bluuebunny/crossref_metadata_2025 huggingface dataset:
Noninvasive, automated and reliable detection of spreading depolarizations in severe traumatic brain injury using scalp EEG
Authors: Chamanzar Alireza , Elmer Jonathan , Shutter Lori , Hartings Jed , Grover Pulkit
Published: October 2022

Background

Noninvasive detection of spreading depolarizations (SD), as a potentially treatable mechanism of worsening brain injuries after traumatic brain injuries (TBI), has remained elusive. Current methods to detect SDs are based on intracranial recording, an invasive method with limited spatial coverage. Less invasive methods to diagnose SD are needed to improve generalizability and application of this emerging science and to guide worsening brain injury treatments. Here, we demonstrate, for the first time, a signal processing paradigm that can enable automated detection of SDs using noninvasive electroencephalography (EEG).

Methods

Building on our previously developed WAVEFRONT algorithm, we have designed a novel automated SD detection method. This algorithm, with learnable parameters and improved velocity estimation, extracts and tracks propagating power depressions, as well as near-DC shifts using low-density EEG. This modified WAVEFRONT is robust to the amplitude outliers and non-propagating depressions on the scalp. We show the feasibility of detecting SD events (700 total SDs) in continuous, low-density scalp EEG recording (95±42.2 hours with 19 electrodes) acquired from 12 severe TBI patients who underwent decompressive hemicraniectomy (DHC) and intracranial EEG that could be used as a ground truth for event detection. We quantify the performance of WAVEFRONT in terms of SD detection accuracy, including true positive rate (TPR) and false positive rate (FPR), as well as the accuracy of estimating the frequency of SDs.

Results

WAVEFRONT achieves the best average validation accuracy of 74% TPR (with 95% confidence interval of 70.8%-76.7%), with less than 1.5% FPR using Delta band EEG. Preliminary evidence suggests that WAVEFRONT can achieve a very good performance (regression with R2≃0.71) in the estimation of SD frequencies.

Conclusions

We demonstrate feasibility and quantify the performance of noninvasive SD detection after severe TBI using an automated algorithm. WAVEFRONT can potentially be used for diagnosis and monitoring of worsening brain injuries to guide treatments by providing a measure of SD frequency. Extension of these results to patients with intact skulls requires further study.
Efficiency of heterogenous functional connectomes explains variance in callous-unemotional traits after computational lesioning of cortical midline and salience regions
Authors: Winters Drew E. , Leopold Daniel R. , Sakai Joseph T. , Carter R. McKell
Published: October 2022

Callous-unemotional (CU) traits are a youth antisocial phenotype hypothesized to be a result of differences in the integration of multiple brain systems. However, mechanistic insights into these brain systems are a continued challenge. Where prior work describes activation and connectivity of the connectome in relation to these systems, new mechanistic insights can be derived by removing nodes and characterizing changes in network properties (hereafter referred to as computational lesioning) to characterize the resilience and vulnerability of the brain’s functional connectome. Here, we study the resilience of connectome integration in CU traits by estimating changes in efficiency after computationally lesioning individual-level connectomes. From resting-state data of 86 participants (48% female, age 14.52±1.31) drawn from the Nathan Kline institute’s Rockland study, individual-level connectomes were estimated using graphical lasso. Computational lesioning was conducted both sequentially and by targeting global and local hubs. We calculated changes in network efficiency after each lesion. Then, elastic net regression was applied to determine how these changes explained variance in CU traits. Follow-up analyses characterized modeled node hubs, examined moderation, determined impact of targeting, and decoded the brain mask by comparing regions to meta-analytic maps. Elastic net regression revealed that computational lesioning of 23 nodes, network modularity, and Tanner stage explained variance in CU traits. Hub assignment of selected hubs differed at higher CU traits. No evidence for moderation between simulated lesioning and CU traits was found. Targeting global hubs increased efficiency and targeting local hubs had no effect at higher CU traits. Identified brain mask meta-analytically associated with more emotion and cognitive terms. Although reliable patterns were found across participants, adolescent brains were heterogeneous even for those with a similar CU traits score. Adolescent brain response to simulated lesioning revealed a pattern of connectome resiliency and vulnerability that explains variance in CU traits, which can aid prediction of youth at greater risk for higher CU traits.
Causality-Enriched Epigenetic Age Uncouples Damage and Adaptation
Authors: Ying Kejun , Liu Hanna , Tarkhov Andrei E. , Sadler Marie C. , Lu Ake T. , Moqri Mahdi , Horvath Steve , Kutalik Zoltán , Shen Xia , Gladyshev Vadim N.
Published: October 2022

Machine learning models based on DNA methylation data can predict biological age but often lack causal insights. By harnessing large-scale genetic data through epigenome-wide Mendelian Randomization, we identified CpG sites potentially causal for aging-related traits. Neither the existing epigenetic clocks nor age-related differential DNA methylation are enriched in these sites. These CpGs include sites that contribute to aging and protect against it, yet their combined contribution negatively affects age-related traits. We established a novel framework to introduce causal information into epigenetic clocks, resulting in DamAge and AdaptAge—clocks that track detrimental and adaptive methylation changes, respectively. DamAge correlates with adverse outcomes, including mortality, while AdaptAge is associated with beneficial adaptations. These causality-enriched clocks exhibit sensitivity to short-term interventions. Our findings provide a detailed land-scape of CpG sites with putative causal links to lifespan and healthspan, facilitating the development of aging biomarkers, assessing interventions, and studying reversibility of age-associated changes.
Trends in opioid seizure data and their association with opioid mortality
Authors: McBrien Heather , Alexander Monica
Published: October 2022

Background

The opioid epidemic remains an emergent health issue in the United States, as opioid-related deaths continue to rise in the second year of COVID-19. The introduction of synthetic opioids into the illicit supply began causing deaths in 2015, however, data describing the illicit opioid supply is scarce.

Methods

We used a newly available national dataset of drug seizure reports, aggregated from law enforcement agencies across the United States, to describe changes in fentanyl, heroin, and other opioid presence in the national illicit supply from 2011-2017, by state and geographic region. We assessed the relationship between drug seizures and opioid-related deaths at the state level using linear regression.

Results

National and state increases in opioid seizure rates from 2011-2017 were entirely due to increased fentanyl and heroin seizures, as other opioid seizure rates remained constant. Most increases in seizures occurred in the Northeast, Midwest, and Appalachia, where fentanyl seizures and heroin seizures were highest and increased most sharply along with opioid deaths. The composition of drugs seized was similar within geographic regions, but did vary across regions. State opioid seizures of all types were strongly associated with state opioid deaths. The strongest relationship was between fentanyl seizures and fentanyl deaths.

Conclusions

The association between opioid seizures and deaths means seizure data has potential as an early-warning system to predict overdose, although national level data requires quality improvement. Regional variation in seizure rates supports existing evidence that illicit fentanyl and heroin supplies differ between regions, producing distinct regional risk environments, causing varying mortality rates.
RNetDys: identification of disease-related impaired regulatory interactions due to SNPs
Authors: Barlier Céline , Ribeiro Mariana Messias , Jung Sascha , del Sol Antonio
Published: October 2022

The dysregulation of regulatory mechanisms due to Single Nucleotide Polymorphisms (SNPs) can lead to diseases and does not affect all cell (sub)types equally. Current approaches to study the impact of SNPs in diseases lack mechanistic insights. Indeed, they do not account for the regulatory landscape to decipher cell (sub)type specific regulatory interactions impaired due to disease-related SNPs. Therefore, characterizing the impact of disease-related SNPs in cell (sub)type specific regulatory mechanisms would provide novel therapeutical targets, such as promoter and enhancer regions, for the development of gene-based therapies directed at preventing or treating diseases. We present RNetDys, a pipeline to decipher cell (sub)type specific regulatory interactions impaired by disease-related SNPs based on multi-OMICS data. RNetDys leverages the information obtained from the generated cell (sub)type specific GRNs to provide detailed information on impaired regulatory elements and their regulated genes due to the presence of SNPs. We applied RNetDys in five disease cases to study the cell (sub)type differential impairment due to SNPs and leveraged the GRN information to guide the characterization of dysregulated mechanisms. We were able to validate the relevance of the identified impaired regulatory interactions by verifying their connection to disease-related genes. In addition, we showed that RNetDys identifies more precisely dysregulated interactions linked to disease-related genes than expression Quantitative Trait Loci (eQTL) and provides additional mechanistic insights. RNetDys is a pipeline available athttps://github.com/BarlierC/RNetDys.git
Patients with ACPA-positive and ACPA-negative Rheumatoid Arthritis Show Different Serological Autoantibody Repertoires and Autoantibody Associations with Disease Activity
Authors: Cunningham Kevin Y. , Hur Benjamin , Gupta Vinod K. , Arment Courtney A. , Wright Kerry A. , Mason Thomas G. , Peterson Lynne S. , Bekele Delamo I. , Schaffer Daniel E. , Bailey Marissa L. , Delger Kara E. , Crowson Cynthia S. , Myasoedova Elena , Zeng Hu , Rodriguez Moses , Weyand Cornelia M. , Davis John M. , Sung Jaeyun
Published: October 2022

Objectives

Patients with rheumatoid arthritis (RA) can test either positive or negative for anti-citrullinated protein antibodies (ACPA), and are thereby ACPA-positive (ACPA+) or ACPA-negative (ACPA–), respectively. Through comprehensive profiling of autoantibodies in serum, we aimed to identify autoantibodies that are differentially abundant between patients with ACPA+ RA and ACPA– RA, and also those that are significantly associated with clinical disease activity.

Methods

Serum was collected from patients with ACPA+ RA (n= 32), ACPA– RA (n= 30), and healthy controls (n= 30). Sengenics Immunome™protein microarray was used to screen for over 1,600 IgG autoantibodies against native, unmodified human proteins from each serum sample. Autoantibody profiles were compared between each RA subgroup and controls to identify differentially abundant autoantibodies (P< 0.05, Mann–WhitneyUtest; |Cliff’s delta (d)| > 0.33). Additionally, the relationship between RA patients’ autoantibody abundances and Clinical Disease Activity Index (CDAI) was examined for correlations between serum autoantibodies and disease activity (|Spearman’sρ| > 0.4 andP< 0.01).

Results

We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA– RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies higher in ACPA+ RA patients and ACPA– RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons. On the other hand, we found 30 and 25 autoantibodies lower in ACPA+ RA and ACPA– RA, respectively, of which eight autoantibodies were common in both comparisons. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with CDAI, but associate differently depending on the presence or absence of ACPA.

Conclusions

ACPA status in patients with RA determines not only the composition of the serum autoantibody repertoire, but also the correlative relationships between autoantibodies and disease activity. Notably, many of the autoantibodies identified herein were reported for the first time. Our findings warrant further investigation into the immunological differences between these two RA subgroups, and shed new light on the possible need for different treatment approaches.
Accessibility of covariance information creates vulnerability in Federated Learning frameworks
Authors: Huth Manuel , Arruda Jonas , Gusinow Roy , Contento Lorenzo , Tacconelli Evelina , Hasenauer Jan
Published: October 2022

Federated Learning (FL) is gaining traction in various fields as it enables integrative data analysis without sharing sensitive data, such as in healthcare. However, the risk of data leakage caused by malicious attacks must be considered. In this study, we introduce a novel attack algorithm that relies on being able to compute sample means, sample covariances, and construct known linearly independent vectors on the data owner side. We show that these basic functionalities, which are available in several established FL frameworks, are sufficient to reconstruct privacy-protected data. Additionally, the attack algorithm is robust to defense strategies that involve adding random noise. We demonstrate the limitations of existing frameworks and propose potential defense strategies analyzing the implications of using differential privacy. The novel insights presented in this study will aid in the improvement of FL frameworks.
Cell type catalog of middle turbinate epithelium
Authors: Mathews Fasil , Keng Tung Victoria Sook , Foronjy Robert , Boruk Marina , Knowles James A , Evgrafov Oleg V
Published: October 2022

Importance

Elucidation of the cellular makeup of the middle turbinate provides a foundation for future studies of pathogenesis of sinonasal disease. Neural progenitors and pluripotent basal cells found in middle turbinate mucosa potentially can be used to develop cellular models to study brain disorders or in regenerative medicine to substitute neuronal tissues.

Objective

Single cell RNA-sequencing (scRNA-seq) of middle turbinate mucosa was performed to create the first single cell transcriptome catalog of this part of the human body.

Design

Samples were obtained from the head of the middle turbinate from healthy volunteers. After the specimen was prepared per lab protocol, cells were dissociated, suspended, and counted. Single cell libraries were then prepared according to the 10x Genomics protocol and sequenced using NovaSeq 6000 (Illumina). Sequencing data were processed using Cell Ranger, and clustering and gene expression analysis was performed using Seurat. Cell types were annotated using known markers and data from other single cell studies.

Setting

Single center, tertiary care center

Participants

Healthy volunteer

Intervention(s) (for clinical trials) or Exposure(s) (for observational studies)

None

Main Outcome(s) and Measure(s)

Identification of cell types of middle turbinate mucosa through expression profiling of single cells using known markers

Results

14 unique cell types were identified, including serous, goblet, club, basal, ciliated, endothelial, and neural progenitor cells, as well as multiple types of blood cells.

Conclusions and Relevance

This catalog provides a comprehensive depiction of the cellular composition of middle turbinate mucosa. By uncovering the cellular stratification of gene expression profiles in healthy middle turbinate epithelium, the groundwork has been laid for further investigation into the molecular pathogenesis and targeted therapy of sinonasal disease.

Key Points

Question

What is the cellular makeup of human middle turbinate mucosa?

Findings

Single-cell RNA sequencing revealed 14 cell types in middle turbinate epithelium, including neural progenitors, a previously unrecognized component of middle turbinate epithelium.

Meaning

Gene expression profiles of middle turbinate mucosa cell types are concordant with other respiratory mucosa transcriptomic data with notable heterogeneity in serous and basal cells.□
A Cross-sectional Analysis of Food Perceptions, Food Preferences, Diet Quality, and Health in a Food Desert Campus
Authors: Aldaz Kaitlyn J. , Ortiz Sigry , Ortiz Rudy M. , Diaz Rios L. Karina , Dhillon Jaapna
Published: October 2022

The sensory properties of foods guide food choices and intake, importantly determining nutritional and health status. In communities that have inconsistent access to nutritious foods, such as food deserts, the food taste perceptions and preferences have yet to be explored. The paucity of data pertaining to food perceptions, preferences, and choices and the complex relationship of socioeconomic status (SES), race/ethnicity, and sex on cardiometabolic and cognitive health warrants further examination. Two hundred fifty participants (aged 18-24 years) living in a food desert campus were recruited for this cross-sectional study where participants underwent taste tests on selected fruits, vegetables, and nuts, and clinical tests (anthropometrics, blood glucose, blood pressure, and endothelial function), cognitive function tests (memory and attention), diet quality assessment (HEI), and food preference and perception assessments. Food taste intensities were influenced by sex with bitter and umami taste intensities of several foods being perceived more intensely by males. Moreover, food liking was largely influenced by ethnicity with Hispanics having higher liking ratings for several foods compared with non-Hispanics. Both, Hispanics and females, had higher total fruit HEI scores and lower attention scores than non-Hispanics and males respectively. Females also had lower blood pressure, reactive hyperemia index, and fasting blood glucose. Food-insecure individuals rated cost and convenience as more important factors for overall food consumption and had lower attention scores than those with higher food-security status. Future research should consider the complex interactions of factors such as taste and flavor perception, sex, ethnicity, prior exposure to foods, and other environmental factors when studying food preferences and health in young adults.
Epidemic graph diagrams as analytics for epidemic control in the data-rich era
Authors: Valdano Eugenio , Colombi Davide , Poletto Chiara , Colizza Vittoria
Published: October 2022

COVID-19 highlighted how modeling is an integral part of pandemic response. But it also exposed fundamental methodological challenges. As high-resolution data on disease progression, epidemic surveillance, and host behavior are now available, can models turn them into accurate epidemic estimates and reliable public health recommendations? Take the epidemic threshold, which estimates the potential for an infection to spread in a host population, quantifying epidemic risk throughout epidemic emergence, mitigation, and control. While models increasingly integrated realistic host contacts, no parallel development occurred with matching detail in disease progression and interventions. This narrowed the use of the epidemic threshold to oversimplified disease and control descriptions. Here, we introduce the epidemic graph diagrams (EGDs), novel representations to compute the epidemic threshold directly from arbitrarily complex data on contacts, disease and control efforts. We define a grammar of diagram operations to decompose, compare, simplify models, extracting new theoretical understanding and improving computational efficiency. We test EGDs on two public health challenges, influenza and sexuallytransmitted infections, to (i) explain the emergence of resistant influenza variants in the 2007-2008 season, and (ii) demonstrate that neglecting non-infectious prodromic stages biases the predicted epidemic risk, compromising control. EGDs are however general, and increase the performance of mathematical modeling to respond to present and future public health challenges.
Persisting low skin prick test prevalence among children receiving periodic anthelminthic treatment after recurrent soil-transmitted helminth infections: a one-year observation
Authors: Lubis Inke Nadia D. , Nasution Masitah , Nasution Rizky Keumala Ansari , Lubis Aridamuriany D. , Yanni Gema Nazri , Trisnawati Yunnie , Sofyan Ferryan
Published: October 2022

Background

The immune system in human develops when they are exposed to severe helminth infections. Chronic soil-transmitted helminth (STH) infection can modulate and suppress allergic reactions particularly by changing the responses from the immune effector. This study observed how STH infections are correlated with allergic reactions as determined by skin prick test (SPT).

Methodology

Fourty-five primary school children with recurrent STH infections (determined by at least two positive results in 4-monthly Kato Katz examination over a year period) who received periodic treatment from Mandailing Natal, were classified as case, and 45 primary school students with no history of STH infections from Medan were classified as control in this study. Positive SPT occurred among 27% and 89% of children in the case and control groups (OR 22, 95% CI 7.032-68.827), respectively. No history of helminthiasis, history of allergy, history of parent’s allergies, and history of sibling’s allergies were associated with increased risks of positive SPT.

Conclusion

Our findings supported the hygiene hypothesis, where decreased exposure to infectious disease pathogens and decreased diversity of microbial exposures in the environment increases the prevalence of allergies, and anthelminthic treatment show limited effect in reversing the protective effect of STH infections to allergies.
Structural snapshots uncover a lock-and-key type conserved activation mechanism of β-arrestins by GPCRs
Authors: Maharana Jagannath , Sarma Parishmita , Yadav Manish K. , Saha Sayantan , Singh Vinay , Saha Shirsha , Chami Mohamed , Banerjee Ramanuj , Shukla Arun K.
Published: October 2022

Agonist-induced phosphorylation of G protein-coupled receptors (GPCRs) is a key determinant for the binding and activation of multifunctional regulatory proteins known as β-arrestins (βarrs). Although the primary sequence and phosphorylation pattern of GPCRs are poorly conserved, the downstream functional responses mediated by βarrs such as receptor desensitization, endocytosis and signaling are broadly applicable across GPCRs. A conserved principle of βarr activation, if any, upon their interaction with different GPCRs harboring divergent phosphorylation patterns remains to be visualized, and it represents a major knowledge gap in our current understanding of GPCR signaling and regulatory paradigms. Here, we present four structural snapshots of activated βarrs, in complex with distinct phosphorylation patterns derived from the carboxyl-terminus of three different GPCRs, determined using cryogenic-electron microscopy (cryo-EM). These structures of activated βarrs elucidate a “lock-and-key” type conserved mechanism of βarr activation wherein a P-X-P-P phosphorylation pattern in GPCRs interacts with a spatially organized K-K-R-R-K-K sequence in the N-domain of βarrs. Interestingly, the P-X-P-P pattern simultaneously engages multiple structural elements in βarrs responsible for maintaining the basal conformation, and thereby, leads to efficient βarr activation. The conserved nature of this lock-and-key mechanism is further illustrated by a comprehensive sequence analysis of the human GPCRome, and demonstrated in cellular context with targeted mutagenesis including “loss-of-function” and “gain-of-function” experiments with respect to βarr activation measured by an intrabody-based conformational sensor. Taken together, our findings uncover previously lacking structural insights, which explain the ability of distinct GPCRs to activate βarrs through a common mechanism, and a key missing link in the conceptual framework of GPCR-βarr interaction and resulting functional outcomes.
Structure-first identification of conserved RNA elements that regulate dengue virus genome architecture and replication
Authors: Boerneke Mark A. , Gokhale Nandan S. , Horner Stacy M. , Weeks Kevin M.
Published: October 2022

The genomes of RNA viruses encode the information required for replication in host cells in both their linear sequence and in complex higher-order structures. A subset of these complex functional RNA genome structures show clear sequence conservation. However, the extent to which viral RNA genomes contain conserved structural elements – that cannot be detected by sequence alone – that nonetheless are critical to viral fitness is largely unknown. Here, we take a structure-first approach to identify motifs conserved across the coding sequences of the RNA genomes for the four dengue virus (DENV) serotypes. We used SHAPE-MaP to identify 22 candidate motifs with conserved RNA structures, but no prior association with viral replication. At least ten of these motifs are important for viral fitness, revealing a significant unnoticed extent of RNA structure-mediated regulation within viral coding sequences. These conserved viral RNA structures promote a compact global genome architecture, interact with proteins, and regulate the viral replication cycle. These motifs are constrained at the levels of both RNA structure and protein sequence and are potential resistance-refractory targets for antivirals and live-attenuated vaccines. Structure-first identification of conserved RNA structure is poised to guide efficient discovery of RNA-mediated regulation in viral genomes and other cellular RNAs.
Fusion event-triggered model predictive control based on shrinking prediction horizon
Authors: Cao Qun , Xia Yuanqing , Sun Zhongqi , Dai Li
Published: October 2022

Purpose

This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.

Design/methodology/approach

A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.

Findings

The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.

Originality/value

The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.
Impression management tactics in Covid-19 related disclosures: a study on the annual reports of Bangladeshi listed insurance companies
Authors: Hossain Dewan Mahboob , Alam Md. Saiful , Mazumder Mohammed Mehadi Masud
Published: October 2022

Purpose

The purpose of this article is to explore the impression management practices in Covid-19 related discourses in the annual reports of the insurance companies in Bangladesh.

Design/methodology/approach

To fulfil this objective, the authors have conducted a discourse analysis of the Covid-19 related corporate narratives in the latest annual reports of listed insurance companies. The findings are then interpreted through the lens of impression management theory, following the impression management strategies identified by Caliskan et al. (2021).

Findings

It is found that companies tried to manage the impression of the stakeholders through the strategic use of language. There is evidence that the companies used assertive and performance-oriented tactics to impress their stakeholders. In few cases, defensive strategies were applied.

Practical implications

This study will facilitate improving the understanding of corporate communication during the Covid-19 crisis. Policymakers will be able to understand the current status of Covid-19 related disclosures and consider the necessity to provide guidance that may lead to better accountability during the crisis.

Originality/value

This study will contribute to the limited literature on Covid-19 related disclosure from the context of developing economies. This research is methodologically novel as it applies discourse analysis and interprets the findings through the lens of impression management.
The role of data platforms in COVID-19 crisis: a smart city perspective
Authors: Radu Laura-Diana , Popescul Daniela
Published: October 2022

Purpose

The Covid-19 pandemic has profoundly affected urban communities, generating the need for an immediate response from local governance. The availability of urban data platforms in some smart cities helped the relevant actors to develop various solutions in an innovative and highly contextual way. The purpose of this paper is to explore the role of data platforms in smart cities in the context of the Covid-19 crisis.

Design/methodology/approach

A total of 85 studies were identified using the Clarivate Analytics Web of Science electronic library. After applying exclusion and inclusion criteria, 61 publications were considered appropriate and reasonable for the research, being read in-depth. Finally, only 52 studies presented relevant information for the topic and were synthesized following the defined research questions. During the research, the authors included in the paper other interesting references found in selected articles and important information regarding the role of data in the fight against Covid-19 in smart cities available on the Internet and social media, with the intention to capture both academic and practical perspectives.

Findings

The authors' main conclusion suggests that based on their previous expertise in collecting, processing and analyzing data from multiple sources, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The results highlight the importance of open data, data sharing, innovative thinking, the collaboration between public and private stakeholders, and the participation of citizens, especially in these difficult times.

Practical implications

The city managers and data operators can use the presented case studies and findings to identify relevant data-driven smart solutions in the fight against Covid-19 or another crisis.

Social implications

The performance of smart cities is a social concern since the population of urban communities is continuously growing. By reviewing the adoption of information technologies-based solutions to improve the quality of citizens' life, the paper emphasizes their potential in societies in which information technology is embedded, especially during a major crisis.

Originality/value

This research re-emphasizes the importance of collecting data in smart cities, the role of the diversity of their sources and the necessity of citizens, companies and government synergetic involvement, especially in a pandemic context. The existence of smart solutions to process and extract information and knowledge from large data sets was essential for many actors involved in smart cities, helping them in the decision-making process. Based on previous expertise, some smart cities quickly adapted their data platforms for an efficient response against Covid-19. The paper analyzes also these success cases that can be considered models to be adopted by other municipalities in similar circumstances.
Sirona Hygiene Private Ltd.: raising a cup to menstrual freedom
Authors: Jayakumar Tulsi , Arora Sunny Vijay
Published: October 2022

Learning outcomes

The learning outcomes of this study are as follows:▪ to explain the marketing of products that fall under “stigmatised” products;▪ to develop a multi-segmentation strategy and identify variables used in segmentation;▪ to identify the target segments;▪ to draw a value proposition canvas;▪ to construct positioning statements; and▪ to decide the product portfolio based on segmentation, targeting and positioning (STP).

Case overview/synopsis

This case considers the dilemma faced by Deep Bajaj, CEO of Sirona Hygiene Pvt. Ltd., a company in the female menstrual and intimate hygiene products space, in May 2021. During an investor meeting, an investor questions Sirona’s focus on menstrual cups (MCs) and advises Deep to expand instead the sanitary pads category. While the company has been growing at more than 100% year-on-year and has also been profitable for the last three years, the case considers how Deep can better participate in the bull run in the Indian menstrual hygiene market. Should he discard menstrual cups from Sirona’s product portfolio and concentrate on sanitary pads – India’s most highly accepted menstrual hygiene product? Alternatively, should he discard sanitary pads from his product portfolio and focus on MCs – his flagship product? Or, could he tap the large and growing menstrual hygiene market to “have his cup and pad too”?

Complexity academic level

This case is suitable for a class of 90 min in an undergraduate course or an extended session of two 90-min classes in a graduate MBA course. It can be studied as part of the STP module in a Marketing Management course. It may also be used in a strategic management course within a graduate MBA program to provide an understanding of the value proposition canvas as part of the module on business model canvas.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS 8: Marketing.
Crowdsourcing initiatives during the COVID-19 pandemic: empirical evidence from the Italian context
Authors: Vermicelli Silvia , Cricelli Livio , Grimaldi Michele , Mignacca Benito , Strazzullo Serena
Published: October 2022

Purpose

Academics and practitioners are increasingly discussing the role of crowdsourcing initiatives in dealing with the challenges imposed by the COVID-19 pandemic, along with their role in an emergency context in general. However, empirical evidence about the role of crowdsourcing initiatives in an emergency context is still scarce. This paper aims to address this gap in knowledge.

Design/methodology/approach

The authors adopted an inductive approach to investigate how companies leveraged crowdsourcing initiatives to address the issues posed by COVID-19. Data were collected through semi-structured interviews. The selection of the interviewees was based on a purposive sampling strategy. Data were analysed through thematic analysis.

Findings

The analysis led to the identification and examination of drivers (e.g. preserving relationships with customers), advantages (e.g. increased demand for services) and disadvantages (e.g. increased platform cost) of implementing crowdsourcing initiatives during COVID-19. By leveraging the findings, this paper suggests future research opportunities. Relevant future research opportunities include: (1) quantitatively evaluating the economic impact of crowdsourcing initiatives during a disruptive event and (2) examining how the sector in which the company operates influences the beneficial and detrimental effects of crowdsourcing initiatives on company performance.

Originality/value

The involvement of crowds as innovation partners has provided unique opportunities for companies to innovate and address the challenging scenario. The scientific literature about the role of crowdsourcing during COVID-19 is growing. However, there is still a scarcity of empirical evidence about the mechanisms underpinning the use of crowdsourcing during the pandemic. By leveraging semi-structured interviews, this paper addresses this relevant gap in knowledge.
Do performance measures matter for stock mutual funds? An international analysis
Authors: Durán Santomil Pablo , Lombardero Fernández Pablo Crisanto , Otero González Luis
Published: October 2022

Purpose

The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

Design/methodology/approach

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

Findings

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

Research limitations/implications

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

Practical implications

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

Originality/value

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.
The role of emotions in B2B product advertising on social media: a family business case study
Authors: Pirraglia Emilio , Giuliani Felice , De Cicco Roberta , Di Berardino Claudio , Palumbo Riccardo
Published: October 2022

Purpose

The outbreak of Covid-19 increased the average time spent on social media (SM). This led to a transformation in how companies manage their digital marketing channels and created additional pressure for business-to-business (B2B) and family businesses, which tend to focus more on personal relationships with customers and stakeholders than on the implementation of digital marketing strategies on SM. The present research examines the case study of a Facebook advertising campaign created to promote the products and business values of an Italian family firm specialising in the production and commercialisation of biostimulants for agriculture.

Design/methodology/approach

The research aims to combine digital marketing avenues (i.e. a Facebook advertising campaign) with established psychological and behavioural theories, such as the dual process theories, by comparing the effects of two promotional videos (emotional vs functional).

Findings

The results suggest that emotional videos generate more passive behaviours, such as views, as well as active behaviours in the form of likes, comments and shares, while functional videos induce people to search for more information about the advertised products.

Originality/value

This is the first study to validate the role of Facebook advertising campaigns in developing an information-based approach to B2B family firms by testing the effectiveness of a targeted campaign comparing the impact of emotional and functional cues on increasing users' engagement while optimising the circulation of video content. The study helps to reduce the academic–practice gap by investigating the example of a fruitful integration between academic research and management practice.
The prevalence of depression among students in higher education institution: a repeated cross-sectional study
Authors: Cheong Wei Shan , Degeras Karunanithy , Suliman Khairul Rizuan , Selvaraju Mohan , Subramaniam Kavitha
Published: October 2022

Purpose

Undergraduate students are known to be a high-risk group for mental health problems. The purpose of this paper is to constitute a repeated cross-sectional study on the trend of depression over the years and factors associated with depression among undergraduates.

Design/methodology/approach

Cross-sectional data from five surveys between 2013 and 2020 (N = 1,578) among the undergraduates of Universiti Tunku Abdul Rahman, a private university in Kampar Malaysia, were combined. The Depression Anxiety and Stress Scale-21 was used to screen for depression. Cochran’s Armitage test was used to detect trend in depression. Logistic regression, random forest regression and extra gradient boosting regression were used to identify risk factors and classification.

Findings

The prevalence of depressive symptoms was found to be between 26.4% and 36.8% between the years with an average of 29.9%. There was no significant time trend in the prevalence. The risk of depressive symptoms was higher among female students, those who were dependent on family for financial support and those who were stressed.

Practical implications

Periodical screening for depression is warranted for the identification of students at risk for depression. Professional cognitive-behavioral therapies, peer support and consulting services should be made available to the students in need.

Originality/value

Depression among students had been studied widely, but the trend over years remains unexplored, especially in developing countries.
Perceived usability evaluation of learning management systems via axiomatic design with a real life application
Authors: Baykasoglu Adil , Felekoglu Burcu , Ünal Ceylin
Published: October 2022

Purpose

Usage of learning management systems (LMSs) has become widespread with the disruption of face-to-face educations after the COVID-19 pandemic. There are several software products, usually named as LMS to enable and support distance education. However, selection of a suitable LMS is a complex multiple criteria decision making (MCDM) problem that requires consideration of many criteria and inputs from different parties like students, academicians, education managers, etc. Usability evaluation of LMS is one of the critical steps in deciding which LMS system to be adapted. There are several studies related to usability evaluation of LMS in the literature, but utilization of MCDM methods and real life case studies are very rare. Based on this motivation, perceived usability evaluation of SAKAI-LMS that is in use at an academic department is performed by employing axiomatic design procedure (ADP). This paper aims to discuss the aforementioned issues.

Design/methodology/approach

ADP is considered as a suitable MCDM method for perceived usability evaluation as it allows an easy approach to data fusion and setting performance targets for decision makers. A questionnaire is developed to collect data from three types of system users about predetermined usability criteria and their importance. After detailed statistical analyses and weighting criteria via analytical hierarch process (AHP), ADP is carried out to evaluate usability of the LMS.

Findings

It is found that the proposed ADP based approach is easy to apply in practical circumstances and able to quantify perceived usability of the LMSs.

Research limitations/implications

The proposed approach provides an easy and practical evaluation of perceived usability of the LMSs for decision makers who are responsible for the implementation of LMSs. The developed novel and practical MCDM-based perceived usability approach for LMS in this study has been verified through a real life case study at an academic department. Perceived usability results, therefore, reflects only the views of this focus group and are not generalizable.

Originality/value

First time in the literature, a comprehensive ADP based MCDM approach is proposed based on the analyses of the related literature and information gathered from the system users.
The impacts of mHealth technology and healthcare e-consultation on workout levels among obese and overweight people post-COVID-19
Authors: Oetoro Samuel , Permadhi Inge , Sumarliah Eli
Published: October 2022

Purpose

The COVID-19 outbreak has worsened the issues of obesity and overweight in Indonesia. Technologies related to mHealth are becoming more popular for its capability to lessen obesity, if enabled by patient-focussed consultation. The paper assesses influential determinants of medium workout for obese and overweight adults post-COVID-19.

Design/methodology/approach

A total of 1,171 participants who self-stated being overweight and called on a health professional in the previous year are chosen using cross-sectional survey. Participants stated their mHealth tracking behaviours, viewpoints regarding obesity, bodily activities and consultation post-COVID-19 epidemic. This study uses structural equation modelling to assess inter-variables relationships.

Findings

Patient–professional e-consultation is substantially related to mHealth tracking adoption and transformations in adults' obesity-associated viewpoints, forecasting adequate workout post-COVID-19. The results indicate the necessity of patient-focussed consultation meetings to incorporate communications about mHealth technology and available techniques of joining in bodily activities.

Originality/value

The research is the first effort to assess primary information from obese and overweight Indonesian adults post-COVID-19 epidemic (January–July 2022). The population can take advantage of pointed health interferences employing mHealth innovations. The results propose that health professionals must involve patients through mHealth technologies and attempt to enhance digital health knowledge to advance bodily activities nationally.
Financial capability and households’ financial vulnerability: evidence for the Spanish case
Authors: Fernández-López Sara , Álvarez-Espiño Marcos , Castro-González Sandra , Rey-Ares Lucía
Published: October 2022

Purpose

The present study examines the potential relationship between financial capability and household financial vulnerability for a sample of Spanish individuals.

Design/methodology/approach

The methodology combines a literature review deepening on the two concepts addressed in this paper – financial vulnerability and financial capability – and an empirical analysis. Based on a sample of 7,811 Spanish individuals taken from the Survey of Financial Competences, different probit regression models are used to test the relationship of key independent variables (namely, financial literacy, financial inclusion, and financial capability) with household financial vulnerability.

Findings

Empirical evidence points to the existence of a negative relationship between financial capability and household financial vulnerability. Besides, the variable on financial capability demonstrates, per se, a greater explanatory power than its two components (i.e. objective financial literacy and financial inclusion) separately, particularly in the case of financial literacy.

Originality/value

This paper contributes to the research on household finances along three main dimensions. Firstly, it enhances the research on financial capability by analysing how it relates to consumers' financial vulnerability; an association barely explored by the extant literature. Secondly, it gets closer to the multifaceted concept of financial vulnerability through a wide set of objective and subjective proxy variables. And thirdly, the empirical evidence found leads to proposing some recommendations aimed at improving households' financial capability.