Network Events Research Articles

Networking Frictions and Entrepreneurial Learning in Developing Economies

Relationships with peers help entrepreneurs learn and improve firm performance. Recent scholarship confirms that events—social gatherings such as mixers, conferences, or training programs—can help entrepreneurs build valuable social connections. Yet, for entrepreneurs in developing economies, networking frictions may make connecting with peers challenging and undermine the benefits of events. We argue that when networking frictions are high, the value of events will lie more in connecting neighbors rather than bringing together distant peers. In the presence of networking frictions, neighbors are both less likely to be someone the entrepreneur has already learned from and easier to sustain a relationship with. To test this argument, we use data from a series of networking events in Togo during which entrepreneurs were randomly assigned to meet with peers from across the city of Lomé. We find that entrepreneurs who were assigned to neighboring peers were much more likely to sustain a relationship, learn from their peer’s management knowledge, and in turn benefit more: Profits increase by 10% when entrepreneurs get to know peers who are located on average 1 km closer to them. Our results highlight the central role that networking frictions play in shaping who entrepreneurs in developing economies can successfully learn from. This paper was accepted by Lamar Pierce, organizations. Funding: Ewing Marion Kauffman Foundation [Dissertation Fellowship] and the Strategic Management Society [SRF Dissertation Fellowship]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.00281 .

Arginine vasopressin activates serotonergic neurons in the dorsal raphe nucleus during neonatal development in vitro and in vivo

Birth stress is a risk factor for psychiatric disorders and associated with exaggerated release of the stress hormone arginine vasopressin (AVP) into circulation and in the brain. In perinatal hippocampus, AVP activates GABAergic interneurons which leads to suppression of spontaneous network events and suggests a protective function of AVP on cortical networks during birth. However, the role of AVP in developing subcortical networks is not known. Here we tested the effect of AVP on the dorsal raphe nucleus (DRN) 5-hydroxytryptamine (5-HT, serotonin) system in male and female neonatal rats, since early 5-HT homeostasis is critical for the development of cortical brain regions and emotional behaviors. We show that AVP is strongly excitatory in neonatal DRN: it increases excitatory synaptic inputs of 5-HT neurons via V1A receptors in vitro and promotes their action potential firing through a combination of its effect on glutamatergic synaptic transmission and a direct effect on the excitability of these neurons. Furthermore, we identified two major firing patterns of neonatal 5-HT neurons in vivo, tonic regular firing and low frequency oscillations of regular spike trains and confirmed that these neurons are also activated by AVP in vivo. Finally, we show that the sparse vasopressinergic innervation in neonatal DRN originates exclusively from cell groups in medial amygdala and bed nucleus of stria terminalis. Hyperactivation of the neonatal 5-HT system by AVP during birth stress may impact its own functional development and affect the maturation of cortical target regions, which may increase the risk for psychiatric conditions later on.

Welcome to the first issue of the College’s Asia Pacific Journal of Health Management for 2024.

The College is going from strength to strength with membership increasing notably over the past few months and great attendance at College free webcast events as well as growing participation in other ACHSM professional development opportunities. In March a very successful one day Conference was held in Auckland, New Zealand with many from Australia and nearby countries amongst the more than 250 who attended this event. Through attending that conference, we now have 58 new College members in New Zealand who can take advantage of the benefits of College membership like this Journal, free webcasts, local networking events and access to bespoke professional development for health leaders. Our Fellowship Program for 2024 has commenced with 46 Associate Fellows applying themselves to our most prestigious capstone program. Further we have over 30 current enrolments to undertake Certification with those College members committing to maintaining their profession through the expectations of this credential. We also launched a Managing Digital Health micro credential that aligns fully with the digital health competencies in the ACHSM Master Health Service Management Competency Framework. We are in the process of distributing digital badges to all membership levels and Certified Health Managers and Executives for use on media such as LinkedIn, CVs and email signatures. These badges provide and outline of what it means to be a Fellow, Certified Health Manager or Executive of ACHSM. In this issue, as is the purpose of the Journal, there are learned articles on the importance of continuing to self-reflect on our leadership behaviours and workplace relationships. I take this opportunity of thanking Prof Mark Avery our Editor for his great work in maintaining a high quality of publication and ensuring relevancy to leaders in all sectors. I commend these to you and continue to wish you success in your ongoing leadership journey.

PMUs data based detection of oscillatory events and identification of their associated variable: Estimation of information measures approach

Information theory can be a useful tool for quantifying the perturbations in the associated state variables at the time of disturbance occurrence. The study introduces a framework for the spectral decomposition of multivariate information measures to detect initiation of low frequency oscillations (LFOs), caused due to physical events in the power grid. A frequency-specific quantification of the information is shared between a target variable and two source variables from their time series data. Initially, the approach is applied on different synthetic test signals having different oscillatory frequency modes and decay time constant. Then, approach is extended on PMUs signals. The combination of cross-spectral and information-theoretic approaches is applied for the multi-variable analysis of PMUs signals from the same bus. The interdependence among the frequency, voltage angle and voltage magnitude, corresponding to specific oscillations, manifested due to cause-effect relationships obtained in terms of statistics is estimated. The dynamics in terms of unique (interaction), redundant and synergetic information is determined with the contribution from two of these three signals as source variables to target variable (frequency/voltage angle). This provides a direct coupling to identify driver-response relationships between source variables and target variable to indicate the onset of LFOs, following physical events in power network. The extension of approach among the variables from different buses aids to identify the responsible area of event occurrence.

JAPPI: An unsupervised endpoint application identification methodology for improved Zero Trust models, risk score calculations and threat detection

The surge in global digitalization triggered by COVID-19 has led to a significant increase in internet traffic and has precipitated a rapid transformation of the network security landscape. Despite being increasingly difficult, accurate traffic inspection is vital for ensuring productivity while reliably protecting internal assets. Endpoint application identification enables high accuracy inspection and detection by providing network security solutions with specific context on individual connections. However, achieving it in real-time with standard fingerprinting methods based only on client-side traffic has proven to be a challenging problem with no comprehensive solution thus far. In this article, we present a new methodology for identifying endpoint applications from network traffic, utilizing machine learning. Our methodology leverages similarities in the pre-hash string of the JA3 algorithm for fingerprinting application specific TLS Client Hello messages. By utilizing well-known clustering algorithms it is possible to identify the underlying TLS libraries and the application from the traffic remarkably better than with simple string-based matching. Our model can categorize 99,5% of the traffic in a controlled network, and 93,8% in an uncontrolled network, compared to 0,1% and 0,2% using simple string matching. Our methodology is especially effective for enhancing Zero Trust models, calculating a risk score for network events, and improving threat detection accuracy in network security solutions.

Undergraduate Ancillaries in the Economics Department at the University of North Carolina at Chapel Hill

The Economics Department at the University of North Carolina at Chapel Hill (UNC) has had a long-term commitment to offering extra-curricular opportunities for undergraduate students to enhance their learning beyond the classroom. These opportunities include research, problem-solving, leadership development, Undergraduate Learning Assistance (ULA), peer tutoring, and networking events, among others. Given the Economics program’s substantial size within UNC’s College of Arts and Sciences—with over 1400 declared or intended majors in recent years—it is important to structure the activities in a manner that accommodates students’ diverse interests as well as their time constraints. In this paper, we introduce these different activities and discuss their scope, skill objectives, and time commitment. The benefits to students include opportunities for community, networking, exposure, application, teamwork, presentation, analysis, and research. We also discuss several challenges a department faces to successfully offer these diverse opportunities.

A Review of Research on Social Network Event Detection Methods

In recent years, with the development of technological infrastructure and the use of tech products, internet usage has become widespread globally. Significant advancements have been made in the use of social networks, which are now more readily accessible through Internet and Web 3.0 technologies such as Facebook, Twitter, and Instagram. Consequently, over the past decade, numerous researchers have been developing methods for event detection based on data collected from social media platforms. The methodologies devised for discovering events are typically modular in design and novel in terms of scale and speed. To review the research in this field, we have compiled existing works on social network event detection and conducted a comprehensive and in-depth survey. Methods for social network event detection are elaborated and categorized, with performance evaluations conducted using relevant metrics. Finally, we offer perspectives on future directions.

Arid1b haploinsufficiency in cortical inhibitory interneurons causes cell-type-dependent changes in cellular and synaptic development.

Autism spectrum disorder (ASD) presents with diverse cognitive and behavioral abnormalities beginning during early development. Although the neural circuit mechanisms remain unclear, recent work suggests pathology in cortical inhibitory interneurons (INs) plays a crucial role. However, we lack fundamental information regarding changes in the physiology of synapses to and from INs in ASD. Here, we used transgenic mice to conditionally knockout one copy of the high confidence ASD risk gene Arid1b from the progenitors of parvalbumin-expressing fast-spiking (PV-FS) INs and somatostatin-expressing non-fast-spiking (SST-NFS) INs. In brain slices, we performed paired whole-cell recordings between INs and excitatory projection neurons (PNs) to investigate changes in synaptic physiology. In neonates, we found reduced synaptic input to INs but not PNs, with a concomitant reduction in the frequency of spontaneous network events, which are driven by INs in immature circuits. In mature mice, we found a reduction in the number of PV-FS INs in cortical layers 2/3 and 5. However, changes in PV-FS IN synaptic physiology were cortical layer and PN cell-type dependent. In layer 5, synapses from PV-FS INs to subcortical-projecting PNs were weakened. In contrast, in layer 2/3, synapses to and from PV-FS INs and corticocortical-projecting PNs were strengthened, leading to enhanced feedforward inhibition of input from layer 4. Finally, we found a novel synaptic deficit among SST-NFS INs, in which excitatory synapses from layer 2/3 PNs failed to facilitate. Our data highlight that changes in unitary synaptic dynamics among INs in ASD depend on neuronal cell-type.

'Queer in Microbiology': a Microbiology Society members' endeavour for creating a safe and inclusive environment for LGBTQIA+ microbiologists.

The past decade has seen growing awareness of the challenges faced by LGBTQIA+ scientists, including discrimination in the workplace and the lack of representation. Initiatives such as 500 Queer Scientists, Pride in STEM and the Microbiology Society's LGBTQIA+ events have been instrumental in promoting inclusivity in science, technology, engineering, mathematics and medicine (STEMM). The Microbiology Society and its members have played a pivotal role in these efforts and summarized here are their initiatives towards safer and more inclusive scientific and research environments. Starting with a series of interviews and blog posts about the experiences of LGBTQIA+ microbiologists in research, the Society has promoted the organization of networking and social events and developed guidelines for creating more inclusive scientific conferences. These initiatives have not only improved the representation and visibility of LGBTQIA+ individuals in microbiology, but have also served as a blueprint for similar efforts in other scientific areas. Nevertheless, despite improvements in some areas, full inclusion of LGBTQIA+ scientists is still hindered by societal and institutional policies around the world. Here, we propose novel measures to support and empower LGBTQIA+ microbiological communities within learned societies.

Clinical Implications and Molecular Features of Extracellular Matrix Networks in Soft Tissue Sarcomas.

The landscape of extracellular matrix (ECM) alterations in soft tissue sarcomas (STS) remains poorly characterized. We aimed to investigate the tumor ECM and adhesion signaling networks present in STS and their clinical implications. Proteomic and clinical data from 321 patients across 11 histological subtypes were analyzed to define ECM and integrin adhesion networks. Subgroup analysis was performed in leiomyosarcomas (LMS), dedifferentiated liposarcomas (DDLPS), and undifferentiated pleomorphic sarcomas (UPS). This analysis defined subtype-specific ECM profiles including enrichment of basement membrane proteins in LMS and ECM proteases in UPS. Across the cohort, we identified three distinct coregulated ECM networks which are associated with tumor malignancy grade and histological subtype. Comparative analysis of LMS cell line and patient proteomic data identified the lymphocyte cytosolic protein 1 cytoskeletal protein as a prognostic factor in LMS. Characterization of ECM network events in DDLPS revealed three subtypes with distinct oncogenic signaling pathways and survival outcomes. Evaluation of the DDLPS subtype with the poorest prognosis nominates ECM remodeling proteins as candidate antistromal therapeutic targets. Finally, we define a proteoglycan signature that is an independent prognostic factor for overall survival in DDLPS and UPS. STS comprise heterogeneous ECM signaling networks and matrix-specific features that have utility for risk stratification and therapy selection, which could in future guide precision medicine in these rare cancers.

Co-creating and implementing a novel pre-conference event to promote equity and inclusivity among academic researchers and people who use drugs.

This commentary draws on our experience organising a targeted networking event at the 10th International Conference on Health and Hepatitis in Substance Users, in Glasgow, Scotland in October 2022. The event, held the day before the conference, brought together people with lived and living experiences of drug use and early- and mid-career researchers on an equitable basis. We offer reflections, focussing on how the event promoted community-academic engagement from members of the respective groups. We provide recommendations for how conferences can organise to engage with people who use drugs-both those with lived and living experience and foster greater inclusion for all attendees.

Network state transitions during cortical development.

Mammalian cortical networks are active before synaptogenesis begins in earnest, before neuronal migration is complete, and well before an animal opens its eyes and begins to actively explore its surroundings. This early activity undergoes several transformations during development. The most important of these is a transition from episodic synchronous network events, which are necessary for patterning the neocortex into functionally related modules, to desynchronized activity that is computationally more powerful and efficient. Network desynchronization is perhaps the most dramatic and abrupt developmental event in an otherwise slow and gradual process of brain maturation. In this Review, we summarize what is known about the phenomenology of developmental synchronous activity in the rodent neocortex and speculate on the mechanisms that drive its eventual desynchronization. We argue that desynchronization of network activity is a fundamental step through which the cortex transitions from passive, bottom-up detection of sensory stimuli to active sensory processing with top-down modulation.

Unraveling Cyber Threats: The Role of Forensic Investigation in Cyber Security

In today's digital landscape, cyber threats pose significant risks to organizations worldwide, demanding robust cybersecurity measures. Forensic investigation is pivotal in identifying, analyzing, and mitigating these threats, providing insights into their nature and impact for effective incident response. Leveraging forensic techniques and tools empowers organizations to fortify defense strategies and resilience against evolving threats. Cyber forensics encompasses diverse domains such as digital, data, system, and network forensics, crucial for legally admissible evidence presentation. System forensics focuses on standalone machine investigations, while network forensics scrutinizes network events. Data forensics involves analyzing volatile and non-volatile data, while proactive forensics facilitates ongoing evidence collection for enhanced preparedness. Email forensics addresses the evidential role of emails in forensic investigations.

XAI Human-Machine collaboration applied to network security

Cyber attacking is easier than cyber defending—attackers only need to find one breach, while the defenders must successfully repel all attacks. This research demonstrates how cyber defenders can increase their capabilities by joining forces with eXplainable-AI (XAI) utilizing interactive human-machine collaboration. With a global shortfall of cyber defenders there is a need to amplify their skills using AI. Cyber asymmetries make propositional machine learning techniques impractical. Human reasoning and skill is a key ingredient in defense and must be embedded in the AI framework. For Human-Machine collaboration to work requires that the AI is an ultra-strong machine learner and can explain its models. Unlike Deep Learning, Inductive Logic Programming can communicate what it learns to a human. An empirical study was undertaken using six months of eavesdropped network traffic from an organization generating up-to 562K network events daily. Easier-to-defend devices were identified using a form of the Good-Turing Frequency estimator which is a promising form of volatility measure. A behavioral cloning grammar in explicit symbolic form was then produced from a single device's network activity using the compression algorithm SEQUITUR. A novel visualization was generated to allow defenders to identify network sequences they wish to explain. Interactive Inductive Logic Programming (the XAI) is supplied the network traffic meta data, sophisticated pre-existing cyber security background knowledge, and one recurring sequence of events from a single device to explain. A co-inductive process between the human cyber defender and the XAI where the human is able to understand, then refute and shape the XAI's developing model, to produce a model that conforms with the data as well as the original device designers programming. The acceptable model is in a form that can be deployed as an ongoing active cyber defense.

A Comprehensive Web-Based Solution Using Django Framework and SQLite Database

In today's competitive job market, universities play a crucial role in preparing students for successful careers. A well-designed placement cell website serves as a vital bridge between students and potential employers, facilitating seamless communication and fostering employment opportunities. This paper presents the abstract of such a website, aimed at enhancing student employability. The placement cell website offers a user-friendly interface, providing students with easy access to a myriad of resources such as job listings, internship opportunities, and career guidance materials. Employers, on the other hand, can efficiently browse through student profiles and post job openings, creating a dynamic ecosystem for talent acquisition. The website incorporates tools for interview preparation, and skill assessment, empowering students to present themselves effectively in the job market. Furthermore, the website alerts students with relevant job opportunities based on their qualifications and preferences. This personalized recommendation system enhances the efficiency of the job search process, increasing the likelihood of successful placements. To foster collaboration between academia and industry, the website facilitates communication between students, alumni, faculty members, and potential employers through forums, webinars, and networking events. This collaborative environment promotes knowledge sharing, mentorship, and professional development, ultimately enriching the overall student experience.

Reliability analysis of diesel engine cooling system based on improved Bayesian network

For the benefit of solving the problem of absoluteness of conditional probability distribution and difficulty in obtaining basic event probability in Bayesian networks, this paper studies the reliability of diesel engine cooling systems through leakage noise or gate intuitionistic fuzzy Bayesian network. Firstly, the leakage noise or gate is introduced into the intuitionistic fuzzy Bayesian network, which makes the results more realistic. Secondly, prior probability in the Bayesian network is obtained based on the similarity aggregation method of triangular intuitionistic fuzzy numbers. The results show that the introduction of leakage noise or gate, intuitionistic fuzzy set, and Bayesian network can solve the problem that the probability of basic events in a Bayesian network is difficult to obtain. The conditional probability table corrected by leakage noise or gate is more realistic and greatly reduces the workload. It is determined that the two weakest components of the cooling system are the thermostat and the water pump. The results show that the way in this paper can provide support for the reliability analysis of the complex system.

Formation of entrepreneurial values through communication in entrepreneurial interactions in coastal areas

This study examines how entrepreneurial values are fostered through interaction and communication between local and migrant entrepreneurs in coastal tourism areas. The study emphasizes the critical role of a shared understanding of these values, highlighting the need to promote local economic growth and develop a sustainable entrepreneurial ecosystem. Research objectives: This study aims to identify the factors that drive entrepreneurial values among local and migrant entrepreneurs in coastal tourism areas. Methods: A qualitative research approach was used, and data was collected through interviews and observations. The study focused on micro, small, and medium enterprises (MSMEs) operating in Pangandaran. The research shows that essential attributes of business success - such as grit, new ideas, and a willingness to stand on one’s own two feet - come from life experiences and the give-and-take within the community and culture. Both local entrepreneurs and travelers can use social connections and circles as tools for growth and support. At the heart of this discovery? These sociable traits are passed down through different groups, while language skills are spread across many places. Together, they create resilient people skilled in business and entrepreneurship. This Recommendation focuses on increasing collaboration between entrepreneurs through mentoring programs, workshops, and networking events to encourage the exchange of knowledge and experience. These initiatives are expected to increase innovation, competitiveness, and business sustainability in coastal tourism, strengthening the entrepreneurial ecosystem.

Research on the Sentiment Analysis and Evolutionary Mechanism of Sudden Network Public Opinion Based on SNA-ARIMA Model with Text Mining

This article is based on the massive text data in the digital era, using text mining methods to explore the evolution mechanism of online public opinion, in order to achieve the control of public opinion trends in sudden network events and regulate the stability of online and offline public opinion. We introduced time series for decision-making assistance, combined with time series autoregressive integrated moving average model (ARIMA) for prediction, and comprehensively evaluates the evolution of public opinion from two dimensions: sentimental orientation and social network analysis (SNA). Based on this, a new exploration model for public opinion evolution, SNA-ARIMA, is constructed. The research results indicate that the process of public opinion dissemination exhibits distinct phased characteristics, and each stage is comprehensively influenced by different key nodes or factors. This study provides decision support for managing public opinion crises, making the identification of key nodes in online public opinion events, the evolution mechanism of public opinion, and the guidance of public opinion crises more systematic, forward-looking, and scientific.

Developing Soft Skills in the Artificial Intelligence Era: Communication, Business Writing, and Composition Skills

This study explores the development of soft skills in the Artificial Intelligence era. Initially, the study, through an anonymous online survey, explored why students use AI and Large Language Models (LLMs). It was found that students use AI for general and academic purposes. From a general perspective, students use AI and LLMs for (1) convenience, (2) lack of time, and (3) lack of curiosity/interest. From an academic perspective, students use AI and LLM platforms as they (1) lack familiarity/knowledge, (2) lack basic skills, (3) lack confidence, (4) have an eagerness to score high grades, and (5) wish to provide different perspectives. To assist in developing students’ soft skills and discourage possible destructive outcomes in the AI era, the study suggests integrating AI platforms as part of teaching. This integration can be carried out by (1) introducing AI tools to students in a productive manner, (2) aligning the use of AI tools with the curriculum and teaching styles, (3) planning lessons and interactive activities using AI platforms, and (4) using AI tools to provide feedback and vice versa. In communication courses, instructors shall (1) create a supportive environment, (2) organize classroom discussions and debates, (3) create public speaking opportunities, (4) provide room for oral communication practices, (5) integrate the use of technology and multimedia, and (6) provide feedback and reflection. In business writing courses, instructors shall (1) encourage effective communication in classrooms, (2) facilitate collaboration and teamwork, (3) use role-play scenarios, (4) introduce project management tools, (5) teach professional etiquette, and (6) organize networking events. In composition courses, instructors shall (1) embrace technology, (2) teach students to critically evaluate online sources, (3) design assignments that require critical analysis, (4) encourage creative writing assignments, (5) promote imagination and originality, and (6) conduct workshops. These practices, which are provided in line with AlAfnan’s taxonomy of educational objectives, shall assist students in developing their soft skills in a way that maintains the relevance of classroom teaching in the AI era.

Developing a mentoring program to support the next generation of immunologists.

Mentorship refers to the guidance given by a mentor to a less experienced individual to enhance their professional and personal development. For graduate research students, seeking independent mentors external to their institution offers the rewarding opportunity to obtain objective guidance on a variety of work, study and life matters. This article outlines the steps taken to develop a professional society-based, international mentoring program of over 70 participants. This 6-month program aimed to connect graduate research students with more senior academic scientists in response to the limited networking opportunities imposed by the coronavirus disease 2019 (COVID-19) pandemic in Australia. Outlined here are the resources used to maximize the potential of this successful program, which include (1) an 'Introduction to Mentoring' workshop, (2) the use of a mentoring software or communication strategy to maintain program momentum and (3) the integration of in-person networking events. Overall, the program was a great success, with a high satisfaction rating (8.7/10) and a large number of participants reported that they would maintain their mentoring relationship. All participants stated that they would recommend the program to a peer, and thus reiterations of the program would likely be similarly well-received and beneficial to the Australasian immunology community.