi, the close relatives of animals, have also evolved with their own NF-κB-like regulators called velvet family proteins to govern cellular and chemical development. Here, we conducted a detailed investigation of the taxonomic broad presence of velvet proteins. We observed that velvet proteins are widely distributed in the fungal kingdom. Moreover, we have identified and characterized 21 major velvet clades in fungi. We have further revealed that the highly conserved velvet domain is composed of three distinct motifs and acts as an evolutionarily independent domain, which can be shuffled with various functional domains. Such rearrangements of the velvet domain have resulted in the functional and type diversity of the present velvet regulators. Importantly, our in-deep analyses of the primary and 3D structures of the various velvet domains showed that the fungal velvet domains can be divided into two major clans: the VelB and the VosA clans. The 3D structure comparisons revealed a close similarity of the velvet domain with many other eukaryotic DNA-binding proteins, including those of the Rel, Runt, and signal transducer and activator of transcription families, sharing a common β-sandwich fold. Altogether, this study improves our understanding of velvet regulators in the fungal kingdom.IMPORTANCEFungi are the relatives of animals in Opisthokonta and closely associated with human life by interactive ways such as pathogenicity, food, and secondary metabolites including beneficial ones like penicillin and harmful ones like the carcinogenic aflatoxins. Similar to animals, fungi have also evolved with NF-κB-like velvet family regulators. The velvet proteins constitute a large protein family of fungal transcription factors sharing a common velvet domain and play a key role in coordinating fungal secondary metabolism, developmental and differentiation processes. Our current understanding on velvet regulators is mostly from Ascomycota fungi; however, they remain largely unknown outside Ascomycota. Therefore, this study performed a taxonomic broad investigation of velvet proteins across the fungal kingdom and conducted a detailed analysis on velvet distribution, structure, diversity, and evolution. The results provide a holistic view of velvet regulatory system in the fungal kingdom.

Theoretical and Technological Analysis of Smart Manufacturing Systems

This study presents a comprehensive evaluation of the current status of smart manufacturing systems (SMS), with a specific emphasis on their theoretical significance in the context of technology management and technology development. The paper examines the theoretical underpinnings of development of technology through the lens of Rogers' Diffusion of Innovation (DoI) theory. Additionally, the paper employs Rieck and Dickson's Technology Strategy Model (TSM) to emphasize the importance of technology management. By incorporating the Management of Technology (MOT) theory, the paper aims to provide a comprehensive framework for understanding and shaping technology development. The integration of several technologies inside the SMS system has been the subject of discussion in relation to patenting. The features of Smart Manufacturing Systems (SMS) have been examined in order to analyze the comprehensive components of this emerging technological system. The suggested SMS model of the clothing manufacturing unit has been used to represent the global textile complex. This research incorporates recent scholarly publications and advancements in technology to provide a comprehensive understanding of future manufacturing system views. The objective is to minimize human involvement and enhance production efficiency within the manufacturing business. The primary components of the SMS have been identified as the cyber-physical system, artificial intelligence (AI), digital twin, enterprise resource planning, additive manufacturing, and big data.

Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS.

Advances in machine learning (ML) methodologies, combined with multidisciplinary collaborations across biological and physical sciences, has the potential to propel drug discovery and development. Open Science fosters this collaboration by releasing datasets and methods into the public space; however, further education and widespread acceptance and adoption of Open Science approaches are necessary to tackle the plethora of known disease states. In addition to providing much needed insights into potential therapeutic protein targets, we also aim to demonstrate that small patient datasets have the potential to provide insights that usually require many samples (>5,000). There are many such datasets available and novel advancements in ML can provide valuable insights from these patient datasets. Using a public dataset made available by patient advocacy group AnswerALS and a multidisciplinary Open Science approach with a systems biology augmented ML technology, we aim to validate previously reported drug targets in ALS and provide novel insights about ALS subpopulations and potential drug targets using a unique combination of ML methods and graph theory. We use NetraAI to generate hypotheses about specific patient subpopulations, which were then refined and validated through a combination of ML techniques, systems biology methods, and expert input. We extracted 8 target classes, each comprising of several genes that shed light into ALS pathophysiology and represent new avenues for treatment. These target classes are broadly categorized as inflammation, epigenetic, heat shock, neuromuscular junction, autophagy, apoptosis, axonal transport, and excitotoxicity. These findings are not mutually exclusive, and instead represent a systematic view of ALS pathophysiology. Based on these findings, we suggest that simultaneous targeting of ALS has the potential to mitigate ALS progression, with the plausibility of maintaining and sustaining an improved quality of life (QoL) for ALS patients. Even further, we identified subpopulations based on disease onset. In the spirit of Open Science, this work aims to bridge the knowledge gap in ALS pathophysiology to aid in diagnostic, prognostic, and therapeutic strategies and pave the way for the development of personalized treatments tailored to the individual's needs.

Neutral Currents in Large Public Lighting Networks

The modern large public lighting networks are characterized by two major aspects that rise problems from both power quality and neutral current point of view in low voltage wye-connected three-phase electrical systems: (i) the supply system is unbalanced loaded; (ii) the presence of discharge sources. It is important to underline that nowadays,these aspects are not taken into account in the proper sizing of neutral conductors. The paper presents a simplified but enough accurate methodology to estimate the RMS value of neutral currents in lighting networks. The theoretical relationships are illustrated for a three-phase public lighting network that contains high pressure sodium lamps.

Mapping Renewable Energy among Antarctic Research Stations

This paper presents an overview of current electricity generation and consumption patterns in the Antarctic. Based on both previously published and newly collected data, the paper describes the current status of renewable-energy use at research stations in the Antarctic. A more detailed view of electricity systems is also presented, demonstrating how different types of resources may be used and combined. The paper will serve as a guide to various renewable-energy generation technologies, highlighting well-established praxis, lessons learned, and potential ideas for improvement. Several renewable electricity generation technologies that have proven effective for use in the Antarctic environment are described. as well as those that are currently in use. Finally, the paper summarizes the major lessons learned to support future projects and close the knowledge gap. The use of renewable-energy sources has the potential to reduce research stations’ greenhouse gas emissions, making research in Antarctica more sustainable. The availability of high-quality energy is crucial for survival and to allow scientists to conduct meaningful research at research stations under harsh Antarctic conditions.

An Analysis of the Differences in Family Education Between China and the United States under the Orientation of Educational Policies

Family education is influenced by many factors, and education policy is one of the most important factors. There is a big difference between China and the United States in terms of family education. From the point of view of the different admission systems of colleges and universities in the two countries, the diversified admission system of the United States contributes to the formation of the concept of "quality education" family education. In contrast, the single-indicator admission system of China leads to the concept of "teaching to the test" family education to a certain extent. This paper examines the differences between the admissions systems of China and the United States and their impact on the differences between family education in China and the United States and makes suggestions for family education in China through a comparative analysis of the strengths and weaknesses of family education in the two countries. Parents should have a long-term view of education and regard academic performance as one of the goals of family education, and more importantly, take the comprehensive development of children as the primary goal, so that they can raise healthy and excellent children.

WHAT DO WE KNOW ABOUT CUSTOMER SATISFACTION IN THE HOSPITALITY AND TOURISM INDUSTRY? THE GLIMPSE FROM A BIBLIOMETRIC ANALYSIS

Numerous previous studies have emphasized that investigating customer behavior in hospitality and tourism services is a crucial research area that significantly impacts the industry's success, particularly in terms of customer satisfaction. According to a report by Small Business Chron, customer satisfaction holds paramount importance in the hospitality and tourism industry, where customers pay close attention to the quality of service they receive. The goal of this paper is to offer researchers a systematic view of how this topic contributes to the development of effective research channels for future analysis and research on the subject. The method used is bibliometric analysis, and mapping analysis has been conducted involving 107 articles from the SCOPUS database on customer satisfaction spanning from the year 2013 to 2023. The study employs bibliometric analysis of literature using Vosviewer. The findings reveal that research on customer satisfaction has steadily grown over the study period in the hospitality and tourism industry. The network analysis of customer satisfaction publications indicates that important themes covered include service quality, customer experience, customer value, and customer reviews

IIoT System Canvas — From architecture patterns towards an IIoT development framework

Industrial Internet of Things (IIoT) solutions are poised to enable digital transformation across industry verticals. However, the diversity of IIoT applications has resulted in a multitude of constantly evolving technologies, standards, and reference architectures with differing terminologies and frequent incompatibilities. A unified approach to describe and develop IIoT systems is needed not only to ease development, but also identify cross-cutting research gaps and exploit synergies.Building on a substantial literature survey, this work proposes the IIoT Development Framework, taking a systems engineering perspective to derive an IIoT Systems Development Process along with several key tools: After defining business objectives, an IIoT system is broken down into system components using the IIoT Architecture Pattern. Second, functionalities for each component are identified leveraging morphological boxes. Third, suitable technologies capable of providing these functionalities need to be selected. For this task, technology selection criteria and processes as well as technology comparison sheets are detailed, covering key technologies. Throughout the entire process of technology selection, the IIoT System Canvas is the central tool summarizing components, required functionalities and selected technologies to provide a comprehensive end-to-end view of the entire IIoT system. It may be understood as a modeling template akin to the Business Model Canvas.The IIoT Development Framework aims to achieve three objectives: Completeness (covering all aspects of IIoT systems), actionability (low barriers for researchers and practitioners) and generalizability (covering not just one product family, but cutting across industry verticals). The framework is validated by comparison to the state of the art and application to a set of use cases covering multiple industry verticals with differing requirements, showing superior results especially in terms of completeness and actionability, while maintaining generalizability.

Crash-Resilient Decentralized Synchronous Runtime Verification

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Runtime verification</i> is a technique, where a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">monitor</i> process extracts information from a running system in order to evaluate whether system executions violate or satisfy a given correctness specification. In this paper, we consider runtime verification of synchronous distributed systems, where a set of decentralized monitors that only have a partial view of the system are subject to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">crash failures</i> . In this context, it is unavoidable that monitors may have different views of the underlying system, and, therefore, have different opinions about the correctness property. We propose an automata-based synchronous monitoring algorithm that copes with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$t$</tex-math></inline-formula> crash monitor failures. In our proposed approach, local monitors do not communicate their explicit reading of the underlying system. Rather, they emit a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">symbolic verdict</i> that efficiently encodes their partial views. This significantly reduces the communication overhead. To this end, we also introduce an (offline) SMT-based monitor synthesis algorithm, which results in minimizing the size of monitoring messages. We evaluate our algorithm on a wide range of formulas and observe an average of 2.5 times increase in the number of states of the monitor automaton.

Exploring the Path of Village Protection and Renewal Strategy Based on the Maximum Information Entropy Model in the Context of Rural Revitalisation

Abstract A comprehensive and systematic view and solution to the protection and renewal of traditional villages can help actively promote and implement the strategy of rural revitalization. This paper constructs a village protection and renewal evaluation system based on the maximum information entropy model, utilizes the entropy weight method to build the index weight evaluation matrix, and introduces the confidence factor to correct the index weights, realizing the combination of the system. Then, based on the linear weighting method to carry out a comprehensive assessment of village protection and renewal development, and based on the assessment results to formulate a personalized village protection and renewal strategy, and the feasibility analysis of the strategy with the village of T city. The results show that village protection and renewal in T city villages generally indicate an upward trend from 2016 to 2023, and the comprehensive evaluation index reached a peak of 0.3227 in 2023. In the case study, the linear regression equations fitted to the scattering points of the uptown residential area villages and the entire T city villages’ axes intersect with a difference in slopes of 14.5123. The angle of the regression line continues to increase in comparison with 2016, indicating that the role of traditional village protection planning is significant. Village protection planning plays an important role in verifying the effectiveness of the formulated village protection and renewal strategy, which can promote the development of village regional characteristics for the good.

Strategic Key Elements in Big Data Analytics as Driving Forces of IoT Manufacturing Value Creation: A Challenge for Research Framework

Big Data (BD)-driven business intelligence (BI) is considered to be a new development stage within industrial engineering management to achieve higher business value creation. The article provides extensive research of BD-driven approaches to identify strategic knowledge and value-creating components within Internet of Things (IoT) manufacturing. Due to previous research studies focused mostly on partial solutions and lack a holistic view, this article topic is still far from being sufficiently explored and resolved. The article presents the results of an extensive research study of contemporary professional literature with a specific aim to provide a more holistic and systematical view on the current state and future trends in this issue. To solve this high complex research problem, both quantitative and qualitative research methodology approaches are used. The article is primarily based on a systematic literature review covering 187 essential and 36 additional current research papers within the Web of Science and Scopus database from 2012 to the present. Research findings identify the seven key strategic elements determining that Big Data analytics (BDA) can become a real and tremendous business value creation driver within IoT intelligent manufacturing. These research results provide important conclusions and implications for challenging future investigations into BDA and BI systems in the context of advancing the Industry 4.0 revolution. In conclusion, we propose a final suggestion in the form of a strategic future research chain from IoT through BDA to value creation based on BD intelligence within IoT manufacturing, whereas seven strategic elements might play a crucial.

Dancing with AI: AI-employee collaboration in the systemic view

Dancing with AI: AI-employee collaboration in the systemic view

Alterations of SARS-CoV-2 Evolutionary Dynamics by Pharmaceutical Factors

Abstract The outbreak of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been influenced by the human response to the virus. These responses have undoubtedly impacted the evolutionary dynamics of the virus in ways distinct from a scenario lacking a widespread response. Two important pharmaceutical interventions, vaccination and the utilization of medications, particularly molnupiravir, known to have mutagenic properties, were the focus of this article. The impact of molnupiravir on human health was evaluated through 3 mechanisms: viral resistance, mutagenesis of SARS-CoV-2, and mutagenesis occurring in patients undergoing treatment with molnupiravir. These mechanisms, as well as the impact of vaccination, have inadvertently given rise to unforeseen challenges in the management of the COVID-19 crisis. Taking a systems view in future pandemic responses, and taking into account the evolution of the pandemic virus, may be critical to ending the pandemic at an earlier date.

Theorizing Entrepreneurial Ecosystems by Taking a Systems View?

Theorizing Entrepreneurial Ecosystems by Taking a Systems View?

ОБОСНОВАНИЕ НЕОБХОДИМОСТИ ВНЕДРЕНИЯ КРОССПЛАТФОРМЕННЫХ ГЕНЕРАТИВНЫХ ЦИФРОВЫХ ИННОВАЦИОННЫХ ТЕХНОЛОГИЙ В КООПЕРАЦИИ

This research paper substantiates the necessity of implementing cross-platform digital innovation technologies of entrepreneurs' co-operation based on artificial intelligence. Emphasis is placed on the mechanism of direct super-fast cooperation and super agility in making managerial decisions to improve the efficiency of businesses of different taxonometric levels. The scope of application of the solutions is elaborated in agriculture, industrial production, trade, services, and general management. The article stresses the importance of developing programmes of interaction between small and medium-sized enterprises in order to accelerate the development of the Russian economy. Special attention is paid to the introduction of generative digital technological innovations in the system of digitalisation of cooperation and integration as factors contributing to the growth of economic activity efficiency and significant reduction of risks for business. In the coming years, expert knowledge of strategic, tactical, operational as well as financial management will significantly change the business culture and improve the quality of management of organisations. This study shows the prospect and depth of increased connectivity through multi-vector networking among various market participants. In his hypothesis, the author points to the geometric growth of an economy based on a revolutionary technological foundation, when autonomous digital business models, created with successful experiences and dynamically changing legislation of local or international format, will be able to instantly connect business chains in a huge flow of information and business resources. The implementation of cross-platform generative digital innovation models represents a huge business niche of providing and receiving unique consulting services. The article outlines and develops a new view of integrative economic systems in the digital economy, allowing businesses to reach a new qualitative level of development and efficiency.

New challenges for city logistics: a unified view of energy and transport systems for addressing sustainability

Urban freight transport has been studied from the point of view of economic efficiency, however, it is also important to consider energy efficiency with respect to the goals of the 2030 Agenda. The method used in this paper is to reconstruct the cycles from production to the end user for energy and transport/logistics by identifying the intersection areas, which turn out to be the vehicles and the exchange nodes. The measurement of impacts is introduced considering the “carbon footprint” indicator. The continuous advancement of automotive technologies is highlighted that requires a continuous updating of the impact results to make optimal economic and energy choices for city logistics within the framework identified by Agenda 2030.

Induction of puberty vs. induction of ovulation using steroid hormones in beef heifers: a comprehensive review.

This review elucidates the physiological and endocrinological processes intrinsic to puberty and ovulation induction protocols in Bos indicus and Bos taurus beef heifers. Puberty is a complex physiological event involving gonadotropic and metabolic changes that lead to sexual maturity, first ovulation, and regular reproductive cycles, enabling females to reproduce. Exposure to progesterone-based hormonal protocols, with or without additional hormones, can reduce the age at first ovulation and improve sexual maturity through stimuli in the hypothalamus-pituitary-gonadal (HPG) axis and uterine development. However, inducing puberty differs from inducing ovulation, as it does not ensure the heifer will continue cycling or be ready to establish and maintain pregnancy after hormonal exposure. Regardless of the pharmacological basis, studies consistently report that beef heifers that had a corpus luteum (CL) prior to the timed-artificial insemination (TAI) protocol, have greater expression of estrus in response to synchronization and greater pregnancy per AI compared to heifers without a CL. The combination of P4 and E2 significantly impacts uterine development, increasing reproductive efficiency. Exposure to P4 causes a positive effect on inducing ovulation. However, studies indicate that the addition of E2 esters at the time of P4 device removal increases the ovulation rate. In general, the studies showed that fertility varied according to the type of the ovulation induction protocol used, but with inconsistent results. Although ovulation induction protocols are strategic tools to accelerate sexual maturity, a holistic view of the entire system is extremely important, combining integration with genetics and nutrition to enhance the reproductive outcomes of beef heifers. Future research is needed to understand and refine these protocols, driving the efficiency of beef cattle production systems.

A systemic framework for Enterprise Resource Planning systems: A bibliometric networking analysis

Enterprise Resource Planning (ERP) systems have been considered by numerous organizations as a key part of their strategy to support the optimization of their processes and enhancement of their business performance. However, managing business processes through ERP systems and their integration with other systems and data sources is complicated. Part of this difficulty comes from the lack that managers, executives, and implementers have of an integrated and holistic view of ERP systems. This article presents a systemic framework for ERP systems based on many publications as a data sources. It derives from a bibliometric network analysis previously made based on a systematic literature review on ERP major concerns. The methodology used to do the systematic literature review was PRISMA 2020, and the software used to do the bibliometric networking analysis was VOSViewer. The bibliometric analysis was based on the network built based on the previous systematic review and on the clusters that emerged from it. Fifty-nine terms with the highest occurrence were chosen to support six clusters that were found. The data obtained from the bibliometric map, specifically the meaning of each identified cluster, was analysed. These clusters were used as the pillars of the systemic framework proposal. The clusters were used as core areas of the ERP systems field, respectively: (1) infrastructure & technology, (2) leadership & people, (3) processes & performance, (4) implementation & adoption, (5) supplier & implementer, and (6) enterprise & application architecture. The six different clusters and their main relationships were analysed and discussed.

Collaborative Multi-Agent Video Fast-Forwarding

Multi-agent applications have recently gained significant popularity. In many computer vision tasks, a network of agents, such as a team of robots with cameras, could work collaboratively to perceive the environment for efficient and accurate situation awareness. However, these agents often have limited computation, communication, and storage resources. Thus, reducing resource consumption while still providing an accurate perception of the environment becomes an important goal when deploying multi-agent systems. To achieve this goal, we identify and leverage the overlap among different camera views in multi-agent systems for reducing the processing, transmission and storage of redundant/unimportant video frames. Specifically, we have developed two collaborative multi-agent video fast-forwarding frameworks in distributed and centralized settings, respectively. In these frameworks, each individual agent can selectively process or skip video frames at adjustable paces based on multiple strategies via reinforcement learning. Multiple agents then collaboratively sense the environment via either 1) a consensus-based distributed framework called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DMVF</b> that periodically updates the fast-forwarding strategies of agents by establishing communication and consensus among connected neighbors, or 2) a centralized framework called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MFFNet</b> that utilizes a central controller to decide the fast-forwarding strategies for agents based on collected data. We demonstrate the efficacy and efficiency of our proposed frameworks on a real-world surveillance video dataset VideoWeb and a new simulated driving dataset CarlaSim, through extensive simulations and deployment on an embedded platform with TCP communication. We show that compared with other approaches in the literature, our frameworks achieve better coverage of important frames, while significantly reducing the number of frames processed at each agent.